University of Ghana http://ugspace.ug.edu.gh HYDROCHEMICAL AND ISOTOPIC CHARACTERIZATION OF AQUIFERS IN THE LOWER TANO RIVER BASIN, GHANA, WEST AFRICA. BY ADWOBA EDJAH (10359157) THIS THESIS IS SUBMITTED TO UNIVERSITY OF GHANA, LEGON IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR THE AWARD OF DOCTOR OF PHILOSOPHY IN EARTH SCIENCES JULY 2020 University of Ghana http://ugspace.ug.edu.gh DECLARATION This is to certify that this Thesis is entirely my original work and does not contain any previously published materials except where due reference has been duly made in the text. This Thesis has also not been previously submitted to any other University for the purpose of the award of a Doctor of Philosophy degree. However, portions of this thesis have been published in international Scopus journals. i University of Ghana http://ugspace.ug.edu.gh ABSTRACT The Lower Tano River basin is one of the basins endowed with minerals, oil, and gas resources in West –Africa. It covers 104,000 km2, and the major riparian countries are Ghana and Ivory Coast. The basin, underlain by the Birimian supergroup rocks and the rocks of the Apollonian has enough surface water resources to meet current water demands, but there are many challenges including high population growth rate (due to influx of oil and gas industrial workers), land degradation, mining activities, climate change etc. These challenges have put immense pressure on the groundwater resources in the basin. Also, the surface water is unreliable to meet the basin’s water demand for socio-economic development. This therefore makes groundwater the most cost effective and preferred means of supplying water to the dispersed population and rural settlements across the basin. One probable requirement for a sustainable and efficient management of groundwater is the characterization of aquifers in terms of its quantity, quality, and quantification of the recharge sources. Hence in this study, the aquifer hydraulic parameters were estimated, the overall quality of groundwater including the level of trace elements contamination, and its suitability for domestic and agricultural purposes was assessed, the hydrogeochemical processes that produces the chemical characteristics or compositions of the aquifer system was determined, the sources of recharge to the aquifer was investigated and the ages of groundwater was determined. The methodology used involved pumping tests carried out on 55 boreholes drilled across the basin, yearly sampling of surface water and groundwater resources, measurement of cations, anions, trace elements, stable isotopes of deuterium (δ2 H), oxygen-18 (δ18 O), tritium (3H) and measurement of silica. Pumping test together with Theis (1934) graphical method was used to estimate the aquifer hydraulic parameters (transmissivity, hydraulic conductivity, and specific capacity). From the estimation of the aquifer hydraulic parameters, it was observed that the mean transmissivity, hydraulic conductivity, and specific capacity ii University of Ghana http://ugspace.ug.edu.gh values were 5.96 m2/day, 5.70 m/day and 18.80 L/min/m, respectively. The cations (calcium, sodium, potassium, magnesium) and anions (chloride, bicarbonate, nitrate, and sulphate) show that the aquifer of the Apollonian formation and the Birimian super group produces fresh groundwater with most being soft and few being moderately hard and hard. Na + and SO 2- 4 were the dominant cation and anion in the surface water and ground water sampled in 2016. Likewise, Na+ and HCO - 3 were the dominant cation and anion in the surface water sampled in 2017, the groundwater sampled from 2013 to 2015, and the hand dug wells sampled in 2017. The boreholes sampled in 2017 had Na+ and SO 2-4 as the dominant cation and anion, respectively. All the measured ions (bicarbonates, sulphate, chloride, nitrate, calcium, magnesium, sodium, potassium) in most of the surface water and groundwater sampled from the rocks of the Apollonian and the Birimian supergroup were within the WHO (2011) allowable limits for drinking water. The results of the measured trace elements that is Fe, Pb, Cd, Ni, As, and Al were high in most of the surface water samples. Also, the results of Cu, Cd, Zn, Cr, Fe, Ni, Mn, Co, Pb, As and Al in most groundwater especially those sampled from the aquifer of the Apollonian formation were higher than the WHO (2011) permissible limits for drinking water. The elevated concentrations of trace elements in the surface water and the groundwater were mostly related to geogenic sources. Based on water quality index (WQI) results, it was observed that majority of the groundwater sampled from the aquifer of the Apollonian formation were unsuitable for drinking whiles most groundwater samples taken from the aquifer of the Birimian supergroup were suitable for drinking. As per sodium adsorption ratio (SAR), 99% of the groundwater sampled from both aquifer of the Apollonian formation and the Birimian supergroup were suitable for irrigation. The sodium percent classification indicates that, minority of the groundwater sampled from the aquifer of the Apollonian formation and the Birimian supergroup falls under excellent category for irrigation. Wilcox diagram and magnesium hazard classification indicate that majority of the groundwater especially those sampled from the aquifer of the Apollonian formation gave out iii University of Ghana http://ugspace.ug.edu.gh excellent to good water for irrigation. The residual sodium carbonate and Permeability index classification specify that all the sampled groundwater from the aquifer of the Apollonian formation and the Birimian supergroup were suitable for irrigation. The chlorinity index classification indicates that the aquifer of the Apollonian formation and the Birimian super group produce groundwater that were suitable for irrigation. Graphical including hydrogeochemical modelling and statistical approaches applied in the delineation of the major factors influencing the evolution of groundwater and the general hydrochemical characteristics revealed that the chemistry of groundwater in the Apollonian formation aquifer and the aquifer of the Birimian supergroup was mainly rock weathering and rainfall. In addition, ion exchange processes, rock-water interaction and incongruent dissolution were the major natural factors governing the formation of the groundwater chemistry in the Lower Tano River Basin. However, the occurrence of sulphate implies that sulphide mineral (pyrites, arsenopyrites and chalcopyrite) oxidation or mobilization and mining activities including illegal and legal small-scale mining possibly have an impact on the groundwater chemistry in the Lower Tano River Basin. The hydrochemistry of the sampled groundwater transited from Ca-HCO-3 to Na-Cl water type along a flow direction for the groundwater samples taken from 2014 to 2015 and 2017. For the groundwater sampled in 2016, the hydrochemistry evolved from Ca-HCO - to Ca-SO 2-3 4 water type and then to NaCl water type along the flow direction. The evolution was influenced by ion exchange processes and rock-water interaction. Based on mineral stability diagram, most groundwater in the aquifer of the Apollonian formation and the aquifer of the Birimian super group appears to be stable within the Kaolinite field suggesting ion exchange processes. Stable isotope composition (δ18O and δ2H) of rainwater indicates that the rainwater was not highly evaporated. Also, the slope and intercept of the rainfall regression lines obtained for this study were slightly similar to the local meteoric water line for Ghana and the global meteoric water line. Stable isotope composition (δ18O and iv University of Ghana http://ugspace.ug.edu.gh δ2H) of surface water (rivers, streams, lagoon, and seawater) and groundwater (hand dug wells and boreholes) reveal that the mechanism of recharge to the aquifer of the Apollonian formation and the Birimian supergroup was rapid with the source being meteoric. Also, the surface water (rivers and streams) contributed to the groundwater recharge of the Lower Tano River Basin. Tritium in rainfall ranges from 1.27 to 10.11 TU. That of the rivers ranges from 2.04 to 3.08 TU and that of the groundwater ranges from 0.99 to 6.78 TU. The tritium results revealed that groundwater from the aquifer of the Apollonian formation and the Birimian supergroup were young, of modern recharge with short residence time. Also, the groundwater was recharged between 1960- 1965 and 1965 – 1970. The outcome of this study has added to the current hydrogeological knowledge about Lower Tano River Basin. It has also added to the characteristics of semi-confined and unconfined aquifers. v University of Ghana http://ugspace.ug.edu.gh DEDICATION THIS WORK IS DEDICATED TO MY DAD (ING, KWASI ASEMONE EDJAH) AND MY CHILDREN, KWAW (Junior) KOJO AND NANA YAW (MY THREE ISOTOPES). vi University of Ghana http://ugspace.ug.edu.gh ACKNOWLEDGEMENT I wish to express my profound gratitude to ICTP (The Abdus Salam, International center for theoretical physics), IAEA (International Atomic Energy Agency), and GETFUND (Ghana Educational Trust Fund) for financial assistance for this PhD Programme. I am indeed, invaluably grateful to Prof Barbara Stenni, Giuliano Dreossi (PhD), Giulio Cozzic (PhD), Clara Turetta (PhD), all of Ca Foscari University of Venice Italy and Prof Covelli Stefano of the Department of Mathematics and Geology, University of Trieste, Italy for their strict supervision, untiring efforts, and encouragements throughout my PhD studies. My profound gratitude also goes to Naa Prof Bruce Kofi Banoeng Yakubo, Dr Thomas Tetteh Akiti, and Prof Sandow Mark Yidana, all of University of Ghana for their constructive criticisms and encouragement throughout the studies. My heartfelt appreciation also goes to Prof. Kwabena Doku- Amponsah (Department of Statistics, UG), who took care of my kids whiles analyzing my samples in Italy. I also wish to thank the lecturers and staff of the Department of Environment, Statistics, and Informatics, Ca Foscari University of Venice, Italy, and Daniele Karlicek (PhD) of the Isotope geochemistry laboratory, University of Trieste as well as staff of the Department of Mathematics and Geology, University of Trieste, Italy. I am also grateful to Dr Ofosu (Director, NNRI, GAEC), Dr Dennis Adotey, Prof Shiloh Osae (Deputy Director General, GAEC), Dr Daniel Gyingiri Achel (Deputy Director, RAMSRI), Prof. Daniel Asiedu (Provost, UG), Dr Thomas Armah, Prof Patrick Sakyi, Prof. David Atta-Peters, All of the Department of Earth Science, UG, Dr Kippo (CEO, of Heisa Engineering,) Sir Nash Bentil (Principal Technologist, GAEC), George Crabbe(Senior Technologist, GAEC), Hendrick, Nana Bonsu,Kwabina Ibrahim(UG), Godfred Ayanu (Senior Technologist, GAEC), Edward Awuku Kaka ( Research Scientist,GAEC ), Michael A. Owusu (Catholic Priest, St Patrick Parish, Half Assini) and Dennis Mensah (Farmer, Esiama) for their technical assistance and helpful guidance. I also wish to acknowledge the priceless efforts of Mr. Eric Kufuor, a Senior Driver at the Transport Section of the Ghana Atomic Energy Commission, and all staff of Heisa Engineering. vii University of Ghana http://ugspace.ug.edu.gh TABLE OF CONTENTS DECLARATION ....................................................................................................................... i ABSTRACT .............................................................................................................................. ii DEDICATION ......................................................................................................................... vi ACKNOWLEDGEMENT ...................................................................................................... vii TABLE OF CONTENTS ....................................................................................................... viii LIST OF TABLES ................................................................................................................. xiv LIST OF FIGURES ............................................................................................................. xviii LIST OF ABBREVIATIONS .............................................................................................. xxiii CHAPTER ONE ........................................................................................................................ 1 INTRODUCTION ..................................................................................................................... 1 1.1 Background ...................................................................................................................... 1 1.2 Statement of the Problem ................................................................................................. 3 1.3 Justification ...................................................................................................................... 3 1.4 Aim and Objectives .......................................................................................................... 7 1.5. The Area of Study ........................................................................................................... 8 1.5.1. Study Location .......................................................................................................... 8 1.5.2. Topography, Relief and Drainage System ................................................................ 9 1.5.3. Climate ...................................................................................................................... 9 1.5.4. Land use and Vegetation ........................................................................................ 13 1.5.5. Soil Type ................................................................................................................. 14 1.5.6. Geology .................................................................................................................. 16 1.5.7. Stratigraphy ............................................................................................................ 19 1.5.8. Hydrogeology ......................................................................................................... 20 1.5.9. Socio-economic Activities ...................................................................................... 21 CHAPTER TWO ..................................................................................................................... 22 LITERATURE REVIEW ......................................................................................................... 22 2.1 Introduction .................................................................................................................... 22 2.1.1 Estimation of Aquifer Hydraulic Parameters using Pumping Tests. ...................... 22 2.1.2 Assessing the overall Quality of Groundwater including the level of Trace Element Contamination, and its Suitability for Domestic and Agricultural purposes. ... 25 viii University of Ghana http://ugspace.ug.edu.gh 2.1.2.1 Groundwater Quality and its suitability for domestic and agricultural purposes ....................................................................................................................................... 25 2.1.2.2 Trace Elements Contamination in Groundwater ............................................... 27 2.1.2.3 Sources of Trace Element concentration in groundwater ................................. 30 2.1.2.4 Effects of Trace Elements contamination in groundwater ................................ 30 2.1.3 Determination of the Hydrogeochemical processes that produces the Chemical Characteristics or Compositions of an aquifer system ..................................................... 31 2.1.4 Sources of Recharge to the Aquifer System using oxygen-18 (δ18 O) and deuterium (δ2H).................................................................................................................................. 37 2.1.5 Groundwater Age (residence time) Determination ................................................. 39 2.1.5.1 Sources of Tritium (3H) ..................................................................................... 40 2.1.5.2 Understanding groundwater recharge sources in Ghana using tritium (3H). .... 42 CHAPTER THREE .................................................................................................................. 43 METHODOLOGY ................................................................................................................... 43 3.1. Desk Study ..................................................................................................................... 43 3.2 Field work ....................................................................................................................... 43 3.2.1. Geophysical Sitting ................................................................................................ 43 3.2.2. Borehole Drilling and Development ...................................................................... 44 3.2.3. Pumping Test .......................................................................................................... 45 3.2.4. Sample Collection .................................................................................................. 46 3.2.4.1. Surface water and groundwater sampling for chemical and trace element analysis .......................................................................................................................... 46 3.2.4.2. Rainfall, Surface water and groundwater sampling for stable isotope compositions (δ18O and δ2H) ........................................................................................ 49 3.2.4.3 Rainfall, Surface water and groundwater sampling for Tritium analysis ......... 51 3.2.5. Measurements of Field Parameters ........................................................................ 52 3.2.6. Laboratory Analysis................................................................................................ 56 3.2.6.1. Measurement of Calcium by EDTA (ethylenediaminetetraacetic acid or its salts) titrimetric method at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. ................................................ 56 3.2.6.2. Measurement of Magnesium (Mg2+) using Atomic Absorption Spectrometric (AAS) Method at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. ................................................................ 57 ix University of Ghana http://ugspace.ug.edu.gh 3.2.6.3. Measurement of Total Hardness by Ethylenediaminetetraacetic acid (EDTA) titrimetric method at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. ................................................ 59 3.2.6.4. Measurement of sodium and potassium using flame photometric method at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. ..................................................................................................... 60 3.2.6.5. Measurement of Chloride (Cl-) by MOHR Ajentometric Method at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. ..................................................................................................... 62 3.2.6.6. Measurement of Phosphate using a UV –visible Spectrophotometer at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. ..................................................................................................... 63 3.2.6.7. Measurement of Sulphate using a UV –visible Spectrophotometer at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. ..................................................................................................... 65 3.2.6.8. Determination of Nitrate (NO -3 ) at the Laboratory of Nuclear Chemistry and Environmental Research center, Ghana Atomic Energy Commission. ........................ 67 3.2.6.9. Measurement of Silica in surface water and groundwater at SGS Laboratory in Tema, Ghana ................................................................................................................. 70 3.2.6.10. Measurement of Arsenic (As) in the water samples at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. ................................................................................................................. 70 3.2.6.11 Measurement of trace elements (Cu, Cd, Zn, Cr, Fe, Ni, Mn, Co, Pb, As and Al) in the water samples at the Laboratory of Nuclear Chemistry and Environmental Research center, Ghana Atomic Energy Commission. ................................................. 74 3.2.6.12 Measurement of trace elements (Cu, Cd, Zn, Cr, Fe, Ni, Mn, Co, Pb, As and Al) in the water samples at the Laboratory of Environmental, Informatics and Statistics, Ca Foscari University of Venice, Italy. ........................................................ 78 3.2.6.13 Measurement of Stable Isotopes of Water (δ18 O and δ2 H) using Los Gatos Research instrument at the National Isotope Hydrology Laboratory of the Ghana Atomic Energy Commission. ........................................................................................ 80 3.2.6.14 Picarro Cavity ringdown spectrometer instrument for the measurements of stable isotopes (δ18O and δ2H ) at the Laboratories of Environmental, Statistics and Informatics, Ca Foscari University of Vernice, Italy. ................................................... 83 x University of Ghana http://ugspace.ug.edu.gh 3.2.6.15. Measurements of Tritium (3H) in the water samples conducted at the Laboratory of Geology, University of Trieste, Italy. .................................................... 86 3.2.7. Validation of Data .................................................................................................. 88 3.2.7.1 Treatment of Data ............................................................................................. 88 3.2.7.2. Data analysis and interpretation ....................................................................... 89 3.2.7.3. Spatial interpolation methods ........................................................................... 90 3.3. Limitation of the Study .................................................................................................. 90 CHAPTER FOUR .................................................................................................................... 92 RESULTS AND DISCUSSIONS ............................................................................................ 92 4.1 Estimation of Aquifer Hydraulic Parameters ................................................................. 92 4.1.1 Borehole depths ....................................................................................................... 92 4.1.2 Borehole Yields ....................................................................................................... 93 4.1.3 Groundwater Flow direction ................................................................................... 96 4.1.4 Transmissivity.......................................................................................................... 98 4.1.5 Hydraulic Conductivity ......................................................................................... 100 4.1.6 Specific Capacity ................................................................................................... 101 4.2 Assessing the overall quality of surface water and groundwater together with the level of trace element contamination and groundwater suitability for domestic and agricultural purposes .............................................................................................................................. 103 4.2.1 Surface water chemistry and its suitability for drinking ....................................... 103 4.2.1.1 Results of the field data ................................................................................... 103 4.2.1.2 Results of the Laboratory Data and Alkalinity (as in Bicarbonate) ................ 107 4.2.1.3 Occurrences and Distribution of Trace Elements in surface water (Assessment of surface water contamination) .................................................................................. 116 4.2.1.4 Metallic elements (Cu, Cd, Zn, Fe, and Cr) .................................................... 119 4.2.1.5 Transition metals (Ni, Co, and Mn) ................................................................ 121 4.2.1.6 Toxic Elements (Pb and As) ........................................................................... 122 4.2.1.7 Non-metallic elements (Al) ............................................................................. 124 4.2.2 Groundwater chemistry and its suitability for drinking ........................................ 142 4.2.2.1 Results of the field data ................................................................................... 142 4.2.2.2 Results of the Laboratory analysis (Hydrochemical data) and Alkalinity (as in Bicarbonate) in groundwater ....................................................................................... 151 xi University of Ghana http://ugspace.ug.edu.gh 4.2.2.3 Occurrences and Distribution of Trace Elements in Groundwater of the Lower Tano River Basin (Assessment of groundwater contamination)................................. 170 4.2.2.4 Metallic elements (Cu, Cd, Zn, Fe, and Cr) .................................................... 174 4.2.2.5 Transition Metals (Ni, Mn, and Co) ................................................................ 184 4.2.2.6 Toxic Elements (Pb and As) ........................................................................... 187 4.2.2.7 Non-Metallic Elements (Al) ............................................................................ 189 4.2.3. Pearson Correlation Matrix .................................................................................. 190 4.2.4 Calculation of Water Quality Index (WQI) ........................................................... 208 4.2.5 Groundwater quality for irrigation ........................................................................ 213 4.2.5.1 Sodium Hazard – Sodium Adsorption ratio .................................................... 214 4.2.5.2 Sodium Percentage (Na %) ............................................................................. 217 4.2.5.3. Residual sodium carbonate (RSC) ................................................................. 219 4.2.5.4. Magnesium Hazard (MH) .............................................................................. 220 4.2.5.5 Permeability Index (PI) ................................................................................... 221 4.2.5.6 Chlorinity Index .............................................................................................. 223 4.3 Determination of the Hydrogeochemical Processes that produces the Chemical Characteristics or Compositions of the Aquifers. .............................................................. 224 4.3.1 Geochemical processes controlling the chemistry of groundwater ...................... 225 4.3.1.1. Ficklin diagram .................................................................................................. 225 4.3.2. Hydrogeochemical facies and Evolution ............................................................. 232 4.3.4 Groundwater mineralization Processes .................................................................. 244 4.3.4.1 Rock weathering .............................................................................................. 247 4.3.4.1.1 Cation Exchange ....................................................................................... 251 4.3.4.2 Precipitation (Rainfall) .................................................................................... 254 4.3.5. Hydrogeochemical modelling ............................................................................... 256 4.3.5 Sub -Conclusions ....................................................................................................... 267 4.4. Sources of Recharge to the aquifer system ................................................................. 267 4.4.1 Isotopic composition (δ18O and δ2H) in Rainwater ........................................... 268 4.4.2. Isotopic Composition (δ18O and δ2H) in Rivers .................................................. 272 4.4.3. Isotopic Composition (δ18O and δ2H) in Streams ................................................ 273 4.4.4. Isotopic Composition (δ18O and δ2H) in Lagoons. .............................................. 275 4.4.5. Isotopic Composition (δ18O and δ2H) in Seawater .............................................. 276 4.4.6 Isotopic Composition (δ18O and δ2H) in Groundwater ......................................... 279 4.4.7 Deuterium excess in groundwater of the study area .............................................. 284 xii University of Ghana http://ugspace.ug.edu.gh 4.4.8 Quantification of River water contribution to Groundwater recharge of the study area. ................................................................................................................................. 286 4.4.9 Quantification of sampled stream water contribution to sampled groundwater recharge in the study area ............................................................................................... 292 4.5. Groundwater age determination (Residence time) ...................................................... 294 4.5.1. Tritium concentration results in the sampled Surface water ................................ 295 4.5.2. Results of Tritium concentration in the sampled Groundwater ........................... 297 CHAPTER FIVE .................................................................................................................... 301 CONCLUSIONS AND RECOMMENDATION ................................................................... 301 5.1 General Conclusions ..................................................................................................... 301 5.1.1 Estimation of aquifer hydraulic parameters .......................................................... 301 5.1.2 Assessing the overall quality of groundwater including the level of trace elements contamination and its suitability for domestic and agricultural purposes ..................... 302 5.1.3 Determination of the Hydrogeochemical processes that produces the chemical characteristics or compositions of the aquifer system ................................................... 303 5.1.4 Investigating the sources of recharge to the aquifer system and age determination to understand the recharge sources................................................................................. 305 5.2 Recommendations ........................................................................................................ 306 REFERENCES ....................................................................................................................... 307 APPENDICES ....................................................................................................................... 342 xiii University of Ghana http://ugspace.ug.edu.gh LIST OF TABLES Table 3. 1: MDL for water sample ........................................................................................... 58 Table 3.2: Microwave digestion programme used for the digestion of the water samples ...... 72 Table 3.3: The correlation coefficient of the calibration lines of the trace elements ............... 76 Table 3.4: MDLs for the water samples ................................................................................... 77 Table 3. 5: Percentage recoveries of the various metals analysed ........................................... 77 Table 4. 1: Descriptive statistics of aquifer parameters within the Lower Tano River Basin 92 Table 4.2: Descriptive statistical summary of the field data measured in the River samples (Sampling year: 2016 and 2017) ........................................................................ 104 Table 4. 3: Descriptive statistical summary of the field data measured in the Stream samples (Sampling year: 2016 and 2017) ........................................................................ 105 Table 4. 4: Descriptive statistical summary of the hydrochemical data for the Rivers sampled in 2016 ................................................................................................. 108 Table 4. 5: Descriptive statistical summary of the hydrochemical data for 2016 Stream samples ............................................................................................................... 108 Table 4. 6: Descriptive statistical summary of the hydrochemical data for the Rivers sampled in 2017. ................................................................................................ 109 Table 4. 7: Descriptive statistical summary of the hydrochemical data for the Streams sampled in 2017 ................................................................................................. 109 Table 4. 8: Descriptive statistical summary of trace elements in the Rivers sampled in 2016. ............................................................................................................................ 117 Table 4. 9: Descriptive statistical summary of trace elements in the Streams sampled in 2016. ............................................................................................................................ 117 Table 4. 10: Descriptive statistical summary of trace elements in the Rivers sampled in 2017 ............................................................................................................................ 118 Table 4. 11: Descriptive statistical summary of trace elements in the Streams sampled in 2017 ............................................................................................................................ 118 Table 4. 12: Pearson correlation of chemical and trace elements data for the Rivers sampled in 2016. ............................................................................................................... 126 Table 4. 13: Pearson correlation of chemical and trace elements data for the Streams sampled in 2016. ............................................................................................................... 127 Table 4. 14: Pearson correlation of chemical and trace elements data for the Rivers sampled in 2017. ............................................................................................................... 128 xiv University of Ghana http://ugspace.ug.edu.gh Table 4. 15: Pearson correlation of chemical and trace elements data for the Streams sampled in 2017 ................................................................................................................ 129 Table 4. 16: Descriptive statistics of field parameters for the Boreholes drilled in 2013 ...... 142 Table 4. 17: Descriptive statistics of the field parameters for the Boreholes drilled in 2014 to 2015 .................................................................................................................... 142 Table 4. 18: Descriptive statistics of field parameters for the Hand dug wells sampled in 2016. ................................................................................................................... 143 Table 4. 19: Descriptive statistics of field parameters for the Boreholes sampled in 2016 ... 143 Table 4. 20: Descriptive statistics of field parameters for the Hand dug wells sampled in 2017 ............................................................................................................................ 143 Table 4. 21: Descriptive statistics of field parameters for the Boreholes sampled in 2017 ... 144 Table 4. 22: Descriptive statistics of the hydrochemical data for the Boreholes drilled in 2013 ............................................................................................................................ 151 Table 4. 23: Descriptive statistics of the hydrochemical data for the Boreholes drilled in 2014 to 2015 ................................................................................................................ 152 Table 4. 24: Descriptive statistics of the hydrochemical data for the Hand dug wells sampled in 2016 ................................................................................................................ 152 Table 4. 25: Descriptive statistics of the hydrochemical data for the Boreholes sampled in 2016 .................................................................................................................... 152 Table 4. 26: Descriptive statistics of the hydrochemical data for the Hand dug well sampled in 2017 ................................................................................................................ 153 Table 4. 27: Descriptive statistics of the hydrochemical data for the Boreholes sampled in 2017 .................................................................................................................... 153 Table 4. 28: Classification of Total hardness concentration in the Boreholes drilled in 2013 and 2014 to 2015{After McCarly and Sawyer (1967)} ..................................... 157 Table 4. 29: Classification of Total hardness concentration in the groundwater sampled in 2016 {After McCarly and Sawyer (1967)} ........................................................ 157 Table 4. 30: Classification of Total hardness concentration in the groundwater sampled in 2017 {After McCarly and Sawyer (1967)} ........................................................ 157 Table 4. 31: Descriptive statistical summary of trace elements in the Boreholes drilled in 2013 .................................................................................................................... 171 Table 4. 32: Descriptive statistical summary of trace elements in the Boreholes drilled from 2014 to 2015 ....................................................................................................... 171 Table 4. 33: Descriptive statistical summary of trace elements for Hand dug wells sampled in 2016. ................................................................................................................... 172 xv University of Ghana http://ugspace.ug.edu.gh Table 4. 34: Descriptive statistical summary of trace elements for Boreholes sampled in 2016. ............................................................................................................................ 172 Table 4. 35: Descriptive statistical summary of trace elements for Hand dug wells sampled in 2017. ................................................................................................................... 173 Table 4. 36: Descriptive statistical summary of trace elements for Boreholes sampled in 2017. ............................................................................................................................ 173 Table 4. 37: Pearson correlation matrix of hydrochemical data and trace element data for the Boreholes drilled in 2013. .................................................................................. 191 Table 4. 38: Pearson correlation matrix of hydrochemical data and trace element data for the Boreholes drilled from 2014 to 2015. ................................................................. 192 Table 4. 39: Pearson correlation matrix of hydrochemical data and trace element data for the Hand dug wells sampled in 2016. ....................................................................... 193 Table 4. 40: Pearson correlation matrix of hydrochemical data and trace element data for the boreholes sampled in 2016 ................................................................................. 194 Table 4. 41: Pearson correlation matrix of hydrochemical data and trace element data for the Hand dug wells sampled in 2017 ........................................................................ 195 Table 4. 42: Pearson correlation matrix of hydrochemical data and trace element data for the boreholes sampled in 2017 ................................................................................. 196 Table 4. 43: Relative weight of hydrochemical parameters. .................................................. 209 Table 4. 44: Relative weight of trace element parameters ..................................................... 209 Table 4. 45: Water quality classification and water types based on WQI ............................. 211 Table 4. 46: Sodium Hazard (SAR) and Salinity Hazard for irrigation water (adapted from USSL 1954) ........................................................................................................ 214 Table 4. 47: Suitability of groundwater (hand dug well) for irrigation based on Sodium Hazard (USSL, 1954). ........................................................................................ 214 Table 4. 48: Suitability of groundwater (boreholes) for irrigation based on Sodium Hazard (USSL, 1954). ..................................................................................................... 215 Table 4. 49: Sodium percent classification of groundwater within the lower Tano River Basin (After Wilcox, 1955). ......................................................................................... 217 Table 4.50: Groundwater suitability for irrigation based on RSC (After Eaton, 1950) ......... 220 Table 4. 51: Suitability of groundwater for irrigation based on MH% .................................. 220 Table 4. 52: Groundwater suitability for irrigation based on the Permeability Index (PI) .... 222 Table 4. 53: Characterization of groundwater of the basin based on Piper (1944) Trilinear diagram and Stiff (1951) diagram....................................................................... 236 xvi University of Ghana http://ugspace.ug.edu.gh Table 4. 54: Relationship of dissolved Na+ and Cl- in groundwater sampled from 2014 to 2015 .................................................................................................................... 237 Table 4. 55: Relationship of dissolved Na+ and Cl- in groundwater sampled in 2016. ......... 238 Table 4. 56: Relationship of dissolved Na+ and Cl- in groundwater sampled in 2017 .......... 241 Table 4. 57: Values and HCO -3 / SiO2 values showing the dominant weathering activity of groundwater within the Lower Tano River Basin. ............................................. 264 Table 4. 58: Statistical summary of stable isotope composition in rainfall sampled in January, February, March, August, September, and December (2016 and 2017) within the Lower Tano River Basin. .............................................................................. 268 Table 4. 59: Statistical summary of stable isotope composition in rainfall sampled in April, May, June, July, October, and November (2016 and 2017) within the Lower Tano River Basin. ............................................................................................... 268 Table 4. 60: Statistical summary of stable isotope composition in Rivers sampled in 2016 and 2017 within the Lower Tano River Basin. ......................................................... 272 Table 4. 61: A statistical summary of the isotopic compositions of the rivers sampled in 2016 and 2017. ............................................................................................................ 273 Table 4. 62: A statistical summary of the isotopic compositions of the Lagoons sampled in 2016 and 2017. ................................................................................................... 275 Table 4. 63: A statistical summary of the isotopic compositions of the Lagoons sampled in 2016 and 2017. ................................................................................................... 276 Table 4. 64: A statistical summary of the isotopic compositions of the hand dug wells sampled in 2016 and 2017. ................................................................................. 279 Table 4. 65: A statistical summary of the isotopic compositions of the boreholes sampled in 2016 and 2017. ................................................................................................... 279 Table 4. 66: Proportion of Rivers and Streams to recharge of groundwater samples taken in 2016 .................................................................................................................... 287 Table 4. 67: Proportion of Rivers and Streams to recharge of groundwater samples taken in 2017 .................................................................................................................... 289 Table 4. 68: Statistical summary of tritium content in the surface water and groundwater of the study area. All units are in tritium units (TU). ............................................. 295 xvii University of Ghana http://ugspace.ug.edu.gh LIST OF FIGURES Figure 1. 1 The Tano River at Elubo within the basin, serving as a source of water to the citizens................................................................................................................... 7 Figure 1.2: Map of the Lower Tano River Basin (Drawn using ArcGIS 10.5 software) .......... 8 Figure 1.3: Mean Monthly Rainfall (mm) from 2006 to 2007 in Axim (Data Source: Ghana Meteorological Station) ....................................................................................... 10 Figure 1. 4: Mean Monthly Rainfall (mm) from 2006 to 2015 in Elubo (Data Source: Ghana Meteorological Station) ....................................................................................... 11 Figure 1. 5: Mean Monthly Rainfall (mm) from 2006 to 2017 in Half Assini (Data Source: Ghana Meteorological Station) ........................................................................... 11 Figure 1. 6: Mean Monthly Rainfall (mm) from 2006 to 2014 in Nkroful (Data Source: Ghana Meteorological station) ....................................................................................... 12 Figure 1. 7: Average Monthly Minimum and Maximum Temperature from 2006 to 2017 (Data Source: Ghana Meteorological Station). ................................................... 12 Figure 1. 8: Average Monthly Minimum and Maximum Temperature from 2006 to 2017 (Data Source: Ghana Meteorological Station). .................................................... 13 Figure 1. 9 Location Map of the Lower Tano River Basin (Drawn using ArcGIS 10.5 software). ............................................................................................................. 14 Figure 1. 10: Geological Map of the Lower Tano River Basin with the major rock complexes (Drawn Using ArcGis 10.5 software). ................................................................ 18 Figure 1. 11: A map showing the rock formations of the study catchment (Drawn Using ArcGIS 10.5 software). ....................................................................................... 20 Figure 3.1: VES sounding curves generated as model curves that suit the apparent resistivity values (field curves) for some sites within the Lower Tano River Basin. .......... 44 Figure 3. 2: Geological map of the study catchment with the borehole drilling points (2013 and 2014 to 2015). .............................................................................................. 45 Figure 3. 3: Geological map of the study catchment with surface water and groundwater sampling points (2016) ........................................................................................ 47 Figure 3. 4: Geological map of the study catchment with surface water and groundwater sampling points (2017). ....................................................................................... 48 Figure 3. 5: IAEA donated rain collector mounted at Edjah Villa in Esiama .......................... 50 Figure 3. 6: A fabricated rainfall collector mounted at St Patrick Catholic Church in Half Assini. ................................................................................................................. 51 Figure 3. 7: Determination of alkalinity (as HCO -3 ) on the field by titrimetric method .......... 54 xviii University of Ghana http://ugspace.ug.edu.gh Figure 3.8: Fast Sequential Atomic absorption spectrometer (VARIAN, AA 250 FS, Australia) used for the analysis of trace elements. .............................................. 75 Figure 3. 9: ICP-MS used for the measurement of trace elements in the water samples......... 78 Figure 3. 10: Isotopic composition analysis (δ2 H and δ18 O) of the water samples using Los Gatos DLT-100 Liquid-water Stable Isotope Analyzer. ..................................... 80 Figure 3. 11: Picarro L2130-i used for the measurement of δ18O and δ2H in the water samples with its auto sampler. .......................................................................................... 84 Figure 4. 1: Spatial distribution map of the borehole depths in the major rock complexes of the Lower Tano River Basin drawn using ArcGIS 10.5 Software. ..................... 93 Figure 4. 2: Spatial distribution map of the borehole yields in the major rock complexes of the study area drawn using ArcGIS 10.5 software. ........................................... 95 Figure 4. 3: Empirical relationship between the yield and the depth of the boreholes drilled across the Lower Tano River Basin .................................................................... 95 Figure 4. 4: General groundwater flow direction of the Lower Tano river basin drawn using MODFLOW. ....................................................................................................... 97 Figure 4. 5: Empirical connection between surface elevation and hydraulic heads in the study area. ........................................................................................................... 98 Figure 4. 6: Spatial distribution map of aquifer transmissivity values for the boreholes drilled in the major rock complexes of the study catchment. ...................................... 100 Figure 4. 7: A Spatial distribution map of the aquifer hydraulic conductivity values in the major rock complexes of the study area. ........................................................... 101 Figure 4. 8: Spatial distribution map of the aquifer specific capacity in the major rock complexes of the study area. ............................................................................. 102 Figure 4. 9: Enhanced Pb levels in the rivers and streams sampled in both 2016 and 2017, plotted on the major rock complexes of the study area. .................................... 123 Figure 4. 10: Spatial distribution map of pH in groundwater plotted on the various rock matrixes within the Lower Tano River Basin. .................................................. 147 Figure 4. 11: Spatial distribution map of TDS values in groundwater plotted on the various rock matrixes within the Lower Tano River Basin. .......................................... 149 Figure 4. 12: Spatial distribution map of EC (µS/cm) concentrations in groundwater plotted on the various rock matrixes within the Lower Tano River Basin. .................. 151 Figure 4.13: Spatial distribution map of calcium concentrations in groundwater plotted on the various rock matrixes within the Lower Tano River Basin .............................. 155 Figure 4. 14: Spatial distribution map of magnesium concentrations in groundwater drawn on the various rock matrixes within the Lower Tano River Basin. ....................... 157 xix University of Ghana http://ugspace.ug.edu.gh Figure 4. 15: Spatial distribution map of sodium concentration in groundwater drawn on the various rock matrixes within the Lower Tano River Basin ............................ 160 Figure 4.16: Spatial distribution map of K+ concentration in groundwater drawn on the various rock matrixes within the Lower Tano River Basin. ............................ 162 Figure 4. 17: Spatial distribution map of Chloride concentrations in groundwater drawn on the various rock matrixes within the Lower Tano River basin. ........................ 164 Figure 4. 18: Spatial distribution map of bicarbonate content in groundwater drawn on the various rock matrixes within the Lower Tano River Basin. ............................ 166 Figure 4. 19: Spatial distribution map of sulphate concentration in groundwater drawn on the various rock matrixes within the Lower Tano River Basin. ............................ 167 Figure 4. 20: Spatial distribution map of nitrate content in groundwater drawn on the various rock matrixes within the Lower Tano River Basin. ......................................... 169 Figure 4. 21:Spatial distribution map of copper (Cu) content in groundwater drawn in the various rock matrixes within the study catchment. ........................................... 175 Figure 4. 22: Spatial distribution map of Cd concentrations in groundwater drawn on the various rock matrixes within the Lower Tano River Basin. ............................. 177 Figure 4. 23: Spatial distribution map of Zn content in groundwater drawn on the various rock matrixes within the Lower Tano River Basin. ......................................... 179 Figure 4. 24: Spatial distribution map of iron content in groundwater plotted on the various rock matrixes of the study catchment................................................................ 184 Figure 4. 25: Spatial distribution map of Ni concentrations in groundwater plotted on the various rock matrixes of the study area............................................................. 185 Figure 4. 26: Spatial distribution map of Mn in the groundwater plotted on the various rock matrixes of the study area.................................................................................. 186 Figure 4. 27: Spatial distribution Map of lead content in the groundwater plotted on the various rock matrixes of the study catchment. .................................................. 188 Figure 4. 28a Spatial distribution map of water quality index WQI) for groundwater sampled from 2013 to 2015. ............................................................................................ 211 Figure 4. 29: The quality of water for irrigation in relation to Salinity Hazard and Sodium Hazard based on USSL (1954). ......................................................................... 216 Figure 4. 30: Spatial distribution map of groundwater suitability for irrigation based on SAR. ........................................................................................................................... 216 Figure 4. 31: Spatial distribution map of groundwater suitability for irrigation based on Na%. ........................................................................................................................... 218 xx University of Ghana http://ugspace.ug.edu.gh Figure 4. 32: Wilcox diagram for classifying the suitability of groundwater for irrigation.219 Figure 4. 33: Spatial distribution map of groundwater suitability for irrigation in the study area based on MH%. ......................................................................................... 221 Figure 4. 34: Groundwater suitability for irrigation based on Doneen permeability Index (PI) (Doneen 1964) (HDW =hand dug wells, BH =Boreholes) ............................... 222 Figure 4. 35: Groundwater suitability for crop production in the study area based on Chlorinity index (Ramesh et al. (2012)) (HDW = hand dug wells, BH = Boreholes) ......................................................................................................... 223 Figure 4. 36a: Durov diagram (1948) of boreholes drilled from 2014 to 2015 within the Lower Tano River Basin. .............................................................................................. 228 Figure 4. 37: Ficklin diagram (Ficklin et al.1992) showing variations in trace element concentrations as a function of pH for the groundwater in the study area. ...... 226 Figure 4. 38a: Piper (1944) and Stiff (1951) diagram showing the transition of groundwater chemistry along a flow direction (2014 – 2015) ............................................... 234 Figure 4. 39a Gibbs (1970) diagram indicating the general mechanisms of groundwater evolution ............................................................................................................ 246 Figure 4. 40: Relationship between Cl- and Na+ in the sampled groundwater within the study area. ................................................................................................................... 248 Figure 4. 41: Relationship between Na+ and HCO - 3 in the sampled groundwater within the study area. ......................................................................................................... 248 Figure 4. 42: Relationship between (Ca + Mg) vs (SO42- + HCO3-) in the sampled groundwater within the study area. ................................................................... 249 Figure 4. 43: Relationship between Ca2+ + Mg2+ – HCO - - SO 2-3 4 and Na-Cl for the sampled groundwater within the study area (2014 – 2017). ........................................... 250 Figure 4. 44: Relationship between Na+ +K+ and Total cations in the sampled groundwater within the study area. ........................................................................................ 251 Figure 4. 45a: Bivariate plot for studying cation exchange in the sampled groundwater (2014 – 2015) within the Lower Tano River Basin ..................................................... 252 Figure 4. 46: Bivariate diagram for cation exchange reaction in groundwater within the study area .................................................................................................................... 254 Figure 4. 47: Relationship between Na/Cl and EC in the sampled groundwater within the Lower Tano River Basin. .................................................................................. 255 Figure 4. 48: Saturation index of carbonate minerals in the groundwater within the Lower Tano River Basin............................................................................................... 257 xxi University of Ghana http://ugspace.ug.edu.gh Figure 4. 49: Saturation index of silicate minerals in groundwater within the Lower Tano River Basin. ....................................................................................................... 258 Figure 4. 50: Saturation index of alumino silicates in groundwater within the Lower Tano River Basin. ....................................................................................................... 259 Figure 4. 51a Calcium stability diagram for groundwater samples within the Lower Tano River Basin ........................................................................................................ 260 Figure 4. 52: Spatial distribution map of SI (Gibbsite – K-feldspar) in the sampled groundwater within the Lower Tano River Basin. ............................................ 267 Figure 4. 53a Schematic plot of δ2H versus δ18 O for rainfall sampled in January, February, March, Aug, September, and December, 2016 and 2017. ............................... 270 Figure 4. 54: Average monthly humidity in the study area from 2006 to 2017 (Data from Ghana Meteorological Authority) ................................................................................ 271 Figure 4. 55: Isotopic compositions in the rivers sampled in 2016 and 2017 within the Lower Tano River Basin. ............................................................................................. 273 Figure 4. 56: Isotopic compositions in the streams sampled in 2016 and 2017. ................... 275 Figure 4. 57: Isotopic compositions in the Lagoon sampled in 2016 and 2017. ................... 276 Figure 4. 58: Isotopic compositions in seawater sampled in 2016 and 2017. ....................... 277 Figure 4. 59: Isotopic compositions in the hand dug wells sampled in 2016 and 2017. ...... 280 Figure 4. 60: Isotopic compositions in the boreholes sampled in 2016 and 2017. ................ 281 Figure 4. 61: Spatial distribution map of δ18O‰ values in the sampled groundwater of the study area. ................................................................................................................... 284 Figure 4. 62: A cross plot of d-excess‰ against δ18O‰ in surface water and groundwater of the study area..................................................................................................... 286 Figure 4. 63a: Spatial variation of River contribution to 2016 groundwater recharge in the study area. ......................................................................................................... 291 Figure 4. 64a: A Spatial variation map of stream contribution to 2016 groundwater recharge in the study area. .................................................................................................... 293 Figure 4. 65: Tritium concentration in the sampled rainwater of the Lower Tano River Basin ........................................................................................................................... 297 Figure 4. 66: Spatial distribution map of tritium concentrations (TU) in ground water of the study area. ......................................................................................................... 299 xxii University of Ghana http://ugspace.ug.edu.gh LIST OF ABBREVIATIONS AAS Atomic Absorption Spectrophotoscopy ACi Groundwater Acidification AMD Acid Mine Drainage ANC Acid Neutralizing Capacity CAI Chloro alkaline Indices CWSA Community Water and Sanitation Agency EDTA Ethylene diamine tetracetic acid GAEC Ghana Atomic Energy Commission GMWL Global Meteoric Water Line IAEA International Atomic Energy Agency ICP-MS Inductively coupled plasma mass spectrometry LMWL Local Meteoric Water Line NANC Net Acid Neutralizing Capacity NE North East NNRI National Nuclear Research Institiute NW North West RAMSRI Radiological and Medical Sciences Research Institute SE South East SI Saturation Indices SW South West WHO World Health Organization WRC Water Resources Commission xxiii University of Ghana http://ugspace.ug.edu.gh CHAPTER ONE INTRODUCTION 1.1 Background Groundwater resources accessed through hand dug wells and boreholes are the major sources of water supply for all socio-economic activities in the Lower Tano River Basin of Ghana. In the basin, almost 80% of the citizens depend solely on hand dug wells and mechanized boreholes or hand pump fitted boreholes for their daily water supply, while the remaining 20% depends on rainwater, rivers, and streams {WRC (Water Research Commission), 2012}, but most of these surface water bodies have issues with colour and turbidity as shown in Figure 1.1. The change in colour and the turbidity might be resulting from human activities and that might give rise to water borne diseases such as typhoid fever, bilharzia, and other carcinogenic diseases etc. (WHO, 2011). Since groundwater is believed to be of a better quality (Anim- Gyampo et al., 2019; Ewusi et al., 2017; Asante Annor & Ewusi, 2016; Atta-Darkwa, 2016; Affum et al., 2015; Nyarko et al., 2015; Edjah et al., 2015) and requires little or no treatment, it is chosen by most policy makers in charge of water resources as the best source of potable water. This is the case of the Lower Tano River Basin where non-governmental agencies like Tullow oil and Christian organizations have made it their aim to provide mechanized and boreholes fitted with hand pump to supply quality water for the service of the communities. The development of hand dug wells, boreholes and other groundwater access infrastructure within the basin started well before Ghana gained independence. However, it is worth noting that there are now over 600 of such facilities in the area (Unpublished reports from Community water and sanitation agency (CWSA, 2013). The involvement of organized non-governmental agencies, churches, and the central government agencies in the development of groundwater resources in the Lower Tano River Basin in recent times has not led to improvement in the generation of reasonably good datasets 1 University of Ghana http://ugspace.ug.edu.gh such as the lithological data, water quality data, and aquifer hydraulic parameter data etc. This is due to lack of organized data. If the above data were organized and adequately processed, the hydrogeological conditions of the rocks would have been characterized and that would have led to prudent management of groundwater resources in the Lower Tano River Basin. In general, even though, the aquifers in the basin produce groundwater of acceptable quality for most uses (Edjah et al., 2015), there are some communities where the quality is hampered by elevated concentrations of trace elements (Edjah, 2012; Doyi et al., 2018). These trace elements are mostly believed to be of geogenic and/or anthropogenic origin. However, it is not known the extent to which each of these two factors has contributed to the current state of groundwater quality in the area. Increasing anthropogenic activities and the rise in demand for groundwater resources implies that concerns about the resource quality will even increase in the future. Though it is part of the drilling protocol {Rural Water Supply Network (RWSN), 2010} to assess the quality of water before its use, little attempt has been made to monitor changes in the ground water quality. Moreover, a holistic assessment of the hydraulic properties of the groundwater bearing units within the basin, the general factors influencing groundwater hydrochemistry and quality, the mode, spatial and temporal distribution of groundwater recharge are required to form the basis for prudent management of the resource to ensure sustainability. The present study therefore seeks to fill the above knowledge gaps by using pumping test data, hydrochemical and isotope data to characterize various aspects of the hydrogeological conditions and general groundwater resources occurrence in the Lower Tano River Basin. This will facilitate decision making on groundwater resource allocation and it will add to the current baseline information about the aquifers in the Tano Bain. The outcome of this study will contribute to the appropriate development of future groundwater systems within the basin. 2 University of Ghana http://ugspace.ug.edu.gh 1.2 Statement of the Problem The Lower Tano River Basin with its numerous rivers is located along the coast in southwestern Ghana and it is occupied by three districts, namely Ellembelle, Jomoro and Nzema East. The basin is endowed with minerals such as gold, kaolin, limestones etc. The basin is the hub for oil and gas industries as well as mining including legal and illegal small-scale mining. These two has increased the population due to influx of industrial workers and migration of people. In 2010 population census, approximately 298,436 (60, 828 for Nzema East, 87,501 for Ellembelle and 150.107 for Jomoro districts) people were counted (Ghana Statistical service, 2012). The endlessly growing population over the years will put immerse pressure on the available groundwater resources leading to high demand for groundwater. Sustainable development goal (SDG) 6 states that “portable water must be provided for all citizens”. However, this goal is somewhat challenging to attain with respect to the Lower Tano River Basin as there is limited information on the available borehole logs. As a result, most agencies develop boreholes with inadequate processed data on the quantity of water the aquifer yields and the quality. To achieve SDG (6), broad and in-depth knowledge of the Lower Tano River basin dynamics of water use and availability is necessary. Current exploitation and sustainable management of groundwater are only possible with a deep knowledge of the complex dynamics that locally characterize the aquifers of the Lower Tano River Basin. 1.3 Justification Knowledge of aquifer hydraulic parameters, groundwater quality, hydrogeochemistry, groundwater recharge and abstraction levels has become one of the essential issues to safe guard the sustainable use of groundwater resources in the Lower Tano River Basin. Understanding the above are of crucial importance for an effective development and management of groundwater resources within the Tano Basin (WRC, 2012). In the Lower Tano River Basin, estimating the aquifer hydraulic parameters will deliver a quantitative prediction for aquifer response to recharge and groundwater abstraction. One 3 University of Ghana http://ugspace.ug.edu.gh of the suitable methods used in calculating the aquifer hydraulic parameters is pumping test (Hasan et al., 2018 b). The use of Pumping test as a method to estimate the aquifer hydraulic parameters is limited in the study area due to lack of pumping test data. This has made it difficult to predict future groundwater availability. For proper development of any groundwater resource, an understanding of the aquifer hydraulic parameters is important . This is because, when the parameters are understood, the success rate of groundwater development increases. Likewise, when the aquifer hydraulic parameters are known, it is very easy for policy makers and scientists to locate suitable sites for groundwater development. Several authors across the globe have suggested that the estimation of aquifer hydraulic parameters can be highly valuable (Purvance & Andricevic, 2000; Chen & Hubbard et al., 2001; Soupios et al., 2007; Sinha et al., 2009; Batte et al., 2010; Majumdar & Das, 2011; Niwas & Celik, 2012; Sikandar & Christen, 2012; Ugada et al., 2013b; Attwa et al., 2014; Sattar et al., 2016; Hasan et al., 2018b, etc.), since the parameters depend on heterogeneity and pore- space structures. Information on the aquifer quality will not only sustain human and aquatic life but it will contribute to the suitability of groundwater for socio-economic uses. An aquifer is often threatened by population growth, change in land use, agriculture and change in climate. Apart from the above, mining is another contributor, which is rampant in the Lower Tano River Basin. Many studies in Ghana have shown a direct link between mining and trace elements contamination in groundwater (Doyi et al., 2018; Ewusi et al., 2017; Asare – Donkor et al., 2016; Antwi-Agyei et al., 2009; Asanti et al., 2007, etc.). Sulphide bearing rocks which contain gold ore are extensive in the Lower Tano River Basin (Luebe et al., 1990). These rocks frequently contain pyrite and arsenopyrites (Smedley et al., 1995). Exposure of these rocks to the atmosphere habitually results in the generation of acid- mine drainage. When these rocks are in contact with the atmosphere, there is high proportions of toxic trace element mobilization in the aquifer. 4 University of Ghana http://ugspace.ug.edu.gh The indiscriminate use of mercury and other chemicals during mining operations, which are harmful to human health (WHO, 2011), is another problem confronting the water resources within the basin. This is because during mining operations, the miners use simple methods to extract and process the gold (Esdaile & Chalker, 2018). Waste water or effluents from their activities might leach into the aquifer through natural processes like rainfall and that could possibly elevate some trace elements contents in the aquifers and the surrounding surface water bodies. In the Lower Tano River Basin most mining operations especially illegal small-scale mining is usually located along the banks of most rivers and streams and their activities have great impacts on these rivers and streams, polluting the groundwater through leaching (Karmakar et al., 2012; Dorleku et al., 2018). For instance, 80% of water samples collected and analysed from some communities within the Lower Tano River Basin, precisely Ellembelle district by Edjah (2012) and Doyi et al. (2018) contained heavy metal (Pb, Cd, Fe, Mn, and As) concentrations significantly above the drinking water standards of WHO (2011). The presence of these trace metals in the groundwater is a threat to human health. Despite previous research on the susceptibility of groundwater to contamination, the results obtained are difficult to interpret due to the limited study area in which the studies covered. Subsequently, due to fewer literatures in the Tano basin especially in the Lower Tano River Basin about groundwater quality and its suitability for socio-economic uses, it has become difficult to obtain a clear understanding of the groundwater quality. In general, aquifers are becoming more important and critical to human and aquatic life (Olago, 2018). However, inadequate knowledge of the aquifer characteristics and sources (Banoeng- Yakubo et al., 2011; Olago, 2018) means that groundwater is being over exploited under growing uncertain regimes (McDonald & Roger, 2009). With restricted evidence, it is impossible to achieve safe water for rural settlement (Yan et al., 2016). This is the case of the Lower Tano River basin, where the aquifers are strongly dependent on rainwater and surface 5 University of Ghana http://ugspace.ug.edu.gh water for recharge (WRC, 2012) but the aquifer is not characterized. In order to describe the aquifer, there is a need for sufficient evidence based on the understanding of the hydrogeology. This will give a better understanding of the aquifer potential for a sustainable supply of safe water for various uses under rapidly climatic change and groundwater development. Although the Lower Tano River basin depends largely on groundwater, limited comprehensive hydrogeochemical studies have also been carried out. Apart from Edjah et al. (2015) and Edjah et al. (2019) who worked in the Lower part of the Tano Basin, there have not been any detailed studies on the hydrogeochemistry of the aquifer systems. An adequate and a fellow up knowledge on the aquifer hydrogeochemistry are important for proper aquifer characterization and management. Although isotopic research has been conducted in different locations across the basin by Edjah et al.(2015, 2019), a distinct quantification of aquifer recharge especially from local precipitation has not been conducted as well as the ages of groundwater. It is therefore important to understand the aquifer system by combining pumping test data, hydrochemical data, and isotopic data to the current methods used in characterizing an aquifer. To describe the aquifer in the Lower Tano River Basin, new boreholes will be drilled, pumping test will be carried out, samples will be collected from the new boreholes and existing groundwater (hand dug wells and boreholes), the samples will be analyzed in various laboratories in Ghana and beyond and the results will be interpreted with the help of software tools like Aquachem, ArcGIS 10.5 software, AquaSolve, and Phreeqc. Findings of this research after a successful completion will (a) assist policy makers to evaluate old sites and seek new sites for the development of groundwater resources (b) it will help policy makers to evaluate various strategies for water resource planning, development, and management (c) will expand the knowledge of hydrogeology and the application of isotopes in the Tano Basin (d) evaluate various strategies for groundwater management and pollution control. 6 University of Ghana http://ugspace.ug.edu.gh Figure 1. 1 The Tano River at Elubo within the basin, serving as a source of water to the citizens. 1.4 Aim and Objectives The broader goal of this project is to contribute to the hydrogeology of the Lower Tano River Basin in South-Western Ghana, to assist in optimal decision-making regarding groundwater resources management to ensure sustainability. This overarching objective includes groundwater quality and quantity issues in the terrain. The specific objectives of this study are to: 1. Estimate aquifer hydraulic parameters; 2. Assess the overall quality of groundwater including the level of trace elements contamination, and its suitability for domestic and agricultural purposes; 3. Determine the hydrogeochemical processes that produces the chemical characteristics or compositions of the aquifers; 4. Investigate the sources of recharge to the aquifers; 5. Determine the ages (residence time) of groundwater. 7 University of Ghana http://ugspace.ug.edu.gh 1.5. The Area of Study 1.5.1. Study Location The Lower Tano river basin carved out of the Tano Basin is in the South Western zone of Ghana, approximately 260 km west of the capital Accra. The basin lies within latitude 4°40’ and 5°20’ north of the equator and longitude 2°05’ and 2°35’ west of the Greenwich meridian (Fig 1.2). The basin is accessed from Accra by driving 200 km on the main coast high way to Cape Coast and from Cape Coast to Takoradi, and from there to a further 80 km on a paved road to the villages in Axim all the way to Elubo and 8 km from Esiama to Bomuakpole and a further 7 km of unpaved road from the villages of Teleku-bokazo to Salman. The catchment area covers a total of 2812 sq. Km, which constitute about 6.8% of the total land, mass of the Western Region of Ghana {GSS (Ghana Statistical Service), 2010} and extends beneath a coastal ridge from Ankobra Township towards the Ivory-Coast boundary. From the map of Ghana (Figure 1.2), it is observed that the Lower Tano River Basin is in a deposition environment. Figure 1.2: Map of the Lower Tano River Basin (Modified after Ghana Geological Survey Authority, (GSSA, 2010) 8 University of Ghana http://ugspace.ug.edu.gh 1.5.2. Topography, Relief and Drainage System The topography of the study region is characterized by relatively flat land in the coastal zone, which gives way to few peaks in the middle to northern sections of the basin. The highest elevations are in the northern parts and the environs of the eastern parts. In the coastal terrain of the study catchment, altitudes range between zero at the boundary with the Gulf of Guinea to about 150 m above mean sea level. Similarly, the study area lies within the wet evergreen (southeast) and the moist-semi-deciduous agro-ecological zones (AEZ) of Ghana (Ghana Geological Survey Department (GGS, 2009). The southern part of the basin has the thickest vegetation, which appears largely continuous. About 60% of the land cover is enclosed by forests, which are largely protected areas (forest reserves). In the wet evergreen forest area is the Ankasa Resource Reserve. In the middle to northern halves of the basin, the forest cover is relatively sparse and much more scattered. In addition, several rivers and streams drain across the basin and noticeable among them is the Ankobra River and the Amanzure River. The major tributaries of the Amanzura River are Ahama River, the Nwini River, the Ankasa River, the Draw River and the Tano River. In the basin, the Amanzura river and some minor rivers and streams allow flow of water throughout the year. These streams and rivers exhibit a dendritic outline that forms the Lower Tano river basin (Ghana Geological Survey Department (GGS), 2009). 1.5.3. Climate The Climate o f the study area is sub-equatorial wet (WRC, 2012) with two rainfall seasons. The wettest months are May to July and September to October. The drier period is from December to February. Data obtained from the Ghana Meteorological Agency (GMA) indicates that the total annual amount of rainfall from 2006 to 2017 is 6443.8 mm. Additionally, the annual rainfall pattern ranges from 32.8 mm to 87.2 mm (Figure 1.3) in Axim, whiles that of Elubo varies from 22.1 9 University of Ghana http://ugspace.ug.edu.gh mm to 46.6 mm (Figure 1.4). In Half Assini, the annual rainfall patterns vary from 19.1 to 116.8 mm (Figure 1.5) and in Nkroful, it ranges from 33.4 to 78.7 mm (Figure 1.6). The monthly mean minimum temperature ranges from 22.6 °C to 25.9 °C (Figure 1.7) whiles the mean monthly maximum temperatures range from 27.3 ° C to 31.9 ° C (Figure 1.8). The coldest month happens in June, while the hottest month occurs in December to March. The basin is moist and warm with comparative humidity between 75 % - 85 % throughout the year. The mean yearly potential evapo- transpiration is about 1322 mm. Two wind systems are experienced in the basin and these are the southwestern monsoon and dry harmattan winds. Figure 1.3: Mean Monthly Rainfall (mm) from 2006 to 2007 in Axim (Data Source: Ghana Meteorological Station) 10 University of Ghana http://ugspace.ug.edu.gh Figure 1. 4: Mean Monthly Rainfall (mm) from 2006 to 2015 in Elubo (Data Source: Ghana Meteorological Station) Figure 1. 5: Mean Monthly Rainfall (mm) from 2006 to 2017 in Half Assini (Data Source: Ghana Meteorological Station) 11 University of Ghana http://ugspace.ug.edu.gh Figure 1. 6: Mean Monthly Rainfall (mm) from 2006 to 2014 in Nkroful (Data Source: Ghana Meteorological station) Figure 1. 7: Average Monthly Minimum and Maximum Temperature from 2006 to 2017 (Data Source: Ghana Meteorological Station). 12 University of Ghana http://ugspace.ug.edu.gh Figure 1. 8: Average Monthly Minimum and Maximum Temperature from 2006 to 2017 (Data Source: Ghana Meteorological Station). 1.5.4. Land use and Vegetation In the study area, agricultural with extensive cocoa farming is practiced mostly in the forest areas (Figure 1.9). Within the forest belt, logging is another important industry and it is mostly carried out in concessions granted to timber companies. Fuel obtained from wood is the main source of energy for the inhabitants and this is harvested mainly from the forests. This has considerably reduced the forest cover since 1960 (Ahn PM, 1961; GSD 2009). Currently, the existence of agriculture (50 %), human settlements (urban and suburban developed lands) (10 %), and forest (40 %), are the estimated major land use types in the study area (Ghana Statistical Service (GSS, 2012). The main vegetation as described by Ghana survey department (GSD, 2009) and Water Resources Commission (WRC, 2012), is coastal and wet semi – deciduous rain forest. The wet semi – deciduous rain forest can be seen in the northern part of the study area but as one travels southward, it turns into secondary forest and it is characterized by tall trees with grass cover, shrubs, and soft woody types. In addition, rattan and bamboo are some of the non-timber forest 13 University of Ghana http://ugspace.ug.edu.gh products that can be seen and several timber species can be found in the study area. The Savanna vegetation is also situated along the coastline, which is approximately 140 km. Figure 1. 9: Location Map of the Lower Tano River Basin (Modified after Ghana Geological Survey Authority, (GSSA, 2010) 1.5.5. Soil Type The soils in the basin consist of five groups. These are the forest lithosols, regosols, podsols, alluviusols, and forest oxysols (Brammer, 1962). The location of the forest lithosols develops on steep slopes and have extensive exposure of hard rock and iron pan. The soils are shallow or brushy and have very little agricultural significance. The soil covers a wide area within the basin, mostly the forest and savannah belts. The forest belt is seen in the northern part of the study area and the Savanna belt is found along the coast. The Savanna belt stretches from Kikam to Half Assini. The forest oxysols occur normally in high rain forest zones. They are deeply weathered to a depth of approximately 4 m (Ahn PM, 1961). They are mostly orange brown to yellowish brown. Organic matter concentration in the forest zones is described to be moderately low but 14 University of Ghana http://ugspace.ug.edu.gh more intensely distributed (Brummer, 1962). Further, these soils are highly leached due to high rainfall amount, thereby reducing their nutritional contents. Though the forest oxysols have good physical characteristics, their use in the production of crops is limited due to the strong acidic reaction in the soil. As such plantations like oil palm, coconut, rubber, and coffee that are acid tolerant are mainly grown in such soils. In the study area, the forest oxysols cover all areas of the basin including the coastal belt and they occur in the hinterlands of the basin thus from Sanwoma through to Elubo. The regosols are limited to a thin strip along the coastal zone of Ghana. They are deep sands established in an outward costal ridge land scape. The regosols are extremely acidic and deprived of nutrients. They contain quartzite and they support good coconut plantations due to the high quantity of rain. The texture of their sands offers good rooting condition for the growth of the coconut palm that has wide roots. In the basin, the regosols can be found along the coast. In old in-filled lagoons, the groundwater podsols are developed. They can locally be identified along the seashore. The profile consists of humus, which is approximately 5 cm in depth, and stained sand, which is approximately 60 cm in depth. The profile of the podsol also consist of bleached sand that is abruptly underlain by a dark brown organic pan. Beneath the pan, gray to brown sandy soils can be seen. Subsequently, the soils belong to the Atuabo series and the groundwater podsols is found in Atuabo through to Twenen in the southwestern part of the basin (Ahn PM, 1961). In the basin, alluvisols border a network of most rivers and streams (Ahn PM, 1961). The top soils of alluvial sediments are mostly sandy, loamy, or clayey textured. In addition, their lithology is discontinued and likely consist of buried horizons. Their locations in flood plains limit their agricultural use. Locally, they are used for the cultivation of sugar cane. In areas that fall under alluvisols, the dry season vegetable garden is common. Hence, in the study area, alluvisols cover areas from Aniwafutu to Elubo. The soils from the alluvial deposits in the basin 15 University of Ghana http://ugspace.ug.edu.gh belongs to the Fredericksburg association, Tikobo association, and Ankasa association (Ahn PM, 1961). 1.5.6. Geology The Geological Survey Department (GSD) of Ghana, in partnership with Bundesanstalt fur Geowissenchaften and Rohstoffe, Hannover, Federal Republic of Germany have come out with a new Geological Map of Ghana that talks about four major rock complexes namely: i. Paleoproterozoic Supracrustal and intrusive rocks made up of Birimian Supergroup, Tarkwaian Group, Tamnean Plutonic Suite and the Eburnean Plutonic Suite. These groups of rocks are described to be formed between 2195 Ma and 2072 Ma. ii. Neoproterozoic to Early Cambrian, comprising the Voltaian Supergroup, Bombouaka Group, Oti-Pendjari Group and the Obusum Group at the top. iii. Pan African Dahomeyide orogenic belt consisting of the Togo Structural Unit, a variety of gneisses of the Dahomeyan Supergroup and the Buem Structural Unit. iv. Coastal Sedimentary Basins of Ordovician to Cretaceous age comprising Sekondian Group, Accraian Group, Amisian Group and Apollonian Group. From the above, the geological formation underlying the upper part of the Lower Tano River basin is the Paleoproterozoic Supracrustals and Intrusive rocks made up of the Birimian Super group rocks and the Tarkwain formations (Figure 1.10). In addition, the geological formation underlying the Lower Part of the basin is the Coastal Sedimentary Basin of Ordovician to Cretaceous age, comprising of the rocks of the Apollonian formations (Figure 1.10). The Birimian Super group rocks which dominates the hinterland of the study area appears to be folded with a dominant northeast trend and are interfered by granitoids, greywacke, interbedded greywacke-phyllite, undifferentiated Biotite (± hornblende, ± muscovite), gneiss, Muscovite, Hornblende – biotite granitoid etc. (Kesse, 1985; Leube et al., 1990; Hirdes et al., 1992; Taylor et al., 1992). The rocks of the Birimian Super group are strongly foliated, and 16 University of Ghana http://ugspace.ug.edu.gh jointed with connected intense weathering along with weak zones and fractures (Kesse, 1985; Leube et al., 1990; Hirdes et al., 1992; Taylor et al., 1992). The structure can enable percolation of water to improve the storage of groundwater (Kesse, 1985; Leube et al., 1990; Hirdes et al., 1992; Taylor et al., 1992). In addition, the Birimian Supergroup is characterized by isoclinally folded and thickly-bedded metavolcanic rocks and metasedimentary rocks. The metavolcanic rocks overly the metasedimentary rocks and contain generally rocks from volcanic origin, which are dominated by lavas and tuffs and pyroclastics rocks. The metasedimentary rocks form the basement of the Birimian Supergroup and are mainly composed of phyllite, schist, and slate (Dapaah-Siakwan, 2003). The Tarkwaian Supergroup, which is the deficient suit of rocks in the study area displays synclinal structures. It is mainly composed of coarse-grained young sedimentary rocks that have undergone low-grade metamorphism. Consequently, the metasedimentary arrangements in the Tarkwaian Supergroup consist of quartzites, phyllites, conglomerates, sandstones, etc. that are interrupted by igneous rocks such as quartz, porphyry gabbro, dolerite, felsite etc. in some places (Kesse, 1985; Leube et al., 1990; Hirdes et al., 1992; Taylor et al., 1992). Additionally, the Tarkwaian Supergroup has a tectonic connection with the Birimian Supergroup, which is revealed by elevated degree of cropping along the contact zones with most of the crop-related gold deposits hosted in these zones (Junner et al., 1942). Kesse (1985), and Hirdes and Luebe (1989), summarized the literature on the Tarkwaian formation up through the mid-1980's. More recent data is also presented in Eisenlohr & Hirdes, 1992; Oberthur, 1994. Additionally, the rocks of the Tarkwaian formations represent erosional products of the Birimian Super group rocks and are dominated by coarse clastic sediments. They are slightly folded and metamorphosed with some level of openings along the joints, and that makes the Tarkwaian formation permeable for groundwater development and storage (Eisenlohr & Hirdes, 1992; Oberthur, 1994). 17 University of Ghana http://ugspace.ug.edu.gh The rocks of the Apollonian formation which dominates the coastal zone of the study area consist of clay (SiO2 and Al2 O3), fossiliferous sandy limestone interbedded with limestone, sandstone, marl (CaCO3), siltstone, and shale with basal conglomerates (Figure 1.11 and Kesse, 1985). This group forms part of the Coastal Sedimentary Basin and their Basement rocks belong to the Pre-Cambrian metamorphosed rocks of the Birimian Super group. Kitson, 1928 reported that “the rocks of the Lower Tano River Basin are part of the Apollonian System of Cretaceous age and consist mainly of alternating clays and sands with limestones. The limestones within the basin are fossiliferous and are inter bedded with clay (Junner, 1940; Cox, 1952). This clay forms a continuous crest that rises from the beach of Keegan and run in a north-westward direction to the north of Nawuley and north of the Tano River in Ekpu. The coastal zone of the Lower Tano River Basin consists of tertiary deposits of clays, laterite and sands and these overlain the inter bedded and fossiliferous limestones (Cox, 1952). In addition, nodules of pyrite or marcasite in the clays and shales of the Apollonian formations was discovered by Atta-Peters et al. (2014) Figure 1. 10: Geological Map of the Lower Tano River Basin with the major rock complexes (Modified after Ghana Geological Survey Authority, (GSSA, 2010) 18 University of Ghana http://ugspace.ug.edu.gh 1.5.7. Stratigraphy In the Tano basin, deposition of rocks started throughout the Aptian ages of early cretaceous era (Luebe et al., 1990). This agrees to the period of continental rifting between the African plate and the South American plate, which lead to the creation of the Tano basin inside the Atlantic Ocean. The above makes the Lower Tano River basin a region of focus for the deposition of clastic sediment from the African continent. A Palynostratigraphical study carried out by Amoo (2014) and Atta-Peters (2013) to determine the stratigraphy of the Tano basin using oil wells indicate that the stratigraphy started with the deposition of sandstone during the early Aptian age with a mix of shale which formed the basement rocks, with a depth of 7000 ft to 9000 ft. One of the earlier studies conducted by Khan (1974), on a borehole in the Lower Tano River basin revealed the following, that is (a) The sedimentary rocks within the basin has a maximum thickness of 3048 m or more along the coast and towards the border of Côte d'Ivoire, (b) The oldest rocks encountered during the study was of middle Cretaceous age, (c) The maximum depth of 1768 m was found in the marine rocks, (d) An angular discordance separated the non-marine stratigraphy from the marine stratigraphy (e) Two horizons with signs of oil were seen. One was near the surface of the Nauli (Nawulley) Limestone Horizon and the other was the Black-Shale Horizon which had the highest depth. 19 University of Ghana http://ugspace.ug.edu.gh Figure 1. 11: A map showing the rock formations of the study catchment (Modified after Ghana Geological Survey Authority, (GSSA, 2010) 1.5.8. Hydrogeology Sufficient hydrogeological information could not be obtained from the Tano Basin to enable describe the hydrogeology of the Lower Tano River basin. This is due to available borehole records being scanty and unavailability of detailed pumping test records. However, a baseline study carried out by WRC (2012) in the Tano Basin indicates that, the rocks of the Apollonian contains alluvial material, which forms part of the isotropic and heterogeneous unconfined aquifer. They also identified hydrogeological features similar to those of the Pra Basin with transmissivity values ranging from 5.7 m2 /day to 799 m2/day, and the yields ranging from 37.5 L/min to 200 L/min. For a generalized idea about the hydrogeology of the Lower Tano River Basin, borehole records and pumping test results will be obtained from this study through drilling. The methodology to be used will be discussed in chapter 3 and the results obtained from the pumping test data will be used to compute the aquifer hydraulic parameters and that will be discussed in my first specific objective. 20 University of Ghana http://ugspace.ug.edu.gh 1.5.9. Socio-economic Activities In the study area, the main occupation of the citizens is fishing and this takes 40 % of the labour force. In addition, 20% of the labour force are into agriculture particularly cocoa, rubber farm, cassava, oil palm, cocoyam, coconut, and plantain. Most farming is done on a small scale mainly for household consumption and the excess are sold for extra income. Forests within the basin make significant contribution to employment, rural income, and trade. This is done through Non-timber Forest Products (NTFPs). Other rural employment generated for the inhabitants include self-employment and jobs generated from timber processing factories. The transportation and manufacturing sector provides an average of 8% employment to the citizens. Also, about 12 % of the citizens are involved in menial daily jobs which include illegal small- scale mining activities. Equally, the mining industries absorb 10 % of the citizens and the oil and gas industries absorbs the remaining 10 % (Ghana Statistical Service, 2012). 21 University of Ghana http://ugspace.ug.edu.gh CHAPTER TWO LITERATURE REVIEW 2.1 Introduction The literature review in this section provides a broad coverage of subjects related to the thesis topic. The review considers (a ) the estimation of aquifer hydraulic parameters using pumping test, (b) assessing the overall quality of groundwater including the level of trace elements contamination, and its suitability for domestic and agricultural purposes, (c) determining the hydrogeochemical processes that produces the chemical characteristics or compositions of an aquifer, (d) Investigating the sources of recharge to an aquifer system and (e) Determine the ages of groundwater to understand the levels of abstraction. Each of the above represents an integral part in defining the overall aim of this research work. 2.1.1 Estimation of Aquifer Hydraulic Parameters using Pumping Tests. Pumping test method is commonly used for computing aquifer hydraulic parameters (Todd, 1980) though other methods such as bail tests, slug tests, and tracer tests are employed for this purpose. The normal practice in a pumping test is to pump a borehole at a specified discharge rate and observe the draw down recovery rate in an observation well located at some distance from the pumping borehole. The obtained drawdown data can then be used to estimate the aquifer hydraulic parameters by employing Theis (1934) method, Cooper-Jacob's (1946) methods and other methods. One of the challenges encountered when conducting a pumping test is keeping the discharge rate constant. This is because the discharge rate tends to vary slightly when there is (a) an increase in discharge head, (b) fluctuations in electric power supply to the pump motor and (c) fluctuations in voltage. Across the globe, (Boulton, 1954, 1963; Prickett, 1965; Neuman, 1972, 1974; Neuman, 1975; Nwankwor et al., 1992, ; Moench, 1995; Heidari & Moench, 1997; Chen & Ayers, 1998; Meier et al.(1998); Grimestad, 2002; Zhan & Zlotnik, 2002; Wu et al., 2005; Kollet & Zlotnik, 2005; 22 University of Ghana http://ugspace.ug.edu.gh Hunt, 2006; Tartakovsky & Neuman, 2007; Akaha & Promise, 2008; Ishaku et al., 2009; Attwa et al., 2014; Rao et al., 2015; Hamidu et al., 2016; Akhter & Hasan, 2016; Okon et al., 2018; Hasan et al., 2020; Suprapti & Pongmanda, 2020), various methods including pumping test have been used to estimate the aquifer hydraulic parameters for efficient groundwater development and management. Across Ghana, especially in the rocks of the Birimian formations, Yidana et al. (2013) used steady state numerical groundwater flow model to estimate the aquifer hydraulic parameters in a crystalline aquifer system in Southern Ghana. The outcome of the author’s research provided a general framework for understanding the hydrogeology of Southern Ghana. Also, in the Tolon and Wa districts of Northern Ghana, Abdul-Ganiyu et al. (2017) used Theis (1934) graphical type curve method to estimate the transmissivity of two boreholes. The authors monitored the pumping tests, barometric and absolute pressures using non- vented water level sensors for a one-year period (2015 to 2016). Their results indicate that the aquifer in the Wa district is of granitoid intrusions while that of the Tolon district is of Voltaian province. Their estimated transmissivity values for both Wa and Tolon districts were 0.5m2/day and, 0.8 m2/day respectively. They also concluded that the yields for both boreholes were enough for domestic water supply. Asante-Annor (2018) used Cooper-Jacob (1946) graphical method for unsteady state flow graphical test method to estimate the hydraulic conductivity, transmissivity, and specific capacity in Assin and Biriman districts of Ghana. Their results show a strong positive correlation between specific capacity and hydraulic parameters (transmissivity and hydraulic conductivity). In this study, Theis (1934) curve matching method will be used to estimate the aquifer hydraulic parameters. To do this, a plot will be assumed on a semi-logarithmic paper including the relationship between the residual drawdown (∆s’) and (t/t’) and the fitted straight line passing 23 University of Ghana http://ugspace.ug.edu.gh through the plotted points. t is the time in minutes including the recovery time period and the total pumping period, t’ is the time of recovery (min) that is the time in which the pumping process was stopped. The transmissivity of the aquifers will be determined by 2.3 𝑄 𝑇 = 4𝜋∆𝑠′ From the equation above, the residual drawdown difference measured in meter per log cycle of t/t’ is characterized by ∆s’ and Q is the discharge rate. The above equation reflects accuracy when calculating the aquifer hydraulic parameters. This is because the level of water in the borehole becomes normal and prevents fluctuation of the borehole water during pumping. In this study, the aquifer of the Apollonian is assumed to be unconfined and that of the Birimian is assumed to be confined. Since the aquifer of the Apollonian is assumed to be unconfined, the obtained drawdown data would have to be corrected using the equation: 𝑆2 𝑆′ = 𝑆 − 2ℎ Where S is the recorded drawdown and h is the aquifer saturated thickness. The above equation will be used based on the above assumptions. Hence to account for the change in transmissivity that occurs in both aquifers, especially the aquifer of the Apollonian formation, the drawdown must be corrected from the above equation. Estimating the aquifer hydraulic parameters in this study will be the first of its kind in the Lower Tano River Basin and the outcome will add to the current knowledge about the hydrogeology of the Lower Tano River Basin. 24 University of Ghana http://ugspace.ug.edu.gh 2.1.2 Assessing the overall Quality of Groundwater including the level of Trace Element Contamination, and its Suitability for Domestic and Agricultural purposes. 2.1.2.1 Groundwater Quality and its suitability for domestic and agricultural purposes In evaluating and classifying the quality of both surface water and groundwater, the characteristics of chemical and trace element concentrations play an important role. This may reveal immense information regarding the environments through which the water resources have circulated (Appelo & Postma, 1999). During the past decade, various geochemical methods, and chemical indices {water quality index (WQI), Sodium adsorption ratio (SAR)}, Percent sodium, Magnesium hazard (MH), Kelly ratio (KR), Wilcox diagram} have been effectively used to evaluate the quality of groundwater and its suitability for irrigation and domestic purposes (Pazand & Javanshir, 2014; Fijani et al., 2016; Barzegar et al., 2016; Kavurmac & Ustun, 2016). In Ghana, particularly in the Birimian supergroup, Yidana et al. (2012), applied spatial analytical and multivariate statistical techniques to hydrochemical data to aid in the classification of groundwater quality control parameters in the Voltaian and Birimian aquifers in northern Ghana. They determined groundwater suitability for commercial, domestic, and irrigation uses. The findings of Yidana et al. indicated that, the Birimian aquifer is more suitable for irrigation due to generally low salinities. Also, in southwestern and coastal basins of Ghana, Darko et al. (2013) used water quality index (WQI) based on chemical and microbiological data to classify the overall ambient water quality at 19 different stations. The obtained results indicated that most groundwater in southwestern and coastal basins in Ghana were good for drinking and domestic purposes. In the near shore coastal zone of Accra, Nyarko et al. (2015) applied WQI, based on chemical and microbiological data to assess the quality of groundwater. Their results suggest that 25 University of Ghana http://ugspace.ug.edu.gh groundwater in the coastal zone of Accra were poor to grossly polluted and not suitable for aquatic life and recreation. Affum et al. (2015) applied hydrochemical data to explain the quality of groundwater in parts of the Western Region of Ghana. They reported hardness, salinity pollution, and toxic elements as the key factors affecting groundwater quality. Also, according to the authors, 79% of arsenic concentration and 43% of cadmium content exceeded the WHO guidelines of 0.01 mg/L and 0.03 mg/L for suitability. Atta-Darkwa (2016), investigated the quality of groundwater for irrigation in Ejisu- Besease in the Oda River Basin. The author analyzed physicochemical parameters and interpreted the result with Percent sodium, sodium adsorption ratio, Kelly ratio, and Magnesium hazard. Result obtained indicated that EC ranges from 186 to 638 µS/cm, TDS was less than 500 mg/L, Na% varied from 20.55 to 44.09%, SAR values ranged from 0.34 to 0.86 meq/L, KR content varied from 0.13 to 0.44 and MH values ranged between 25.86% to 55.29%. The application of Wilcox, 1955 diagram and USSL, 1954 diagram in the study revealed groundwater in the Oda River Basin was of good quality for irrigation. In the Lambussie-Karni District of Ghana Annor et al. (2018) investigated the suitability of groundwater for irrigation. In their works, sixteen boreholes were sampled and sodium adsorption ratio (SAR), residual sodium carbonate (RSC), sodium percentage (Na %), permeability index (PI) and irrigation quality water index (IQWI), was used to classify the suitability of groundwater for irrigation. Results of the chemical indices indicated that groundwater in Lambussie-Karni District of Ghana was generally suitable for irrigation. Further, in the Atankwidi catchment of the White Volta Basin in Ghana, Anim-Gyampo et al. (2019) investigated the suitability of groundwater for drinking and irrigational purposes. In their study, twenty-six boreholes were sampled, and heavy metal concentrations, and physicochemical constituents were determined. Chemical indices such as water quality index, 26 University of Ghana http://ugspace.ug.edu.gh salinity, chlorinity, sodium adsorption ratio, residual bicarbonates, magnesium hazards, and permeability indices were employed by the authors. The authors also estimated the hazard index, hazard quotient, and cancer risk of the analyzed heavy metals. The estimation was done to assess the potential carcinogenic risk to human health. According to the authors, 80% of groundwater in the Atankwidi catchment was potable and suitable for irrigation. Apart from the above authors, a lot of studies to investigate the quality of groundwater and its suitability for socio-economic uses have been carried out across Ghana (Ackah et al., 2011; Salifu et al., 2017; Agyemang, 2019; Chegbeleh et al., 2020). 2.1.2.2 Trace Elements Contamination in Groundwater The occurrence of trace elements contamination in groundwater has become a problem of increasing concern. This situation has arisen because of increasing population, migration, expansion of industries, exploitation of natural resources, modern agricultural practices, and abuse of environmental regulations. Trace elements have some relationship between public health and the composition of water, which may be related to neither natural condition nor contamination (Karanth, 1987). Additionally, trace elements contribute to groundwater quality from a variety of anthropogenic and natural geogenic sources ( Ramessur, 2000; Newcomba et al., 2002; Abollino et al., 2004; Leung & Jiao, 2006). Problems associated with trace metal contamination in water were first emphasised in countries with advanced industries due to their huge industrial discharges (Kurland et al., 1960; Goldberg 1976). After, various studies have focused on analyzing the normal trace element concentrations in groundwater in order to separate natural as well as anthropogenic causes that disturb the groundwater quality and also define the interactions that occur in an aquifer (Hussain et al., 2008; Shahab et al., 2016; Mahmood et al., 2015; Okogbue et al. 2012; Aghazadeh & Mogaddam, 2010; Kord et al., 2013; Narany et al., 2014; Masoud, 2014; Uddameri et al., 2013; Yadav et al., 2014; Sarikhani et al., 2015; Qing et al., 2015; Golchin 27 University of Ghana http://ugspace.ug.edu.gh & Azhdary Moghaddam, 2016; Cao et al., 2016; Ehya & Marbouti, 2016 Sethy et al., 2016; Jacintha et al., 2016; Rehman et al., 2018; Peng et al., 2019; Gu et al., 2020). In Ghana, in spite of the relatively low level of industrial activities, there is nevertheless a growing awareness on the need for sustainable groundwater development and management. This becomes even more important in view of rampant small-scale mining (legal and illegal). Existing information on various groundwater contamination in Ghana showed that most surface water and groundwater are contaminated with trace elements (Tay & Momade, 2006; Ato et al., 2010; Obiri-Danso et al., 2009; Tiimub et al., 2012; Bempa, 2014; Cobbina et al., 015); Amu-Mensah et al., 2019). However, information on groundwater contamination in the Lower Tano River Basin is limited. This therefore demonstrates the need for a more precise, and specific review of the occurrence of trace metals in various aquifers within the basin. This will aid to the understanding of trace element loads and its distribution from geogenic and anthropogenic sources into the aquifer - for an effective management especially the quantities, qualities and pollution control. The need to assess the level of trace metal contamination in groundwater in the rocks of the Birimian supergroup of Ghana in which the basin lies has led to the initiation of several research work in various universities and scientific institutions across Ghana. Hence, the decision to review trace metal contamination in groundwater in the aquifer of the Birimian supergroup and the Apollonian formation is as a result of the need to have a holistic approach that could influence future control strategies in the Lower Tano River Basin. In the Birimian supergroup, one of the earliest studies carried out by Amasa (1975) examined trace elements content in drinking water within the Obuasi gold mining area and found high levels of Arsenic (As) concentrations in groundwater. 28 University of Ghana http://ugspace.ug.edu.gh This was followed up by Akoto Bamford et al. (1990). According to the authors, heavy metal pollution (Mn, Fe, Cr, Cu, Zn, As, Pb, Rb, Sr, Y, Zr and Nb) in gold ore tailings and sediments was in a range of 0.08 to 49000 μg/g, whereas Zn and Fe was detected in water at levels of 0.08–2.4 μg/ml. Pelig Ba et al. (1991) assessed the level of groundwater contamination from the Accra plains and the upper regions of Ghana and found groundwater with elevated Pb, Cr and Fe concentrations. Pelig Ba, (1998) also analyzed groundwater from some crystalline rocks in the Upper Region of Ghana and identified Al, Fe, Zn, Sr, and Ba to be excessively higher in natural water systems. Tay, (2006) conducted a survey on the levels of trace elements (Cu, Hg, Ni, Pb, Fe, Mn, Fe, Zn, Cr, Cd, Mg and Ca) content in surface water and groundwater in the Northern parts of the Ashanti gold belt. According to the author, correlation between trace elements revealed expected process-based relationship derived mainly from the geochemical and biochemical processes within the aquifer system. Armah et al. (2011) spatially assessed the distribution of heavy metals in surface water and groundwater within the study catchment of the Tarkwa mining area using interpolation techniques in a geographical information system environment. According to the authors, most of the surface water and groundwater had high levels of As, Pb, Cd, Mn and Fe. Edjah (2012) found high concentrations of Pb, Fe, Mn and Cd in groundwater in some communities within the Lower Tano River Basin. Anim –Gyampo et al. (2014) reported high levels of Pb and Cd in groundwater of the Bunpkurugu-yunyo district of Ghana. 29 University of Ghana http://ugspace.ug.edu.gh Boateng et al. (2015) used multivariate statistical model and pollution evaluation indices as a complementary tool to identify the various possible sources of pollution that influence the quality of groundwater. Tay et al. (2016), reported high values of Aluminum, selenium, cadmium, lead, iron, manganese, and mercury in groundwater located in the Lower Pra River basin of Ghana. Doyi et al. (2018) reported high values of lead, cadmium and nickel in groundwater and zinc, cadmium and Iron in soil located in some communities within the Lower Tano River Basin. 2.1.2.3 Sources of Trace Element concentration in groundwater Trace metals enter the aquifer system through natural (geogenic) and anthropogenic sources. Entry may be because of direct discharges into surface water bodies that leaches into the aquifer systems by natural processes. Another way of entry is through indirect directions such as wet and dry deposition as well as runoff. In view of the toxicity of trace metals, it is important to understand their sources and its effects on an aquifer. Some anthropogenic sources of trace metal contamination in groundwater includes effluents from mining, domestic, industries, storm water runoff, leaching of metals from garbage and solid waste dump sites, burning of fossil fuels, industrial emissions, incineration of wastes and activities from petroleum industries. 2.1.2.4 Effects of Trace Elements contamination in groundwater Trace metals such as Fe, Mn, Zn, and Cu are essential for the growth and well-being of humans (WHO, 2011). However, they are likely to show poisonous effects when humans and living beings are exposed to levels higher than the normal requirements of WHO. Other elements such as Pb, Hg and Cd are not essential for metabolic activities but exhibit carcinogenic properties (WHO, 2011). Most published data on the effects of trace metals on human health report adverse effects at concentrations (Boateng et al., 2015; Hadzi et al., 2015; Adewoyin et 30 University of Ghana http://ugspace.ug.edu.gh al., 2019; Tay et al., 2019; Anim-Gyampo et al., 2019) higher than WHO. The WHO has produced water quality criteria for drinking water for several chemicals including trace elements since 1984 to 2017. From the above, it is perceived that, water quality research in Ghana especially areas underlain by the Birimian super group rocks like the area under study focused mainly on surface water and groundwater. In addition, the above studies were restricted to only few sites with most communities not having issues of mineral mining. Unfortunately, small scale gold mining is gradually increasing in southwestern Ghana due to the geology being rich in sulphide minerals (arsenopyrite, chalcopyrite and pyrite) Luebe et al. (1990). Yet the impact of small-scale mining in most communities within southwestern Ghana especially the Lower Tano River Basin has not received the fullest attention. Apart from Edjah (2012) and Doyi et al. (2018), no studies have been conducted to investigate the quality of groundwater with respect to trace elements. Hence the results of this study will define the sources of aquifer contamination with respect to trace elements and that will add to the current literature on aquifer hydrochemistry and its suitability for socio-economic purposes. 2.1.3 Determination of the Hydrogeochemical processes that produces the Chemical Characteristics or Compositions of an aquifer system Hydrogeochemical processes refers to the correlation between water-rock chemistry, groundwater movement and the origin of the chemical composition of groundwater (Appelo & Postma, 1999). A change in the chemical composition of groundwater is principally a function of the interaction between the groundwater and the mineral composition of the aquifer materials through which it moves (Appelo & Postma, 1999). Hydrochemical processes such as precipitation, ion exchange, weathering, dissolution, etc. coupled with groundwater residence time along a flow-path control the changes in chemical composition of groundwater (Apodaca et al., 2002). Besides, the chemical composition of groundwater is controlled by several factors 31 University of Ghana http://ugspace.ug.edu.gh and groundwater has a distinct chemistry or chemical characteristics due to chemical variation of rainfall recharging an aquifer (Drever, 1988; Hem, 1991). In any environment, groundwater has a unique chemistry due to several processes like groundwater flow and rock- water interaction during recharge, dissolution of minerals and prolonged storage in the aquifer (Hem, 1986). In the early times of hydrogeochemical studies, some scientists reported the importance of hydrogeochemical processes in groundwater (Moller et al., 2007; Devadas et al., 2007; Tesoriero et al., 2004; Elango et.al., 2003; Apodaca et al., 2002; Sikdar et.al., 2001). The studies of the above-mentioned authors and other water scientists in the past years have aided in the creation of suitable management plans for aquifer protection and remedial measures for aquifer contamination. To overcome aquifer related issues, a detailed knowledge about the hydrogeochemical processes regulating its chemistry is required. This can be achieved with the help of computerized geochemical models such as Durov (1948), Piper (1944), Stiff (1951), Gibbs, (1970), saturation indices, and mineral stability diagrams (Edmunds et al., 2001; Appelo & Postma, 1999; Sahib et al., 2016). To understand the chemical state of groundwater and predict the various water types as well as the factors controlling the chemistry of an aquifer, the above- mentioned models are the most powerful tools to use. Parkhurst et al. (1995), Felmy et al. (1984), Wolery ,1979, Spostigo et al. (1979), Shannon et al. (1977), Plummer et al. (1976), Helgeson et al. (1970) and other scientists across the globe have established different geochemical models for assuming and describing the chemical character of mixed plus complex water. Plummer et al. (1990), Plummer et al. (1983), Jenne (1981), Runnels (1978) and Nordstrom et al. (1979) gave a brief review of this geochemical models. 32 University of Ghana http://ugspace.ug.edu.gh Numerous researchers have also used geochemical models for groundwater solubility equation study (Murphy & Schramke, 1998; Deutsch, 1997; Elangovan, 1997; Tamata, 1990; Wolery, 1983; Wolery, 1979). Worldwide approaches to groundwater problems and the significance of geochemical modelling are discussed in detail by Jenne, 1981. Currently, across the globe, the temporal and seasonal changes of the hydrogeochemical processes of groundwater are observed by different researchers (Kumar et al., 2006; Halima et al., 2010; Mahato et al., 2016; Abdelshafy et al., 2019; Akoachere et al., 2019) and statistical methods such as factor analysis, multivariate analysis, principal component analysis, correlation matrix, histograms and semi-logarithmic have been used by several researchers across the world for data analysis and interpretation (Banoeng –Yakubo et al., 2009; Gakin & Happell, 2014; Jacintha et al., 2016; Tatou et al., 2017; Baghdadl et al., 2019; Kumar, 2020). The above-mentioned statistical methods are a good way of organizing sets of data to make useful generalizations and understanding of aquifer chemistry. Likewise, the above-mentioned statistical tools can be used to classify groundwater, investigate and interpretate hydrochemical facies of groundwater (Lawrence & Upchurch, 1983). In Ghana, some researchers have similarly carried out investigations about hydrogeochemical processes using geochemical models and statistical tools. For example: Akiti (1980), being one of the early water scientists in Ghana studied the hydrogeochemistry of groundwater in the Accra plains of Ghana. The author applied hydrochemical data and identified three major hydrochemical facies (NaHCO3, NaCl, and MgCl2) for groundwater in the Accra plains. The results indicate NaCl as the dominant water type in parts of the Accra plains. Follow up to Akiti’s work, Kortatsi (2006 a) in some parts of the Accra plains applied mass balance techniques in studying the hydrochemistry of groundwater. The author related the 33 University of Ghana http://ugspace.ug.edu.gh hydrochemistry of groundwater in the Accra plains to the weathering of the host rocks, cation-exchange reaction, evaporative concentration of some solutes and seawater intrusion. In the Ankobra basin, Kortasi, (2006b) used hydrochemical data to establish the hydrochemistry of groundwater. According to the author, groundwater in the Ankobra basin is mildly acidic with low conductivity and under - saturated with carbonate minerals. The author indicated silicate weathering as the main hydrochemical processes controlling the chemistry of groundwater in the Ankobra basin. Using Q - mode mass balance methods and multivariate techniques, Helsrup et al. (2007) attributed the hydrochemistry of groundwater from some sedimentary aquifers in Togo and southern Ghana to silicate mineral weathering, carbonate equilibria, effects of seawater intrusion and ion exchange processes. In the Southern Voltaian sedimentary aquifers in Ghana, Yidana et al. (2008) used mass balance methods to describe the hydrochemistry of groundwater. Their results suggest weathering of silicate minerals as the likely dominating factor influencing the hydrochemistry of aquifers in Southern Voltaian aquifer. Banoeng-Yakubo et al. (2009) determine the main controls on the hydrochemistry of groundwater in some Birimian aquifers of the Birim River basin. In their studies, mass balance modelling was used simultaneously with multivariate R-mode hierarchical cluster analysis to determine the important sources of variations in the hydrochemistry of groundwater. In addition, they identified two water types, thus water influenced by silicate weathering and anthropogenic activities. Mineral speciation and silicate mineral stability diagrams generated from their data indicate montmorillonite, probably derived from the incongruent dissolution of feldspars and micas, as the most stable silicate phase in the groundwater. They also suggest cation exchange processes as one of the hydrogeochemical processes playing minor roles in the hydrochemistry of some areas underlain by the Birimian Supergroup rocks. 34 University of Ghana http://ugspace.ug.edu.gh In the Densu River Basin, Fianko et al. (2009 a) studied the hydrochemistry of groundwater with multipurpose approaches. According to the authors, the analytical results of groundwater was acidic and moderately mineralized. The Chemical constituents they observed were Na+> 2+ 2+ K + and Cl- > HCO - 2-Ca > Mg > 3 > SO4 > NO - 3 . The main water types they identified were Ca–Mg–HCO3, Mg–Ca–Cl, Na–Cl, and mixed waters (neither a particular cation nor anion dominates). The authors also reported that the influence of different anthropogenic activities have an impact on ground water resources within their study catchment. Edjah et al. (2015), studied the hydrogeochemistry of groundwater in some communities within the Lower Tano River basin and identified rock weathering as the dominant processes controlling the chemistry of groundwater and identified NaCl water as the dominant water within the study catchment. In the Lower Pra River basin, Tay et al . (2017) investigated the hydrogeochemical processes and the anthropogenic impact that influence groundwater resources. The hydrochemical results show that, the major processes responsible for chemical evolution of groundwater include silicate weathering, ion- exchange processes, sea aerosol spray, and the weathering of biotite, chlorite, and actinolite from the source rock. Hydrochemical facies of their results delineated two main water types, i.e., Na-HCO3 and Ca-Mg-HCO3 water types, with Na-Cl and Ca-Mg- Cl as minor water types. Using Q-mode Hierarchical Cluster Analyses (HCA), surface water and groundwater within the basin were characterized into four (4) water groups and five (5) subgroups. Results from the hydrochemical data suggest that groundwater within the basin was mainly undergoing the process of recharge, which involves the mixing of freshwater with geochemically different ionic signatures than processes involving saline-freshwater mixing. According to the authors, the use of Principal Component Analysis (PCA) together with Varimax with Kaiser Normalization for component matrix delineated three main processes in their study region and these processes are biochemical (water-soil-rock interactions), natural 35 University of Ghana http://ugspace.ug.edu.gh geochemical, incongruent dissolution of silicates/aluminosilicates, and pollution of the water resources principally from agricultural inputs. In the Central Region of Ghana, Ganyaglo (2015) studied the hydrogeochemical processes occurring in some parts of the region in order to determine the origin of groundwater salinity. The hydrochemical results from his work identified Ca-Mg-HCO3, Na-Cl, Ca-Mg-Cl-SO4, and non-dominant water types as the hydrochemical facies of the Central Region. The author concluded that groundwater salinization in the coastal zone of the Central Region was caused largely by halite dissolution and to a minor extent silicate weathering. Also, seawater intrusion played a minimal role in controlling the chemistry of groundwater in parts of central region. Review from the above studies shows that most authors focused mainly on groundwater potential assessment, groundwater quality and its suitability for domestic and agricultural purposes, and the hydrogeochemical processes controlling the chemistry of groundwater It is apparent that the hydrogeochemistry of groundwater in most communities within the Lower Tano River Basin have not been intensively studied for comparisons, monitoring, and sustainable management of the resource. However, this study being an addition to the previous studies carried out by Edjah et al. (2015) intend using a four-year groundwater hydrochemical data to estimate the hydrogeochemistry of groundwater with the help of statistical tools and hydrogeochemical modelling. Hydrogeochemical modelling which is a very useful tool will be used to evaluate the aquifer chemistry and to see if the aquifers within the basin are controlled by equilibrium with solid phases (Appelo & Postma, 1996). Equally, calcium, magnesium, sodium, and potassium aluminosilicate stability diagrams, and saturation indices for some primary silicate minerals will aid in describing the control on the composition of groundwater within the basin. ArcGIS 10.5 software will help in the production of groundwater quality maps and hydrogeochemical maps of the Lower Tano River Basin. The outcome of this 36 University of Ghana http://ugspace.ug.edu.gh study will add to the current literature on the hydrogeochemical studies of groundwater in the Tano Basin. 2.1.4 Sources of Recharge to the Aquifer System using oxygen-18 (δ18 O) and deuterium (δ2H). Isotopes are used to investigate the inter-relationships between the components of the water cycle such as rainfall, run-off, plant transpiration, and evaporation (Clark & Fritz, 1997). This is done using oxygen-18 (δ18O) and deuterium (δ2H). In addition, these isotopes are used to evaluate recharge, flow direction and mixing conditions as well as trace the origin of groundwater sources (Zaharin et al., 2008). In a particular environment, estimating groundwater recharge or origin comes with a characteristic isotopic signature, most often permitting the separation of water from different environments (Clark & Fritz, 1997). Isotopes are routinely used in hydrogeological investigations to complement physical hydrology and geochemistry due to their ability to provide information about recharge, geochemical evolution, and water- rock interactions, etc. (Clark & Fritz, 1997; Kendall & McDonnell, 1998; Cook & Herezeg, 2000). In Ghana, Akiti (1980) was the first researcher that used environmental isotopes (δ18O, δ2H,), to estimate groundwater recharge in some parts of the Afram plains. He developed a local meteoric water line from δ18O and δ2H in rainfall data. The author’s line is currently used as the local meteoric water line (LMWL) in Ghana and other sub - Saharan African nations. The equation of his line was in the form: δ2H‰ = 7.86δ18O‰ + 13.61. The equation reflects the relatively high humidity in the Accra plains. The slope of the author’s line was slightly close to that of the global meteoric water line of δ2H‰ = 8δ18O + 10. In addition, he used environmental isotopes (δ18O, δ2H) in groundwater to trace the sources of recharge in parts of the Accra plains of Ghana. 37 University of Ghana http://ugspace.ug.edu.gh In the Upper East, Upper West, and parts of the Accra plains of Ghana, Pelig-Ba et al. (1990) carried out a similar work like Akiti (1980). Their study showed that groundwater in the three regions was recharged predominantly from precipitation. Armah (2002), conducted similar environmental stable isotope studies in the Awutu-Senya District and some communities within the Central Region of Ghana. The author’s study showed a close correlation of the isotopic data to the Global Meteoric Water Line (GMWL) data. According to the author, the origin of groundwater in the Awutu-Senya District is of meteoric origin and not marine. In the Densu River basin, stable isotopes (δ18 O and δ2H) from depth profiles were used to estimate groundwater recharge by Adomako et al. (2010). The obtained results suggested recharge in some parts of the Densu River basin to be between 94 and 182 mm/year. Using environmental isotopes (δ18O and δ2H), Kaka et al. (2011), estimated groundwater recharge in the southwestern margin of the Volta Lake in Ghana. Their results suggested meteoric origin of recharge to groundwater in the Volta Lake area. In the same way, Saka et al. (2013), assessed groundwater recharge in the Ga East Municipal area using environmental isotopes (δ18 O and δ2H). In their study, the isotopic compositions suggest groundwater recharge to be from meteoric origin. In the Lower Pra River Basin of Ghana, Tay, 2015 used isotopes (δ18O and δ2H) to investigate groundwater recharge. The author’s results indicated that groundwater recharge in the Lower Pra River Basin was of meteoric origin with evaporation playing a significant role on the infiltrating water. Using isotopes (δ18O and δ2H), Egbi et al. (2018) estimated groundwater recharge in the Lower Volta River Basin of Ghana. Results obtained from their work indicated that groundwater recharge was from direct infiltration of rainwater with minimal evaporation. 38 University of Ghana http://ugspace.ug.edu.gh Using δ18O and δ2H, Edjah (2012) estimated groundwater recharge in the Lower Tano River Basin and results obtained indicated that the source of groundwater was from direct rainfall infiltration. Comparison between stable isotopes (δ18 O and δ2H) from the above studies as well as those carried out in the Southern Voltaian Sedimentary basin (Acheampong, 1996; Kortatsi & Sekpey, 1993; Jorgensen & Banoeng-Yakubu, 2001) showed that the isotopes of δ18 O and δ2 H in groundwater follow one trend, that is, they all cluster along the global meteoric water line (GMWL), suggesting rapid recharge from rainwater with little or no isotopic evaporation. In this study the use of environmental isotopes (δ18O, δ2H) for estimating groundwater recharge will follow the trend carried out by Akiti,1987. Rainfall samples will be collected for 2 years and the results computed to obtain a rainfall regression line for the study area. This research being the first of its kind will give a general rainfall regression line for the Lower Tano River Basin, since the rainfall regression line for Akiti,1987 did not cover the southwestern part of Ghana. Also, the outcome of this research will add to the current studies on groundwater recharge using environmental isotopes (δ18O, δ2H) in south western Ghana and the Birimian Supergroup rocks of Ghana. 2.1.5 Groundwater Age (residence time) Determination The age of groundwater is a vital parameter for understanding the dynamics of groundwater and the contaminants that travels with it (MacDonald et al., 2003). Identification of the age of water and transit times, allows easy determination of delayed impacts of present and past environmental practices on the quality of water (McGuire et al., 2002; MacDonald et al., 2002; Katz et al., 2004; Moore et al., 2006) and for determining the anthropogenic or geogenic effects on the quality (Morgenstern & Daughney, 2012). 39 University of Ghana http://ugspace.ug.edu.gh Ages of groundwater is also described by the groundwater transit time through regions or catchments and it’s important for conceptual understanding of recharge sources (McGuire & McDonnell, 2006; Stewart et al., 2010; Morgenstern et al., 2010, 2012; Cartwright & Morgenstern, 2012). The age of groundwater, which is related directly to fluid flux is also very valuable for calibrating mathematical groundwater transport models (Burton et al., 2002; Molson & Frind, 2005; Bethke & Johnson, 2008) and the age also gives essential information on contamination and water quality of drinking water (Morris et al., 2005; New Zealand ministry of Health, 2008). Hydrochemical evolution resulting from rock-water interaction can be quantified using groundwater age measurements (Burns et al., 2003; Glynn & Plummer, 2005; Daughney et al., 2010; Beyer et al., 2014). In all the above-mentioned applications, it is vital to constrain not only the average age of groundwater, but also the age distribution within the groundwater discharge sampling point. Tritium (3H) with a half-life of 12.43 years is the only radioactive isotope of hydrogen (Unterweger et al., 1980). Thermonuclear testing in the 1950’s and 1960’s introduced large amount of tritium into the hydrological cycle. This provided a useful environmental tracer for groundwater originating from this period (Solomon & Cook, 2000). The unit of tritium content in water is usually computed in tritium units (TU) also known as tritium ratio (TR) (Taylor & Roether, 1982). 2.1.5.1 Sources of Tritium (3H) The only source of tritium in rainfall prior to 1950 was from natural production in the upper atmosphere. This was generally through the bombardments of nitrogen by the flux of neutrons in cosmic radiation. Across the world, atmospheric thermonuclear testing 40 University of Ghana http://ugspace.ug.edu.gh which occurred in 1952 elevated the tritium content in precipitation. This created a natural cause which was used to identify precipitation from 1952. Between October 1952 to December 1953 approximately 600 kg of tritium (3H) was introduced into the atmosphere by thermonuclear test carried out by UK, USA, and USSR (Araguas et al., 1996). The tritium content in rainfall has decreased after the atmospheric test ban treaty of 1963. After the ban, French and China continued with the thermonuclear testing until 1980 thus producing smaller quantities of tritium into the atmosphere (Weiss et al., 1979). Currently, significant amounts of tritium are released into the atmosphere from nuclear fuel reprocessing facilities and nuclear power plants (Kim et al., 1998)). Additionally, little amounts of tritium are released from compasses, exist signs and luminous watches. Globally the averaged production rate of tritium (3H) in the Earth's atmosphere from galactic cosmic rays has been estimated between 0.19 and 0.29 atoms cm·2s·1. Production of tritium is more at higher geomagnetic latitudes (Masarik & Reedy, 1995). The mean global list before the advent of thermonuclear testing has been estimated to be 1.3 x 1018 Bq (35 MCi, or 3.6 kg of 3H) (O'Brien, 1979). The normal level of tritium in rainfall was determined from measurements on vintage wines to be 3-6 TU in North America and Europe (Kaufman & Libby, 1954; Roether, 1967), and 1-3 TU in South Australia (Allison & Hughes, 1977). Thermonuclear tritium content in precipitation has been determined by direct measurement, and indirect measurement from surface water, groundwater, tree ring cellulose and wine samples. Regular measurement of tritium in rainwater began in 1953 in Ottawa, Canada. Since 1961, tritium concentrations in monthly precipitation samples have been measured at a global network of stations (IAEA, 1992). At numerous northern hemisphere stations during the early 1960’s, the average monthly concentrations in excess of 5000 TU were recorded. This follows the 1961- 1962 Soviet testing series in the Arctic. Much lower tritium contents were recorded in the southern hemisphere due to more nuclear tests conducted in the northern hemisphere. In both hemispheres, a strong 41 University of Ghana http://ugspace.ug.edu.gh dependence on latitude was detected, with little tritium concentrations nearer to the equator. Precipitated water re-evaporation instigated higher tritium concentrations at continental stations, relative to those at oceanic stations at similar latitude. Spatial differences in tritium fall out can be read from Gat (1980), Weiss and Roether. (1980), and Eriksson, (1983). 2.1.5.2 Understanding groundwater recharge sources in Ghana using tritium (3H). In Ghana, few studies have tried using tritium to study groundwater age or residence time for groundwater management. In the Accra plains of Ghana, Akiti, 1987 obtained tritium values of 15 TU to 27 TU (tritium units) in groundwater, suggesting that the groundwater in parts of the Accra plains was young water or of modern recharge or have not been overly abstracted. In the Voltaian Sedimentary basin of Ghana, Acheampong and Hess (2000), recorded tritium values of 1TU and 7.2 TU indicating young water. Adomako et al. (2011), reported tritium values of 5 TU and 12 TU for groundwater in the Densu River basin, suggesting young or modern recharge. Ganyaglo, (2017) reported tritium values ranging from 0.05±0.07 TU to 4.75±0.16 TU in the Central Region of Ghana suggesting young or modern recharge. In addition, he recorded low tritium content in three boreholes at Ekumfi Asokwa suggesting an old water. From the above studies, the tritium values revealed short residence time for most groundwater in Ghana. The groundwater residence time in the Lower Tano River basin is unknown. Hence, to have a generalized idea about the residence time, this study intends measuring tritium values in surface water and groundwater and this being the first of its kind in the Basin will add to literature on groundwater age determination in Ghana. 42 University of Ghana http://ugspace.ug.edu.gh CHAPTER THREE METHODOLOGY Under this chapter, the approach and procedures used for Desk study, Field work, Sample preparation, Laboratory analysis, Data validation, Data treatment, Data interpretation and Spatial distribution maps are described. 3.1. Desk Study To achieve the objectives of this study, a desk study was conducted to assess the general hydrogeology and the hydrochemical settings prevailing in the various lithologies of the study area. This involved available literature review, collection of topographical, geological, and hydrogeological maps from the Survey Department (SD) and, Ghana Geological Survey Authority (GGSA), Community Water and Sanitation Agency (CWSA, Takoradi), respectively. Based on the available records (borehole records, topographical, hydrogeological, and geological maps), sampling sites were selected, and fieldwork embarked. 3.2 Field work 3.2.1. Geophysical Sitting In 2013 and from 2014 to 2015, 30 and 18 vertical electrical soundings (VESs) were carried out, respectively using Schlumberger configuration at various communities across the study area. This was done to identify potential aquifers for borehole drilling and development. Resistivity measurement was carried out with SAS 1000 Terrameter apparatus and the obtained resistivity data was reversed and interpreted using Van Der Velpen (1988) software. The software aided in the identification of different geoelectric units as well as aquifer saturated thicknesses and true resistivity units. Potential drilling sites were selected based on VES curve interpretations (Figure 3.1), which were related to the general geology of the Lower Tano River Basin. 43 University of Ghana http://ugspace.ug.edu.gh Figure 3.1: VES sounding curves generated as model curves that suit the apparent resistivity values (field curves) for selected sites in the Lower Tano River Basin. 3.2.2. Borehole Drilling and Development After the geophysical siting, a total number of 30 and 18 boreholes were drilled (Figure 3.2), across the basin in 2013 and from 2014 to 2015, respectively. Reports on the borehole logs, type of drilling cuttings, penetration rate, rock types, geological structures (bedding plane, joints, and fractures), thickness of the saturated zones, drilling and developmental yields were recorded for each drilled borehole. The number of drilling rods used during drilling determined the depth of each borehole, and each successful drilled borehole was cased and screened at water bearing zones. The rocks encountered during drilling belonged mostly to the Apollonian formation with few from the Birimian Supergroup rocks. 44 University of Ghana http://ugspace.ug.edu.gh Figure 3. 2: Geological map of the study catchment with the borehole drilling points (2013 and 2014 to 2015). 3.2.3. Pumping Test Six to twelve hours constant discharge test on a single well pumping test method (Todd, 1980) was adapted for the generation of pumping test data. This method was used due to the high- recorded borehole drilling yields. Prior to pumping, the wellhead of the borehole was opened, and the static water level was measured using a calibrated water level meter. A pump with the specific horsepower per the developmental yield for each drilled borehole was dropped to a substantial depth in the borehole, whiles connected to a source of power. A calibrated 80 litre bucket was set in place to collect the discharge water, and a stopwatch was set to zero as the start time. As pumping started, the drawdown was measured based on the scheduled times on the data sheet. The water level drawdown and the time was simultaneously measured and recorded. The exercise was done in two phases specifically discharge and recovery phase. During the discharge stage, the borehole was pumped at a constant rate and the water level was measured at intervals in the same pumped borehole. 45 University of Ghana http://ugspace.ug.edu.gh In the recovery stage, the borehole was allowed to recover and the water level in the same borehole was measured at the same intervals as that of the discharge. The recovery and time drawdown curves were plotted for each drilled borehole using Theis (1934) solution model. This model was used due to it most simplifying expectations and in using the model, the type curves (mathematical models) to water level changes (response data) were fitted by a curve matching method. The curve matching technique of a computer software known as AQTESOLV 4.0 was employed. The drawdowns according to Theis (1934) model were calculated using the equation: 𝑄 log 𝑟2 𝑆 𝑆 = (−0.5772 𝑒 )………….. Eq 3.1 4𝛱𝑇 4𝛱𝑇 The residual drawdown “s” that is the difference between the drawdown component due to continues pumping and the recovery component due to recharge were given by the formula: 𝑄 4𝑇𝑡 4𝑇𝑡′ 𝑆 = [(log𝑒( ) − log𝑒( )]…….. Eq 3.2 4𝛱𝑇 𝑟2𝑤𝑆 𝑟2𝑊 Where S =storage coefficient Q = discharge (m3/ day) rw = effective radius of the borehole, in which the water recovery is measured T = time since pumping started t’ = time since pumping stopped s = drawdown (m). 3.2.4. Sample Collection 3.2.4.1. Surface water and groundwater sampling for chemical and trace element analysis For this study, 30 and 18 boreholes drilled across the basin in 2013, and from 2014 to 2015 were sampled, respectively (Figure 3.2). Monthly rainfall, 9 rivers, 15 streams, 3 lagoons, 3 seawater, 36 hand dug wells and 44 boreholes were sampled during the rainy season in 2016 46 University of Ghana http://ugspace.ug.edu.gh (Figure 3.3). Additionally, during the dry season in 2017, monthly rainfall, 14 rivers, 13 streams, 3 lagoon, 9 sea water, 30 hand dug wells and 54 boreholes were sampled across the study catchment (Figure 3.4). Figure 3. 3: Geological map of the study catchment with surface water and groundwater sampling points (2016) 47 University of Ghana http://ugspace.ug.edu.gh Figure 3. 4: Geological map of the study catchment with surface water and groundwater sampling points (2017). Before the sampling of the surface water and groundwater, a detergent was used to wash the HDPE (high-density polyethylene) bottles. After, the bottles were rinsed thoroughly with distilled water to remove contaminants from the bottles. The bottles were then washed with 10% nitric acid in order to pre-condition the HDPE bottles. For the sampling of the streams, rivers, lagoons and seawater, a dip sampler was used to collect the water from a downstream direction to upstream direction and placed in a 250 ml pre- condition HDPE bottles. The samples were taken from downstream direction to an upstream direction in order to avoid the minor inclusion of disturbed sediments. The HDPE bottles with the sampled rivers, streams, lagoon, and seawater together with duplicate samples were labelled silica, anions, cations, and trace elements. The bottles labelled anions, silica and trace elements with its duplicates were acidified with 0.2M HNO3. This was done to keep the ions in solution. The sampled streams, rivers, lagoon, and seawater in the HDPE bottles were tightly capped 48 University of Ghana http://ugspace.ug.edu.gh and placed in an ice chest with ice blocks and transported to the various laboratories for analysis. Similar procedures were applied to the sampling of the hand dug wells and the boreholes. The only thing that was done differently was how the groundwater samples were taken. For instance, in the sampling of the hand dug wells, the static water level was first measured, after much water was pumped out for 30 minutes before sampling was done. This was done to purge the aquifer and remove all stagnant water from the hand dug wells. For the sampling of the borehole water, the boreholes drilled in 2013 and 2014 to 2015 were sampled after each pumping test. For the existing boreholes, the hand pump on each borehole was dismantled. After, the static water levels were taken, and the hand pump was rearranged and pumped for 30 minutes in order to purge the aquifer and empty stagnant water from the casing. The purging for both hand dug wells and boreholes were done to get a typical sample of groundwater in-situ. After, groundwater samples were collected with a sterilized bucket. Part of the water in the sterilized bucket was used to rinse the sample bottles thrice before filling. This was done in accordance with Weaver (2007). 3.2.4.2. Rainfall, Surface water and groundwater sampling for stable isotope compositions (δ18O and δ2H) Rainfall samples were collected monthly from 1st January 2016 to 1st January 2018. A rainfall collector donated by the International Atomic Energy Agency (IAEA) as shown in Figure 3.5 was mounted at Edjah Villa near the coast of Esiama (002°21.130´W0456.032´N). Another rain gauge fabricated by the author and Staff of Nuclear Chemistry and Environmental Research Centre of the Ghana Atomic Energy Commission as shown in Figure 3.6 was mounted at St Patrick Catholic Church in Half Assini (002°53.103´W0502.981N). The fabricated rainfall collector was built per IAEA specification (www.iaea.org/water). The rain collector consisted of a funnel, a measuring tube, and an outer cylinder. All the rain collectors were mounted at both sites on the 29th of December 2015. Both collectors were placed 30 to 50 cm above the ground to avoid splashes. Processing of the collected rainfall samples consisted of rainwater 49 University of Ghana http://ugspace.ug.edu.gh transfer from the rain collectors using a wide funnel into a 2000 ml plastic granulated cylinder. The amount of every monthly rainfall collected was measured and recorded on site. After, the rainwater was poured into 50 ml and 500 ml HDPE bottles for the analysis of chemistry, stable isotope compositions and tritium. Both bottles were capped to prevent air bubbles and placed in a cool dry box. It was then transported to the laboratories of Ghana Atomic Energy Commission for preservation. Surface water (rivers, lagoon, streams, and seawater) and groundwater sampled in 2016 and 2017 for isotopic composition measurements, followed the method outline under 3.2.4.1. The only difference was that, the sampled surface water and groundwater were filled directly into a 50 ml HDPE bottles and capped to prevent air bubbles. Surface water including rainfall and groundwater sampling for isotopic composition measurement was done in accordance to the procedures outlined by Boghici (2003) and IAEA, 2000 (www.iaea.org/water). Figure 3. 5: IAEA donated rain collector mounted at Edjah Villa in Esiama 50 University of Ghana http://ugspace.ug.edu.gh Figure 3. 6: A fabricated rainfall collector mounted at St Patrick Catholic Church in Half Assini. 3.2.4.3 Rainfall, Surface water and groundwater sampling for Tritium analysis Sampling of rainfall, surface water (rivers and streams) and groundwater for Tritium analysis does not require any special methodology. But in this study, a 500 ml HDPE bottles donated by IAEA were rinsed thoroughly with some of the rainwater, rivers, streams, hand dug wells and boreholes at each sampling point. The bottles were filled with some of the surface water and groundwater samples. After, the bottles were tightly sealed to prevent contact with air. In all, 57 water samples including rainwater, rivers, hand dug wells and boreholes were sampled for tritium analysis. The selection was done based on proximity of the hand dug wells and boreholes to the rivers and streams. After sampling of the surface water and groundwater for hydrochemical and stable isotope measurements, each sample bottle was given an identification label. Each label consisted of the sample location, date of sampling, record of any stability preservative treatment and prevailing weather condition at the time of sampling. After, the surface water and groundwater samples were preserved at 4° C until laboratory analyses were performed. This was done in order to limit the degradation of nitrate, sulphate, phosphate, and bacterial activity. 51 University of Ghana http://ugspace.ug.edu.gh 3.2.5. Measurements of Field Parameters The geochemistry of the sampled water is centered on the analysis of inorganic ions in water as well as series of physico-chemical parameters controlling the interaction of these ions (Appelo & Postma, 1999). The parameters that control the interaction of these ions are alkalinity, electrical conductivity (EC), oxidation-reduction potential (Eh), pH, temperature, and total dissolved solids (TDS). For all thermodynamic calculations, temperature is one of the fundamental keys required (Appelo & Postma, 1999). In addition, it is needed for modifying pH and electrical conductivity measurements. In this study, the temperature was measured as close to in situ settings using a temperature probe which was a component of the pH meter used. Electrical Conductivity (EC) is relative to the number of dissolved ions present in solution and provides a general idea of the total dissolved solids (TDS) (Appelo & Postma, 1999). EC is normally measured in milli siemens per meter (1mSm-1 = 10μScm-1 = 10μmhoscm-1) but for this study, EC values were recorded in μScm-1 and TDS was recorded in milligram per liter using TDS/EC probe. One of the most essential field parameters is pH. This is because it controls most of the organic and inorganic constituents in water and it is expressed as: pH = - log (H+) ……. Eq (3.3) (Fisher, 2002). pH measurements come in different methods and some of these methods are electronic meters, pH indicator paper, and liquid calorimetric indicators. In this research, a more complex meter designed for conductivity, temperature, salinity, and pH measurement was used. This meter attains an accuracy of ±0. 002 pH units. pH is essential because it will help identify the primary aggressive nature of the groundwater during chemical weathering of the underlying rocks (Hem, 2002). Hem (2002) recognizes the reaction of dissolved carbon dioxide with water as 52 University of Ghana http://ugspace.ug.edu.gh one of the most important processes in establishing the pH of natural water. The author represented this with a three-step reaction expressed as: H2CO3 (aq) ↔ CO2(g) + HO(1) E q (3.4) H+(aq) + HCO - 3 (aq) ↔ H2CO3 Eq (3.5) H+(aq) +CO 2- 3 (aq) ↔ HCO - 3 (aq) E q (3.6) Equations (3.5) and (3.6) produce H+ which influences the groundwater pH. Prior to sampling, the probes used for measurement of the pH, temperature, salinity, electrical conductivity (EC), and total dissolved solids (TDS) were calibrated with a standard solution. A reference buffer solution of pH 4 and 7 was used to calibrate the pH meter. The conductivity probe was also calibrated against a standard solution made up of KCl of value 1480 µS/cm. The probe was calibrated each morning before field measurement. In addition, alkalinity (as bicarbonate) was determined on the field by titrimetric method (Figure 3.7 and Appelo & Postma, 1999) and the procedure used are outlined below. That is: 1. At each sampling point, 100 ml of the sampled water was transferred with a volumetric pipette into a conical flask. 2. Two to three drops of phenolphthalein and methyl orange indicator was added to the water sample in the conical flask and shaken. 3. During shaking, the water sample that turned red or pink had its alkalinity to phenolphthalein determined by titrating that sample against hydrochloric acid until the colour disappears. 4. In the same way, the water sample that turned orange during shaking, without the addition of hydrochloric acid, had its total alkalinity zeroed. 5. The water sample that turned yellow during shaking had the resulting solution titrated against hydrochloric acid until the first noticeable colour changed to orange. 53 University of Ghana http://ugspace.ug.edu.gh Figure 3. 7: Determination of alkalinity (as HCO -3 ) on the field by titrimetric method Equation of reactions occurring during titration was expressed as: HCl(aq) + HCO -13 (aq) ↔ CO2(g) + H2O(l) + Cl -(aq) …………. Eq (3.7) {Appelo and Postma, (1999)} From the equation above, 1 mole of HCl- reacts with 1 mole of HCO - 3 . The mole ratio was 1:1. Hence, the concentration of HCO - 3 in millimol/l was obtained from the equation: 𝑉 [ ] 𝑇(𝐻𝐶𝐿) 𝑀(𝐻𝐶𝐿) 𝐻𝐶𝑂3− = × × 1000 Eq (3.8) {Appelo and Postma, (1999)} 𝑎 𝑎 Where VT(HCL) = total volume of HCl - needed to titrate to a pH of 4.4 M(HCL) = Molarity of HCL a = aliquot of extract in ml The Molar Mass of HCO - 3 = 61 𝑉𝑇(𝐻𝐶𝐿) 𝑀(𝐻𝐶𝐿) Hence [𝐻𝐶𝑂3−] = × × 1000 × 61 𝑎 𝑎 𝑉𝑇(𝐻𝐶𝐿) × 𝑀(𝐻𝐶𝐿) ×6100 = Eq (3.9) 𝑎 54 University of Ghana http://ugspace.ug.edu.gh For quality control (QC) and quality assurance (QA) for the measurement of alkalinity on the field, a duplicate water sample was prepared and taken through the same mentioned procedures above after every 10 sampling points. The end point of the duplicate water sample was within plus or minus 0.1 ml. In addition, a control standard of 50 mg of NaCO3/L was prepared and analyzed together with the water samples. The value of the control standard was plotted on a control chart after a day’s work. From the charts, the values that fell outside the action limits (±α), were reanalyzed by visiting the site and resampling. Calculation of results: 50,000 ×𝐴×𝑁 Phenolphthalein alkalinity as CaCO3 (P) = mg/L …………….. Eq (3.10) 𝑉 50,000 ×𝐵×𝑁 Total alkalinity as CaCO3 (T) = mg/L ………………. Eq (3.11) 𝑉 If, Phenolphthalein alkalinity (P) = 0, then, bicarbonate (HCO-3) is total alkalinity (T) If, Phenolphthalein alkalinity (P) < ½ T, then, HCO -3 equals the difference between total alkalinity (T) and 2 × Phenolphthalein alkalinity (P) (i.e. HCO -3 = T-2P). If, Phenolphthalein alkalinity (P) = ½ T, T or > ½ T, then, HCO -3 = 0 Where, A = ml of hydrochloric acid solution added to obtain the phenolphthalein end-point of 8.3, B = ml of hydrochloric acid solution added to obtain the methyl orange end-point of 4.5 pH N = Normality of the mineral acid, V = volume of water sample used. 55 University of Ghana http://ugspace.ug.edu.gh 3.2.6. Laboratory Analysis 3.2.6.1. Measurement of Calcium by EDTA (ethylenediaminetetraacetic acid or its salts) titrimetric method at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. When EDTA (ethylenediaminetetracacetic acid or its salts) is added to water containing both calcium (Ca2+) and magnesium (Mg2+), it combines first with calcium and then determined directly with EDTA when the pH is made sufficiently high so that magnesium is largely precipitated as hydroxide. Several indicators that combine with calcium only gives colour change when all the calcium has been complexed by EDTA at a pH of 12 to 13. For the determination of calcium in the surface water and groundwater samples using EDTA, titrimetric method, the following procedures were followed and that is: 1. The water samples were diluted to 50 ml, such that the concentration of calcium was about 5 to 10 mg. 2. 2.0 ml of NaOH solution was added to produce enough pH of 12. 3. 0.1 g of CaCO3 indicator mixture was added to the solution. 4. The EDTA titrant was slowly added to the solution with continuous shaking until the colour changed from salmon to orchid purple. 5. The end point was checked by adding one or two drops of titrant in excess to make sure that no further colour change was observed. In accordance to APHA, 2012, the concentrations of calcium in the water samples using EDTA was calculated as: 𝐴 ×𝐵×400.8 Ca (mg/) = …………………… Eq (3.12) 𝑚l of sample Where A = ml of EDTA titrant used 𝑚l of standard cacium soution B = 𝑚l of standard cacium soution = ……………. (Eq 3.13) 𝑚l 𝑜𝑓 𝐸𝐷𝑇𝐴 𝑡𝑖𝑡𝑟𝑎𝑛𝑡 56 University of Ghana http://ugspace.ug.edu.gh For Quality assurance and quality control (QA/QC), 6. Blanks were analyzed after every batch of five water samples. Also, a control standard of 10 mg/l of Ca2+ was prepared and analyzed together with the water samples. 7. The values of the control standard were plotted on a control chart. From the chart, a fresh control standard was prepared and water samples with calcium content outside the action limit of ±3α was reanalyzed. 3.2.6.2. Measurement of Magnesium (Mg2+) using Atomic Absorption Spectrometric (AAS) Method at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. For the measurement of magnesium in the surface water and groundwater samples the following procedures were used: 1. The samples were first digested before using AAS to analyze the samples. To digest the sample, 2. 5 ml of the water sample was measured in three replicates into TFM Teflon vessels of a microwave digester (ETHOS 900). 3. 6 ml of 65% concentrated HNO3, 3 ml of 35% HCl and 0.25% H2O2 were added to each vessel containing the water samples. 4. The vessel was swirled gently to mix. 5. After the vessel was fitted vertically into a microwave digester and digested for 20 mins. 6. Once digestion was completed, the vessel containing the samples cooled in a water bath for 20 mins to reduce high temperature and pressure build up within the vessel. To measure the surface water and groundwater samples using AAS, 7. The mixture in the vessel was transferred quantitatively into a volumetric flask and diluted to 20 ml with deionized water. 57 University of Ghana http://ugspace.ug.edu.gh 8. Each mixture was analyzed using VARIAN AA240FS Flame Atomic Absorption Spectrometer. This instrument searches for a particular element by focusing a beam of ultraviolet light at a specific wavelength through a flame and onto a detector. 9. The mixture was aspirated into a flame, followed by a light absorbance thus reducing its intensity. 10. The instrument measured change in intensity which was later converted to absorbance with the aid of a computer data system. 11. The amount of light absorbed was proportional to the number of atoms in the flame hence, the number of Magnesium ions in solution For QA/QC, 12. The quality of the obtained results was assessed by checking the linearity of the Mg2+ calibration lines for the prepared standards. 13. Under ideal condition, a perfect correlation should be observed and a correlation of r2 = 0.92 was observed for the surfaced water and groundwater samples. 14. A reagent blank (HNO3/HClO4/H2O2) was used to establish the method detection limit (MDL) for the water samples. In the analyses, seven replicates of the water samples were measured for Mg2+ content. Since the values for water blank was below the detection limits for magnesium, the detection limits of the instrument were taken as the detection limit for magnesium concentration (Table 3.1). Table 3. 1: MDL for water sample Detection Limits Element IDLs* (mg/L) MDLs*water (mg/L) Mg2+ 0.002 0.002 IDLs and MDLs water are the instrumental detection limit and method detection limit of the water samples, respectively. 58 University of Ghana http://ugspace.ug.edu.gh The correctness of the methodology used was checked with Fluka, which is an analytical certified reference material (CRM) produced and certified in accordance with ISO/IEC 17025 and ISO Guide 34. 3.2.6.3. Measurement of Total Hardness by Ethylenediaminetetraacetic acid (EDTA) titrimetric method at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. 1. 25 ml of each surface water and groundwater sample was diluted to 50 ml using distilled water. 2. 1 ml of buffer solution was added to the diluted water sample. 3. Two drops of murexide indicator were added. 4. This turned the water to wine red colour. 5. The resulting solution was titrated instantly against EDTA. 6. The titration was carried out slowly with continuous stirring until the last colour (wine red) disappeared from the water Calculation: 𝑉1 ×𝑆×1000 Total Hardness (CaCO3) = 𝑚𝑔/𝐿 …………. Eq (3.14) 𝑉 Where, S = mg CaCO3 equivalent to 1 ml of EDTA titrant = 1mg CaCO3 V = volume of the water sample in Ml V1 = Volume of the added EDTA. For QA/QC procedures, please refer to QA/QC under calcium determination in the previous chapter. 59 University of Ghana http://ugspace.ug.edu.gh 3.2.6.4. Measurement of sodium and potassium using flame photometric method at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. The levels of Na+ and K+ in the surface water and groundwater samples were determined by the flame photometric method, using the Sherwood 420 Flame Photometer (Sherwood, UK). Preparation of the Masking agent 7. 100 mg L-1 Li (lithium) solution (masking solution) was prepared by dissolving 6.941 g of Li2SO4·H2O in double distilled water and diluted to the 1000 mL mark of a volumetric flask. The masking solution is important because Na+, K+ and Li are Group one elements. Hence the addition of Li is to mask other Group one elements [Rubidium (Rb), Cesium (Cs) and Francium (Fr)] that may be present in the water samples except Na+ and K+. To prepare standard (Mixed Na/K calibration standard) solution 8. A 100 mg L-1 mixed Na+ and K+ calibration standard was prepared by pipetting 1 mL of commercially-available stock Na standard and 1 mL of commercially-available stock K+ standard in a 10 mL volumetric flask and then diluted to the 1000 ml mark of a volumetric flask. To calibration the flame photometer 9. 2 mL volume of the masking solution was added to 5 mL of the mixed Na+ and K+ standard and mixed thoroughly by swirling. 10. The combined solution was aspirated into a liquefied petroleum gas (LPG)-fed flame of the Sherwood 420 Flame Photometer. 11. The concentrations of Na+ and K+ were respectively read. 12. This was followed by the analysis of the blank solution and the water samples subsequently. 60 University of Ghana http://ugspace.ug.edu.gh To analysis the water samples 13. A blank solution made up of 5 ml of doubled distilled water and 2 ml of masking solution were aspirated with a liquefied petroleum gas (LPG)-fed flame of the Sherwood 420 Flame Photometer. 14. After analysis of the blank, Na+ and K+ contents in the water samples were determined through the procedure below. The procedure for the analysis of the water samples are as follows: 15. 5 mL volume of the water samples were transferred into 10 mL test tube and 2 ml of masking solution was added. 16. The mixture was homogenized by shaking for about one minute. 17. The homogenized solution was aspirated into the flame of the photometer. 18. Na+ and K+ content was read and recorded. 19. In instances where Na+ or K+ content is high and had to be diluted, the results was calculated as: K+ or Na+(mg/L) = (mg/L K+ or Na+ aliquots) * D …………. Eq (3.15) Where D= dilution ratio expressed as 𝑚𝑙 𝑜𝑓 𝑠𝑎𝑚𝑝𝑙𝑒 + 𝑑𝑖𝑠𝑡𝑖𝑙𝑙𝑒𝑑 𝑤𝑎𝑡𝑒𝑟 ……………..Eq (3.16) 𝑚𝑙 𝑜𝑓 𝑠𝑎𝑚𝑝𝑙𝑒 For QA/QC, 20. Duplicate water samples were analyzed after every batch of five water samples. 21. The prepared standard for sodium and potassium and the masking solution were read after every batch of five samples. 22. 5 mg/L of Na+ or K+ control standards were prepared and analyzed together with the water samples. 23. The value of the control standard was plotted on a control chart, and the values that fell outside the action limits (±3σ), were reanalyzed by preparing a fresh control standard. 61 University of Ghana http://ugspace.ug.edu.gh 3.2.6.5. Measurement of Chloride (Cl-) by MOHR Ajentometric Method at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. In neutral or slightly alkaline solution, potassium chromate can indicate the endpoint of silver nitrate titration of chloride. Silver chloride is precipitated quantitatively before red silver chromate is formed. AgNO3 + NaCl → AgCl + NaNO3………………. Eq (3.17) AgNO3 + K2CrO4 →Ag2CrO4 + KNO3……………………. Eq (3.18) For the determination of chloride content in the surface water and groundwater samples the following was used: 1. 25 ml of the water sample was filtered into a conical flask. 2. 2 drops of potassium chromate indicator (K2CrO4) were added and titrated against 0.0141 molar of AgNO - 3 solution until an endpoint was reached where the colour changed from yellow to reddish brown. 3. In accordance with APHA 2012, the chloride ion concentration in the water sample was calculated as: Cl- (mg/L) = ((A-B)×N×35.450)/(mL of the water sample)……….. Eq (3.19) Where, A = ml titration of the sample B = ml titration of blank N = Molarity of AgNO3 For quality control (QC) and quality assurance (QA), the following procedure was used: 4. Duplicate water samples were analyzed after every batch of five samples. 5. The end point of the duplicate water sample was within ± 0.1 ml. 62 University of Ghana http://ugspace.ug.edu.gh 6. The water samples were analyzed together with a control standard of 20 mg/L prepared from NaCl stock solution. 7. The value of the control standard was plotted on a control chart and the values that fell outside the action limits (±3σ) were reanalyzed by preparing a fresh control standard. 3.2.6.6. Measurement of Phosphate using a UV –visible Spectrophotometer at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. In this study, the phosphate content in the water sample was measured using a Shimadzu UV- 1201 UV- Visible Spectrophotometer with a wave length of 880 nm. The methodology used for the determination of Phosphate was based on the Official Method 4500-P E (Ascorbic acid method) in the Association of Official Analytical Chemists (AOAC International, 2007). Principle Potassium antimonyl tartrate and ammonium molybdate react in an acid medium with orthophosphate to form antimonyl-phosphomolybdate complex. This is reduced to intensely coloured molybdenum blue by ascorbic acid. The absorbance of the molybdenum blue is measured at a wavelength of 880 nm on a UV-visible spectrophotometer. Instrumentation A Shimadzu UV-1201 UV-visible Spectrophotometer (Japan) with 1 cm matching quartz cells was used for phosphate absorbance measurements. Chemicals Used Ammonium heptamolybdate [(NH4)6Mo7O24·4H2O], Potassium antimonyl tartrate [K(SbO)C4H4O6.5H2O], Sulphuric acid (96% H2SO4) and Ascorbic acid. Reagents Potassium antimony tartrate [K(SbO)C4H4O6 ½H2O]. 63 University of Ghana http://ugspace.ug.edu.gh Procedure Used 1. 500ml potassium antimony tartrate solution was prepared by dissolving 1.375 g of K(SbO)C4H4O6 ½H2O in about 400ml double distilled water and diluted to 500ml. 2. The solution was stored in a glass-stoppered bottle. 3. 500 ml ammonium molybdate [(NH4)6Mo7O24 ·4H2O] solution was prepared by dissolving 20 g of ammonium molybdate in double distilled water and then diluted to the 500 ml mark of the conical flask. 4. 0.1 M ascorbic acid solution was prepared by dissolving 1.76 g ascorbic acid in double distilled water and diluted to the 100 ml mark of a conical flask. Since ascorbic acid solutions are not stable for longer periods of time at room temperature, it is advisable to always prepare them fresh due to its stability for four hours. 5. 100 ml combined reagent consisting of an acidic (H2SO4) solution of potassium antimony tartrate, ammonium molybdate and ascorbic acid was freshly prepared by adding 50 ml of 5 M H2SO4 to a mixture of 5 ml potassium antimony tartrate, 15 mL of ammonium molybdate and 30 mL of ascorbic acid. 6. The mixture was allowed to attain room temperature after which it was vigorously mixed and stored in a plastic bottle. 7. After, a stock standard phosphate solution of 50 mg/L was prepared by dissolving 219.5 g of oven-dried potassium dihydrogen phosphate (KH2PO4) in double distilled water to make 1000 ml of stock solution. 8. Working solutions of 0.2, 0.4, 0.6, 0.8, and 1.0 mg/L were prepared daily by suitable dilution of the stock solution. 9. After, 10 ml aliquot of the calibrated stock solution was poured separately into 20 ml test tubes. 10. For each test tube with the calibrated solution, 2 mL of the combined reagent was added and then left for about 5 minutes. 64 University of Ghana http://ugspace.ug.edu.gh 11. During the 5 minutes, a blue colour was formed and that revealed the presence of antimonyl-phosphomolybdate complex. 12. Appropriate aliquot of each blue-coloured solution in each test tube was transferred into a 1 ml cuvette. 13. The cuvette with the solution was inserted into the spectrophotometer and set at a wave length of 800 nm. 14. The absorbance was measured against a reagent blank. 15. A calibration graph of absorbance against phosphate concentration in each calibrant solution was plotted. The concentration of phosphate in the water samples were deduced from a calibration graph. For Quality assurance and Quality control (QA/QC) measurement for phosphate in the water samples the following procedures were used: 16. A control standard of 1 mg/L of phosphate was prepared and analyzed together with the duplicate water samples after every batch of five water samples. 17. The value of the control standard was plotted on a control chart, and a fresh control standard was prepared for re-analysis of samples that fell outside the action limits (±3σ). 3.2.6.7. Measurement of Sulphate using a UV –visible Spectrophotometer at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. Principle The method used is based on the reaction of sulphate ion with barium chloride (BaCl2) under acidic conditions to precipitate to barium sulphate (BaSO4). The absorbance of the white BaSO4 suspension is measured at a wavelength of 420 nm on a UV-visible spectrophotometer. Official Method 4500-SO 2-4 E (Turbidimetric method) is used for the determination of sulphate (AOAC International, 2007). 65 University of Ghana http://ugspace.ug.edu.gh Instrumentation A Shimadzu UV-1201 UV-visible Spectrophotometer (Japan) with 1 cm matching quartz cells was used for absorbance measurements. Chemicals Barium chloride (BaCl2, 99.999%), Sodium chloride (NaCl), Hydrochloric acid (HCl), Sodium sulphate (Na2SO4) and Glycerol. Reagents For the preparation of acid salt solution, the following procedures were used: 1. 60 g of NaCl was dissolved in 5 ml of 37% HCl and diluted to 250 ml mark of a volumetric flask with double-distilled water. For the preparation of sulphate standard, the following were used: 2. 100 mg/L stock standard sulphate solution was prepared by dissolving 0.1479 g of anhydrous Na2SO4 in double distilled water to 1000 ml. 3. Working solutions of 15, 20, 25, 30 and 35 mg/L concentrations was prepared daily by appropriate dilution of the stock. For calibration the following were used: 4. 10 ml of the standard sulphate calibrants solutions was quantitatively transferred into separate test tubes. 5. To each test tube, 1 ml of acid salt solution, 0.5 ml of concentrated glycerol solution and 0.5 g BaCl2 were added. 6. The resulting cloudy solution was shaken for 60 seconds and left for 5 minutes. 7. Appropriate aliquot of the cloudy solution was transferred into 1 cm cell and the absorbance of the coloured solution was measured at a wavelength of 420 nm on the UV-visible spectrophotometer. 66 University of Ghana http://ugspace.ug.edu.gh 8. The absorbance of each calibrant solution was plotted against the concentration of the calibrants. 9. A straight-line graph was obtained. 10. The concentration of the water samples was deduced from the graph after measurement of the absorbance of each water sample at a wavelength of 420 nm on the UV-visible spectrophotometer For the Measurement of Sulphate in the surface water and groundwater samples, the following was used: 11. 10 ml aliquot of the water sample was transferred into a 20 ml test tube and the same procedure as used for the establishment of the calibration graph was followed to obtain the absorbance of each water sample at a wavelength of 420 nm on the UV-visible spectrophotometer. The sulphate concentration of the water samples was deduced from the graph after measurement of the absorbance of each water sample at a wavelength of 420 nm on the UV-visible spectrophotometer. For QA/QC measurement: 12. Duplicate water samples were analyzed after every batch of five water samples. 13. A control standard of 10 mg/L SO 2-4 was prepared and analyzed together with the samples. 14. The value of the control standard was plotted on the control chart and the values that fall outside the action limits (±3σ) was reanalyzed with a fresh control standard. 3.2.6.8. Determination of Nitrate (NO -3 ) at the Laboratory of Nuclear Chemistry and Environmental Research center, Ghana Atomic Energy Commission. Principle The method used is based on the reaction of the nitrate ion with brucine sulfate in a H2SO4 solution at a temperature of 100 °C. The yellow colour of the resulting complex is measured 67 University of Ghana http://ugspace.ug.edu.gh at a wavelength of 410 nm. Nitrate was determined using AOAC Official Method 973.50 (AOAC International, 2007). Preparation of standards A stock standard nitrate solution of concentration 100 mg/L was prepared by dissolving 0.7218 g of KNO3 (pre-oven dried at 105 ºC for 24 hours) in double distilled water to make 1000 ml of solution. The stock solution was preserved with 2 mL CHCl3. Working calibrant solutions of concentrations 0.2, 0.4, 0.6, 0.8, and 1.0 mg L-1 were prepared daily by the appropriate dilution of the stock. Preparation of reagents (Brucine-sulfanilic acid reagent) 1. 1 g of brucine sulfate [(C23H26N2O4)2H2SO4 7H2O] and 0.1 g sulfanilic acid (NH2C6 H4SO3H H2O) were dissolved in 70 mL warm double distilled water. 2. 3 ml concentrated hydrochloric acid was added. 3. The resulting solution was cooled and diluted with double distilled water to 100 ml mark of a conical flask. 4. The prepared reagent was stored in a dark bottle at 5 °C. Calibration 7. 5 ml of each calibrant solution was pipetted into separate 20 mL test tubes. 8. To each test tube, 1 ml of 30% NaCl was added, followed by the addition of 5 ml of 6.5 M of H2SO4. 9. The test tubes with the solution were swirled to ensure thorough mixing of the reagents. 10. 0.5 ml of brucine-sulfanilic acid reagent was added to the content of each tube (except blank) 11. The test tubes with the solution were placed on a rack and lowered into a water bath at 95 ºC for 25 minutes. 68 University of Ghana http://ugspace.ug.edu.gh 12. An appropriate aliquot of the yellow coloured calibrant solutions was transferred into a 1 cm cell. 13. The cell was placed into the spectrophotometer and the absorbance of the solution was measured at a wavelength of 410 nm. 14. A standard graph of absorbance of standards against concentration of standards was plotted. Measurement of Nitrate in the water samples 15. 5 ml aliquot of the water samples were transferred into separate 20 ml test tube and the same procedure as used for the establishment of the calibration curve was followed in order to obtain the absorbance of each water sample at a wavelength of 410 nm on the UV-visible spectrophotometer. 16. The concentration of nitrate in each water sample was deduced from the calibration graph. The concentration of nitrate was calculated from the relation: C − = CCalib.  D f Eq (3.20)NO 3 Where: C − is the nitrate concentration, CCalib. is the concentration from the calibration curve NO3 and D f is the dilution factor. Measurement of QA/QC 17. Duplicate water samples were analyzed after every batch of five water samples. 18. A control standard of 0.5 mg/L nitrate was prepared and analyzed together with the samples. The value of the control standard was plotted on the control chart and those that fell outside the action limits (±3σ) were reanalyzed with a fresh prepared control standard. 69 University of Ghana http://ugspace.ug.edu.gh 3.2.6.9. Measurement of Silica in surface water and groundwater at SGS Laboratory in Tema, Ghana 1. 2 ml ammonium molybdate reagent and 1.0 ml 1-1 HCl were added to 50 ml of the water sample in rapid succession. 2. This was mixed by reversing at least six times and allowed to stand for five to ten minutes. 3. 2 ml oxalic acid solution was added and mixed thoroughly. 4. The colour was read after 2 minutes at a wave length of 410 nm. 5. To correct for turbidity and colour, a blank was prepared by adding hydrochloric acid and oxalic acid without the addition of molybdate reagent. 6. Thermo Scientific* Aquakem 250 Photometric analyzer was adjusted to zero absorbance with the blank containing no molybdate before reading absorbance of molybdate-treated samples. 7. Silica concentration in the water sample was directly determined from the calibration curve of the photometer. For quality control (QC) and quality assurance (QA), blanks were analyzed after every batch of 5 water samples. Additionally, a control standard of 10 mg/L of Silica was prepared and analyzed together with the samples. 3.2.6.10. Measurement of Arsenic (As) in the water samples at the Laboratory of Nuclear Chemistry and Environmental Research Center, Ghana Atomic Energy Commission. Instrumentation for Arsenic (As) measurement in the water samples Total arsenic (As) was determined using the HG-AAS technique. The HG-AAS system consist of an AA 240FS fast sequential Atomic Absorption Spectrometer (with a deuterium background corrector) equipped with a VGA-77 vapor generator (Varian, Australia). The Varian’s Vapor Generation Accessory (VGA-77) employs a peristaltic pump to provide 70 University of Ghana http://ugspace.ug.edu.gh continuous generation of flow vapor. The radiation sources involve the hollow cathode lamp of As (wavelength 193.7 nm; spectral slit width 0.5 nm; lamp current 10 mA) and the hollow cathode lamp of Hg (wavelength 253.7 nm; spectral slit width 0.5 nm; lamp current 4 mA) (Varian, Australia). ETHOS 900 microwave digester (Milestone, USA) is used for the sample water digestion. Chemicals and Reagents for As measurement in the surface water and groundwater samples All solutions was prepared from analytical reagent grade chemicals: Commercially available stock standard solution [(1000 ± 4 mg As L-1 in 2% (w/w) HNO3, Trace CERT®, Fluka Chemie, Switzerland)], Commercially available stock standard solution [(999 ± 4 µg Hg ml in 1.4% (w/w) HNO3, Spectrascan, Teknolab AB, Sweden], Sodium borohydride (NaBH4), Sodium hydroxide (NaOH), Nitric acid (65% HNO3), Hydrochloric acid (37 % HCl), Hydrogen peroxide (30%, H2O2). Reagents 1. For As determination, hydride generation was performed with a 0.6% (w/v) NaBH4 in 0.5% (w/v) NaOH as the reductive solution with 6 M HCl as the carrier solution. Standards Calibration standards for As (0.2, 0.4, 0.6 mg L-1) was prepared daily by appropriate dilution of the respective commercial stock standard solutions for As. Digestion of the water samples for As measurement was done in accordance with standard procedures setup by Hoeing et al. (1998). 71 University of Ghana http://ugspace.ug.edu.gh Experimental procedure Digestion Digestion of water samples was done according to the procedure described by Hoeing et al. (1998) and below is an outline of the procedures. 2. 6 ml of HNO3 (65%), 3 mL of HCl (37%) and 0.25 ml of H2O2 (30%) were added to 5 ml of the water sample in a Teflon digestion tubes. 3. The tubes were covered tightly and placed in an ETHOS 900 microwave digester. 4. The water samples were digested using a four-step digestion procedure (Table 3.2). 5. At the end of the digetion, the digested water samples were cooled and transferred into a clean 25 ml volumetric flask. 6. The digested samples were diluted to 20 ml with double-distilled water. 7. To reduce all As5+ to As3+, 4 ml of freshly prepared 5 M KI was added to the digested water samples 8. .This was followed by hydride generation and subsequent measurements using the Atomic Absorption Spectroscopy. Table 3.2: Microwave digestion programme used for the digestion of the water samples Digestion Digestion Microwave Step Time (min) Power Pressure Temperature 1 Temperature 2 (W) (bar) (oC) (oC) 1 5 250 100 400 500 2 1 0 100 400 500 3 10 250 100 400 500 4 5 450 100 400 500 Temperature 1 and temperature 2 represent, the initial and final digestion temperatures Reduction of As5+ to As3+ To reduce all As5+ to As3+, 9. 4 mL of freshly prepared 5 M KI was added to the digested solution. 10. This was followed by hydride generation and measurement by the atomic absorption spectroscopy. 72 University of Ghana http://ugspace.ug.edu.gh Calibration 11. The HG-AAS system was calibrated with As standard calibrants (0.2, 0.4, 0.6 mg As L-1) and the obtained absorbance were used for linear regression analysis (plot of absorbance against the concentration of the calibrants). 12. The concentration of As was deduced from the equation of the regression line. Hydride generation and atomic absorption measurement 13. The continuous flow approach of an HG-AAS system was used to merge the water samples and the reagents. 14. The sample solution (flow rate 5 mL/45 sec) was mixed in a PEEK (polyetheretherketone) cross connector with both HCl (flow rate 5 mL/45 sec) and NaBH4 (flow rate 5 mL/45 sec) solutions (both solutions pumped and added with the peristaltic pump) and pumped into the reaction coil. − 15. During mixing, the tetrahydroborate ion, BH4 converts As (III) into a hydride (AsH3). 16. The tetraborohydrate was hydrolyzed in the presence of HCl producing considerable hydrogen. 17. The gaseous hydride formed together with the hydrogen gas generated were separated from the liquid in the A-shaped gas-liquid separator component of the vapour generator, and then transferred with a flow of argon gas into a Perma-pure dryer and dried by a stream of nitrogen gas. 18. The liquid was released as waste and the gaseous hydride and excess hydrogen formed were swept out of the vapour generation vessel by an argon gas (flow rate 13.5 mL min- 1) into the AAS detection system. 19. In the detection system, AsH3 was atomized in the air-acetylene flame (also fed by the excess hydrogen generated) aligned in the light path of As lamp in the atomic absorption spectrometer. 73 University of Ghana http://ugspace.ug.edu.gh 20. Absorbance measurements were recorded, and the concentration deduced from the regression line. Calculation of Arsenic concentration The concentration of As in each water sample was obtained from the equation of the regression line. The concentration of As in the water sample (mg L-1) was done using the relation; ConcAs = Conccalib  Df Eq (3.21) Where: D f is dilution factor, and Conccalib is the concentration from the calibration curve. Where: D f is dilution factor, and Conccalib is the concentration from the calibration curve. To ensure quality control (QC) and quality assurance (QA), blanks were prepared using the same procedure above. 3.2.6.11 Measurement of trace elements (Cu, Cd, Zn, Cr, Fe, Ni, Mn, Co, Pb, As and Al) in the water samples at the Laboratory of Nuclear Chemistry and Environmental Research center, Ghana Atomic Energy Commission. Instrumentation, Chemicals and Standards Instrumentation Fast Sequential Atomic absorption spectrometer (VARIAN, AA 250 FS, Australia) was used for atomic absorption measurement (Fig 3.8) of trace elements in the water samples. 74 University of Ghana http://ugspace.ug.edu.gh Figure 3.8: Fast Sequential Atomic absorption spectrometer (VARIAN, AA 250 FS, Australia) used for the analysis of trace elements. Chemicals The under-listed commercially available stock standard solutions of Cd, Cr, Cu and Fe were used: 1000 ± 4 mg Cd L-1 in 2% (w/w) HNO3, 1000 ± 4 mg Cr L-1 in 2% (w/w) HNO3, 1000 ± 4 mg Cu L-1 in 2% (w/w) HNO3, and 1000 ± 4 mg Fe L -1 in 2% (w/w) HNO3 (Trace CERT®, Fluka, Chemie, Switzerland). Atomic Absorption Measurement The instrumental conditions used for flame atomic absorption spectrometric determination of Cd, Cr, Cu, Fe, Co, Pb, Ni and Zn were as follows: 1. the air-acetylene flame atomizer was made up of air as oxidant (flow rate: 13.50 L/min) and acetylene as fuel (flow rate: 2 L/min). Calibration of atomic absorption spectrometer 2. The atomic absorption spectrometer was calibrated with calibration standards for the above-mention trace element. 3. The absorbances obtained were used to plot calibration graphs for each trace element. 4. After calibration, each element was determined by measurement of absorbances of the surface water and groundwater samples aspirated into the absorption cell. 75 University of Ghana http://ugspace.ug.edu.gh Calculation of concentration 5. The concentration of each analyte in the water samples was calculated from the calibration curve for the analyte. 6. In cases where there was a dilution of water sample, the concentration deduced from the calibration graph was multiplied by a dilution factor to give the actual concentration of the analyte in the surface water and groundwater sample. Quality Control and Quality Assurance Validation of the analytical technique Calibration Procedure AAS as an analytical method for the measurement of trace metals is affected by many factors including the calibration and standards preparations procedure. The quality of the results obtained was assessed by checking the linearity for the calibration lines for standards prepared (Table 3.3). Under ideal condition this was supposed to give a correlation of unity(r2 = 1) each, but due to systematic and random errors encountered during measurements, the correlation of unity could not be perfectly met. Table 3.3: The correlation coefficient of the calibration lines of the trace elements Metal r2 (coefficient of correlation) Fe 0.93 Cu 0.95 Zn 0.94 Pb 0.99 Cr 0.93 Cd 0.92 As 0.96 Mn 0.94 Analytical Method Detection Limit Method detection limit (MDL) is the minimum concentration of analyte that can be recognized, measured and reported with 99% confidence that the analyte concentration is greater than zero. MDLs for trace metals varies based on the wavelength selected, the spectrometer configuration and operating conditions. 76 University of Ghana http://ugspace.ug.edu.gh Reagent blank (HNO3/HClO4/H2O2) was used to establish the MDLs for each surface water and groundwaterwater sample. In the analyses, seven replicates of both samples were measured for each trace metal. Since the values for water blank was below the detection limits for the metals, the detection limits of the instrument for each trace metal was taken as detection limit for the metals (Table 3.4) Table 3.4: MDLs for the water samples Detection Limits Element IDLs* (mg/L) MDLs*water (mg/L) Fe 0.006 0.006 Cu 0.003 0.003 Zn 0.001 0.001 Pb 0.001 0.001 Cr 0.001 0.001 Cd 0.002 0.002 As 0.001 0.001 Mn 0.002 0.002 IDLs and MDLs of water are the instrumental detection limit and method detection limit of water respectively. Validation with Reference Material Fluka∙ Analytical is a certified reference material (CRM) produced and certified in accordance with ISO/IEC 17025 and ISO Guide 34. This CRM is used to check for the correctness of the methodology. Recovery Test For environmental studies, recoveries are expected to fall within the range of 80 to 115%, and the results obtained fell in this range ( table 3.5). Thus, the recoveries range between 85.44 to 105.00%. Table 3. 5: Percentage recoveries of the various metals analysed Metal CRM Std.CRM* Amount Recovered (mg/L) Mean Recovery number (mg/L) 1 2 3 (%) for metals Fe 16596 2.000 1.962 1.968 1.983 1.971 98.55 Cu 38996 2.000 1.978 1.980 1.989 1.982 99.12 Zn 18827 0.300 0.255 0.256 0.258 0.256 85.44 Pb 16595 1.000 1.936 1.900 1.908 1.915 95.73 Cr 02733 1.000 0.989 0.952 0.974 0.972 97.17 Cd 51994 0.500 0.498 0.490 0.502 0.497 99.33 CRM is standard solutions from the CRM (Fluka∙ Analytical) of each metal. 77 University of Ghana http://ugspace.ug.edu.gh 3.2.6.12 Measurement of trace elements (Cu, Cd, Zn, Cr, Fe, Ni, Mn, Co, Pb, As and Al) in the water samples at the Laboratory of Environmental, Informatics and Statistics, Ca Foscari University of Venice, Italy. Instrumentation Measurement of trace element in the water samples were also performed using ICP- MS (PerkinElmer® Optima™ 7000 DV ICP-OES instrument, Inc. Shelton, CT, USA) instrument equipped with winLab 32 for ICP Version 4.0 software for simultaneous measurement of all selected trace element wavelengths (Fig 3.9). Figure 3. 9: ICP-MS used for the measurement of trace elements in the water samples. Standards, chemicals and Certified Reference Material (CRM) Working standards were prepared by using PerkinElmer NIST® traceable quality control standards for ICP or ICP-MS (N9300235, N9300233 and N9300234) as the stock standards. Calibration was done using three standards with each trace element represented by one standard. The calibration blank consists of ASTM® type one, acidified with nitric acid. 78 University of Ghana http://ugspace.ug.edu.gh Two QC samples consisting of a continuing calibration blank (CCB) was prepared at the midpoint of each calibration. This was run to monitor the long-term solidity of the instrument and it was done after drawing of the calibration curves. Preparation of standards were done in ASTM® type I water and Suprapur® nitric acid (Merck®, Germany) was used for the acidification of the standard. PerkinElmer Quality Control Check standards for ICP/ICP-MS (N9300233, N9300234 & N9300235) was used to prepare the quality control check standard solution. On a daily bases, working standards were prepared in polypropylene vials. This was done on the basis of volume-by-volume dilution. The solution was pipetted using Micro pipettes (Eppendorf®, Germany) with disposable tips. The above method was validated using several certified surface water and groundwater reference materials from high purity standards. Internal Standards 2.5 mm Y was used to spike all solutions. A single element stock solution of Y 1000 ppm was used to make the spiking solution. Sample Preparation All the water samples were filtered through acid treated 0.45 μm mesh millipore disposable filters, into a pre-conditioned polyethylene – terephthalate (PET) bottle. The filtered water samples were acidified to pH less than 2 with ultra-purified 6mol/ L of HNO3. It is then preserved at a temperature of 4°C. The concentration of the dissolved trace elements was analysed using ICP-MS. QA/QC Quality control standards were used to produce calibration curves, and the curves were used to evaluate the data for each surface water and groundwater sample. Blanks, reagents, and water samples were parallel measured six times. The average of the last three values were employed because the first three values were used to clean the pipe in order to prevent contamination by 79 University of Ghana http://ugspace.ug.edu.gh the last water sample. Relative standard deviation (RSD) of the three results was computed and were seen to be less than 5% of all the analysed trace element content in the water samples. 3.2.6.13 Measurement of Stable Isotopes of Water (δ18 O and δ2 H) using Los Gatos Research instrument at the National Isotope Hydrology Laboratory of the Ghana Atomic Energy Commission. Instrumentation Determination of stable isotopes (δ2H and δ18O) composition in the water samples was accomplished using the Los Gatos DLT-100 Liquid-water Stable Isotope Analyzer [off-axis integrated cavity output spectroscopy (OA-ICOS) via laser absorption] (Los Gatos, CA, USA) (Fig 3.10). The equipment was made up of a laser analysis system, an internal computer, a CTC LC-PAL liquid autosampler (Sigma-Aldrich, USA), a small membrane vacuum pump, and a room air intake line that passes air through a Drierite column for moisture removal. The autosampler and the DLT-100 was connected to a ~1 m long polytetrafluoroethylene (PTFE) transfer line. A 1.2 μL microliter syringe (Model 7701.2N, Hamilton) was used to inject 0.75 μL of sample through a PTFE septum in the autosampler. Figure 3. 10: Isotopic composition analysis (δ2 H and δ18 O) of the water samples using Los Gatos DLT-100 Liquid-water Stable Isotope Analyzer. 80 University of Ghana http://ugspace.ug.edu.gh Reference Material The validity of the isotopic composition analysis (δ2 H and δ18 O) using the liquid-water stable isotope analyser was checked using the analysis of International Atomic Energy Agency (IAEA) reference material, GISP [(Water) (δ2H VSMOW and δ18O VSMOW)]. This reference material is also known as NIST RM 8536 and it is developed by the IAEA in cooperation with the United States National Institute of Standards and Technology (NIST). Standards Three secondary standards were used for the analysis: two calibration standards [prepared from IAEA reference material, GISP (Water; δ2H VSMOW and δ18O VSMOW)], and a control standard (‘in-house’ prepared). Calibration standard 1: STD1 (WS1)-enriched: δ2H = 2.10 ± 0.3Hg and δ18 O = 0.24 ± 0.03. Calibration standard 2: STD2 (WS2)-depleted: δ2H = -117.00 ± 1.0 and δ18 O = -15.55 ± 0.1. Control standard 3: STD3 (CS2)-control: δ2 H = -68.78 ± 0.6 and δ18 O = -9.6 ± 0.8. Experimental procedure The experimental procedure is according to the methods prescribed in the IAEA training course series 35 [IAEA laser spectroscopic analysis of liquid samples for stable hydrogen and oxygen isotopes], (IAEA, 2009). The procedure is as follows: 1. About 1 mL aliquot of each standard (in-house, working and control) and 1 mL aliquot of the water sample were quantitatively transferred into 1.5 mL autosampler glass vials using the 1000 μL Eppendorf disposable tip pipette. 2. 1.5 mL autosampler glass vials were capped with PTFE septum caps. 3. The samples and standards were arranged on a CTC LC PAL autosampler. The arrangement of the samples and the standards on the autosampler was done with respect to the following procedure (IAEA, 2009): 81 University of Ghana http://ugspace.ug.edu.gh 4. A dummy sample (de-ionized water or tap water) was placed in the first position to prime the flow line. 5. The dummy vial was followed by three secondary standards (two calibration standards and a control standard); five water samples, followed by another set of the three standards. 6. The array of standards and water samples were repeated up to a maximum of six times (30 water samples) for a single run. 7. Each standard and sample were individually measured with six injections lasting about 25 minutes. 8. Measurement for each batch of 30 samples lasted for a period of 20 hours. 9. The measurement results for the last four of the six injections from each vial was averaged. 10. The measured and known δ values of calibration standards before and after each batch of five water samples was used for a linear regression to convert absolute isotope ratios to δ values. 11. The instrument was prone to give erratic results during the start of a run, the dummy sample used allowed the system to stabilize before the first standards were run on the liquid-water analyser (IAEA, 2009). 12. The arrangement of the vials in the CTC LC PAL autosampler was designed to overcome the effects of instrumental drift which could be significant during a daily run (IAEA, 2009). 13. The first two injections were disregarded because they were often less stable and the injections with the most potential for carrying a memory effect from the previous sample (IAEA, 2009). 82 University of Ghana http://ugspace.ug.edu.gh 3.2.6.14 Picarro Cavity ringdown spectrometer instrument for the measurements of stable isotopes (δ18O and δ2H ) at the Laboratories of Environmental, Statistics and Informatics, Ca Foscari University of Vernice, Italy. Instrumentation and procedures The instrument used was the Picarro L2130-I cavity ringdown spectrometer (Fig 3.11). The instrument was based on wavelength-scanned cavity ring down spectroscopy, and it was equipped with an autosampler. In this technology, light re-circulates severally through the sample, forming a very long operational path length of the water sample to work together with the light. The principle behind the instrument is that, it adopts time- based optical absorption spectroscopy of target gasses for the determination of δ18O and δ2 H in the water samples. The isotopic standards used included SLAP2 (Standard Light Antarctic Precipitation- 2) and the isotopic reference standards VSMOW- 2 (Vienna Standard Mean Ocean Water- 2) obtained from NIST (National Institute of Standards and Technology) and IAEA (International Atomic Energy Agency). In obtaining the standards, all measurements were calibrated and normalized to VSMOW. The instrument had a precision of approximately ±0. 5‰ VSMOW for δ2H and ±0. 10‰ VSMOW for δ18O. For sample preparation, 2 ml of each surface water and groundwater sample was transferred into vials which had caps with a septa appropriate for use with the auto- sampler syringe. The transfer was done using a clean dry pasteur pipette. 2 μL of n- methyl-2 pyrrolidone (NMP) wash solvent, 2μL deionized water and 2µL of the water samples were used to wash the syringe once the autosampler is set. This is done before active measurement of each vial was taken. Also, six separate 2μL injection of the water samples in the vials were analysed after rinsing. The first three injection data were thrown away to reduce any probable contamination from previous water samples. This resulted in three isotopic measurements for each vial. The analytical method involved 25 vials (one for each water sample), a consistency standard in the middle enclosed by international standards, as well as the consistency standards. All these 83 University of Ghana http://ugspace.ug.edu.gh formed the calibration line. Measurement of the water samples were fitted to the corresponding line for each group of 25 samples, one each for δ18O and δ2 H measurements, creating the calibrated measurements. To assess variance and increase analytical confidence, a number of water samples were reanalysed. Standard deviations for each triplicate analysis were calculated using the equation: (𝑋−𝒳)2 𝑆𝐷 = √∑ ………….. Eq (22) (𝑛−1) Where X is each measurement of the set, 𝒳 is the statistical mean of the set, n is the number of samples. Dixons Q- test with 90% confidence level (CL90%^) was used to evaluate possible data outliers and it’s given by; 𝑋 𝑋 𝑄𝑒𝑥𝑝 = 2− 1 …………….. Eq(23) 𝑋𝑛−𝑋1 Qexp > Qcrit (reject outlier) Where X1 is the suspect value, X2 is the closest value to the suspect, and Xn – X1 is the range of the data. Figure 3. 11: Picarro L2130-i used for the measurement of δ18O and δ2H in the water samples with its auto sampler. 84 University of Ghana http://ugspace.ug.edu.gh The obtained isotopic composition values in the surface water and groundwater samples were passed through, a post-processing procedure expressed as: δ=((Rs-Rstd)/Rstd) ˟ 1000 ……………. Eq 3.24 where Rs = the isotope ratio (2H/1H, 18O/ 16O) of the sample Rstd = the isotope ratio (2H/ 1H or 18O/ 16O) of the standard. The above equation was used to compute the delta-scale (δ) values and it was done in accordance with Vienna Standard Mean Ocean Water (VSMOW). Delta values were expressed in parts per thousand (per mil ‰) deviation from the standard, however the global adopted standard for the measurements of deuterium and oxygen-18 was SMOW (Standard Mean Ocean Water) which later became the Vienna-SMOW (V-SMOW). The oxygen-18 for V-SMOW is similar to that of SMOW but the deuterium content is 0.2‰ lesser. Thus, for all practical uses, SMOW and V-SMOW are considered identical since the accuracy of measurements is usually 1‰ and 0.1‰ for deuterium (δ2 H) and oxygen- 18 (δ18O), respectively. When water changes state through vaporisation and condensation, isotopic fractionation occurs due to differences in vapour pressures and diffusion velocities in air of the different isotopic species of water (Sidle, 1998). The degree of isotopic fractionation is contrariwise in relation to temperature. There is seasonal change in the stable isotopic compositions of rainfall at a given area, with more depleted values occurring in the colder months. More depleted values are also seen at upper latitudes. Rainfall falling at higher elevations are more depleted than those falling at lower elevations; this final property is of specific utility in the hydrological cycle. Rainfall at continental locations is more depleted than those that fall nearer to the coast (Fritz & Fontes, 1980; Clark & Fritz, 1997). Under equilibrium condition, evaporation does not take place, that is in contrast to the condensation process. Also, the actual fractionation features are greater than the equilibrium values. When water undergoes evaporation, the lighter isotopic species (1H2, 18O) specially leave the surface, so the remaining 85 University of Ghana http://ugspace.ug.edu.gh water becomes enriched in the heavier isotopic species (1H2 18O or 1H 2H 18O) (Kendal & McDonnell, 1998; Singh & Kumar, 2005). The degree of enrichment depends on the relative humidity of the atmosphere, the temperature, and the hydrological balance of the surface water. The enrichment of δ18O is about one order of magnitude less than that of δ2H. An important process which controls the enrichment of the surface water is molecular exchange, which occurs between the atmospheric water vapour and the surface water. The δ2H and δ18O values of natural waters obey the general relation: 𝛿2 𝐻 = 𝑎𝛿18 𝑂 + 𝑑 after (Criag, 1961b) ……. Eq 3.25. For water which have not been subjected to evaporation, the value of a‘is 8 and the average global value of d for precipitation is 10. The deuterium excess (d), the intercept of the Global meteoric water line (GMWL) is defined as: 𝑑 = 𝛿2 𝐻 − 8𝛿18𝑂 (Dansgaard, 1964) …………. Eq 3.26 Therefore, in this study, the results of the isotopic composition of rainfall samples were separated into dry season samples and wet season samples, and regression lines for each season was obtained using eq 3.18. The regression line for each season was used as reference lines in discussing the isotopic composition in both surface water and groundwater on the δ2H/δ18O diagram illustrated in chapter 4. 3.2.6.15. Measurements of Tritium (3H) in the water samples conducted at the Laboratory of Geology, University of Trieste, Italy. Tritium activity measurement involves two major parts. In the first part, tritium in the water samples was pre-concentrated using electrolytic enrichment. After, the samples were distilled to a conductivity value of 25 µS/cm. The distillation was done to remove impurities which may cause corrosion of the electrodes. During the electrolytic process, which was the second part, two grams (2g) of peroxide were added to the water samples in 500 ml standard glass flask. 86 University of Ghana http://ugspace.ug.edu.gh After, the solution was poured into an electrolytic cell, weighed and the initial mass of water (Wi) recorded. After, the electrolytic cell with the solution was subjected to electrolysis resulting in the release of O2 and H2 at the cathode and anode, respectively. After electrolysis, the cells were weighed, and the final mass of water was recorded as Wf. Subsequently, the samples were transferred from the cell into a distillation flask, neutralized with 8g of PbCl2, and subjected to final distillation. A mixture between the final distillates and a cocktail was poured into polyethylene vials. The vials, together with two dead water (water without tritium) and two standards were placed on the Liquid Scintillation Counter (LSC) for tritium activity measurement. This was done to estimate the tritium enrichment parameter and the calibration of the equipment. All the tritium samples, numbering 57 was analyzed at the Department of Geology, University of Trieste, Italy. The above methodology for the measurement of tritium in the water samples was illustrated below: 𝑊𝑖 = 𝑊𝑐𝑓 − 𝑊𝑐𝑒 …………… Eq 3.27. Where Wi = initial weight of the sampled water Wcf = weight of the empty cell plus the sampled water Wce = weight of the empty cell During electrolysis of the empty cell plus the sampled water, the reactions taking place at the various electrodes are expressed as: Anode: 2OH- → H2O + 2e +1/2 O2 ……………. Eq 3.28 Cathode: 2H2O +2e → 2OH - + H2 ………………….. Eq 3.29 Overall reaction: 2H2O → 2H2 + O2 ……………. Eq 3.30 After electrolysis, the final weight of the cell plus water was expressed as: Wf = Wcf - Wce ………………. Eq 3.31 The enrichment parameter (P-Factor) was expressed as; 87 University of Ghana http://ugspace.ug.edu.gh (𝑊𝑖−𝑊𝑓) 𝐼𝑛 (𝐸) 𝑃 = 𝑄 𝑊𝑖 ……….. Eq 3.32 𝐼𝑛 ( ) 2.975 𝑊𝑓 Where P = average of spike values E = enrichment factor Q = total charge in Ah. The enrichment factor for the tritium is expressed as: 𝑃′𝑎𝑣𝑔 𝑊𝑖 𝐸 = exp ( ) 𝐼𝑛 ( ) ……………… Eq 3.33 𝑊𝑖−𝑊𝑓 𝑊𝑓 3.2.7. Validation of Data Prior to data analysis, an ionic balance of each water sample was evaluated for checking the analytical results. The ionic balance equation per Freeze and Cherry (1979) was given as: (𝑆𝑢𝑚 𝑜𝑓 𝑐𝑎𝑡𝑖𝑜𝑛𝑠−𝑆𝑢𝑚 𝑜𝑓 𝑎𝑛𝑖𝑜𝑛𝑠) 𝐼𝑜𝑛𝑖𝑐 𝐵𝑎𝑙𝑎𝑛𝑐𝑒 = × 100 ………….. Eq (3.34) (𝑆𝑢𝑚 𝑜𝑓 𝑐𝑎𝑡𝑖𝑜𝑛𝑠+𝑆𝑢𝑚 𝑜𝑓 𝑎𝑛𝑖𝑜𝑛𝑠) IBE (Ionic balance error) for the groundwater in the study area was calculated on the bases of ions expressed in mill equivalent per liter for analytical precision for cations and anions measurement. The calculated IBE values for each sampled groundwater are shown in Appendix 15 to 19. The IBE value of the sampled groundwater was within a limit of ±15 % and this was probably due to the omission of constituents such as nutrients, organic anions, and trace elements. These constituents might possibly be a contributing factor to the higher ionic balances (Hem, 1985) recorded in fewer groundwater samples. 3.2.7.1 Treatment of Data The data obtained from the laboratory analyses were examined using different statistical methods like standard deviation, skewness, kurtosis and mean. The skewness and kurtosis analyses were done to assess whether the sampled surface water and groundwater came from a normal distribution. Based on the skewness and the kurtosis, the statistical content found outside the range of -2 to + 2 and -7 to + 7, respectively were considered to depart significantly from normality. 88 University of Ghana http://ugspace.ug.edu.gh The results of the field parameters, chemical data and trace element concentrations were compared to WHO (2011) guidelines for drinking water quality: First Addendum to the third Edition. Pearson correlation between the measured cations, anions and trace elements in the surface water and groundwater were computed to know whether there was any significant linkage, which might reveal strong homology between the ions. Principal Component Analysis (PCA) was not used to demonstrate the relationship between the cations, anions and trace elements in the water samples due to the limited data set for each sampling year. Gorsuch, 1983 recommended at least 100 samples for PCA analysis, and Hatcher, 1994 recommended that the sample size should be larger than five times the number of variables (p) for PCA analysis. Hence, instead of using PCA on the data set, Pearson correlation matrix, bivariate plots and other hydrogeochemical models were employed. The spatial distribution of the physical data, hydrochemical data, trace elemental data and isotopic data were analysed and drawn using ArcGis 10.5 software and the drawing was done based on the topographical map of the study catchment. In addition, the static water levels were computed using Surfer 16.5 software. This was done to identify the general groundwater flow direction. Statistical data analyses performed on all measured variables in the dataset was done using Microsoft excel 2016 version. 3.2.7.2. Data analysis and interpretation This section highlights the statistical analysis and various graphical forms used for the interpretation of the data set. The main analytical error determined was the charge balance error, which had been discussed in previous chapters. The statistical analyses used comprise minimum, maximum, mean, median etc. The major graphical forms used in the interpretation of the results were the chemical indices {water quality index, sodium absorption ratio (SAR), percent sodium (% Na), Wilcox diagram etc.} Ficklin diagram (Manjo et al., 2012; 89 University of Ghana http://ugspace.ug.edu.gh Piper, 1944), diagram (Stiff, 1951), diagram (Gibbs, 1970) plots (Durov, 1948) diagram and mineral stability diagrams. 3.2.7.3. Spatial interpolation methods Spatial interpolation is a numerical model that changes attribute dataset of sampling point into a surface map. This map replicates the spatial changes in a dataset throughout a study catchment. This model used in the generation of maps is a useful tool, which provides sensitive information for decision makers. In this model, there are several computational methods such as inverse distance weighted (IDW), Kriging, natural neighbour spine etc. Nevertheless, the IDW and the Kriging is the interpolation model used mostly in environmental studies. Hence, in this study, the most suitable interpolation tool that reflect the quantity and quality of water in the aquifer system was the IDW model. This was due to variability in the data set, distance between the sampling points and the number of surface water and groundwater available in the study area. Also comparing the performance parameters vis RMSE, R2, RSS for both IDW and Kriging, it was seen that IDW gave a better idea of the prediction accuracy. The IDW model was therefore used to generate spatial interpolation maps for surface water and groundwater in this study. 3.3. Limitation of the Study ➢ This study should have covered the entire Tano Basin for all-inclusive and complete approach towards the characterization of the aquifers to aid in the understanding of the hydrogeology but due to limited funding, this PhD was restricted to the Lower Tano River Basin. ➢ The study could not access the ionic balances for the boreholes drilled in 2013. This is as a result of unavailability of equipment for the measurements of some hydrochemical parameters hence limiting the discussions for 2013 borehole samples. ➢ Due to limited funding, rainfall sampling was carried out from 2016 to 2018. 90 University of Ghana http://ugspace.ug.edu.gh ➢ Due to limited funding, measurement of silica in groundwater was carried out in few selected groundwater samples with respect to their closeness and sampling was done from 2014 to 2015, 2016 and 2017. ➢ Due to inadequate funding, Tritium measurement in the water samples was limited to few surface water and groundwater samples based on the basin topography. ➢ Due to inadequate maintenance, some of the boreholes which were sampled initially could not be sampled during subsequent field sampling. This was because the boreholes had collapsed and some were out of order. 91 University of Ghana http://ugspace.ug.edu.gh CHAPTER FOUR RESULTS AND DISCUSSIONS In this section, the results for each specific objective are discussed. 4.1 Estimation of Aquifer Hydraulic Parameters In this study, the first specific objective was to estimate the aquifer hydraulic parameters, but the depths and the yields are firstly discussed under this section. Table 4.1 contains descriptive statistics of the depths, yields and the computed aquifer hydraulic parameters of the boreholes developed across the Lower Tano River Basin from 2013 to 2015. Table 4. 1: Descriptive statistics of aquifer parameters within the Lower Tano River Basin Parameters SC b K SWL T D Y Number of samples 55 55 55 55 55 55 55 Mean 18.80 45.45 5.70 5.17 205.96 37.67 205.33 Standard Error 5.65 2.13 1.66 0.40 50.03 2.14 25.75 Median 7.47 48.50 2.00 4.09 84.13 41.50 155.00 Mode N/A 53.50 N/A 18.50 N/A 20.00 300.00 Standard Deviation 30.41 11.46 8.91 4.26 269.41 15.42 185.71 Sample Variance 924.68 131.31 79.44 18.14 72580.75 237.75 34489.17 Kurtosis 7.48 -0.07 12.54 3.07 6.34 -1.68 2.73 Skewness 2.76 -0.96 3.17 1.70 2.28 0.04 1.56 Minimum 0.72 19.00 0.04 -0.80 1.73 18.00 10.00 Maximum 122.24 59.00 44.35 20.70 1219.70 62.00 800.00 Sum 545.28 1318.00 165.39 599.72 5972.91 1959.00 10677.00 Confidence Level 11.57 4.36 3.39 0.78 102.48 4.29 51.70 (95.0%) SC- Specific Capacity (L/min/m), b – Aquifer saturated thickness (m), K – Hydraulic conductivity (m/day), SWL – Static Water level (a.m.s.l), T – Transmissivity (m2/day), D – Depth (m), Y – Yield (L/min). 4.1.1 Borehole depths The depths of the newly developed boreholes range from 18 m to 62 m with a mean of 37.67 m. The shallowest depth is measured for a borehole developed at Bankanta, Twene and Agyeza in the aquifer of the Apollonian formation. The deepest depth is recorded for a borehole developed at Bamiankor in the aquifer of the Birimian Supergroup. A spatial distribution map of the borehole depths in the study area is drawn using Inverse distance Weighting (IDW) interpolation in ArcGIS 10.5 software (GIS Geography, 2020). From the interpolated map (Fig 92 University of Ghana http://ugspace.ug.edu.gh 4.1), it is observed that the deeper boreholes represented by shades of red is mostly found in the aquifer of the Birimian Supergroup with fewer representations in the aquifer of the Apollonian formation. The shallowest boreholes represented by shades of blue is dominant in the aquifer of the Apollonian formation. From figure 4.1, it is also seen that the depth (18 to 49.62) of the boreholes developed in the aquifer of the Apollonian formation were shallower than those developed in the aquifer of the Birimian supergroup. Figure 4. 1: Spatial distribution map of the borehole depths drawn using ArcGIS 10.5 Software. 4.1.2 Borehole Yields The yields of the boreholes range from 10 l/min to 800 l/min with a mean of 205.33 l/min. The minimum yield of 10 l/min occurs in a borehole developed at Sameye Barrier 2 in the aquifer of the Birimian Supergroup and the maximum yield of 800 l/m happens in a borehole developed at Keenen and New town, both in the aquifer of the Apollonian formation. The yields of the boreholes in the study area are grouped into three yielding aquifers in accordance with Dike (1960) classification scheme. The aquifers are classified into low, medium, and high. The low yielding aquifer is described as an aquifer that can produce water between 10 l/min 93 University of Ghana http://ugspace.ug.edu.gh to 50 l/min. Such an aquifer is characterized as extensively thick and inadequate for agricultural and industrial usage. The medium yielding aquifer is classified as an aquifer that has the capability of producing water between 50 l/min and 100 l/min. Such an aquifer is described as moderately thick and wide. Additionally, the zone of high yielding aquifer is defined as an aquifer that can produce water between 100 l/min and 300 l/min or more. Such an aquifer is categorized as thick and extensive. In accordance with the above classification, 17.65% (n=55) of the developed boreholes fall in the zone of low yielding aquifer and about 11.76% (n=55) of the developed boreholes falls in the zone of the medium yielding aquifer. The remaining 29.41% of the developed boreholes falls in the zone of high yielding aquifer. From the above classification, it is established that the low yielding aquifer has unproductive bedrock and these are seen mostly in the aquifer of the Birimian Supergroup (Fig 4.2). The medium zone is a good aquifer whose bedrock is moderately productive, and this aquifer is possibly a characteristic of the Birimian Supergroup aquifer (Fig 4.2). This is possible because the rocks of the Birimian are highly fractured with low permeability and porosity. The zone of high yielding aquifer is described as an excellent aquifer with highly productive bedrock. This kind of aquifer is a characteristic of the Apollonian formation aquifer (Fig 4.2). The rocks of the Apollonian are unconsolidated, highly porous, and permeable. The depths of the borehole are plotted against the yields (Fig.4.3) and the graph indicate that the depth of the boreholes developed in the aquifer of the Apollonian formation, and the Birimian supergroup are dependent on the yields. 94 University of Ghana http://ugspace.ug.edu.gh Figure 4. 2: Spatial distribution map of the borehole yields drawn using ArcGIS 10.5 software. Figure 4. 3: Empirical relationship between the yield and the depth of the boreholes drilled in the aquifer of the Apollonian and the Birimian supergroup. 95 University of Ghana http://ugspace.ug.edu.gh 4.1.3 Groundwater Flow direction The water levels vary from -0.8 a.m.s.l to 20.70 a.m.s. l, with an average of 5.17 a.m.s.l. All the water levels measured are above the average mean sea level (a.m.s.l), with the exception of a borehole developed in the aquifer of the Apollonian formation. In this borehole, the water level is below the mean sea level due to the acidity of the borehole water (pH = 5). The low pH of the borehole water aided in carbonate mineral dissolution (Hanshaw & Back, 1979) due to the existence of limestones in the rocks of the Apollonian formsation. The groundwater flow direction as shown in Figure 4.4a and 4.4b are similar. Figure 4.4a and 4.4b shows the controlling factors affecting the groundwater flow direction of the study area. The groundwater is flowing in a downward direction from Northwest (NW), in a higher hydraulic head, towards south west (SE) closer to the sea. This indicates that the groundwater in the Lower Tano River Basin is likely flowing from topographically higher elevation to a lower elevation. Since the aquifer of the Apollonian formation is at a lower elevation, it might possibly be affected by leachates and pathogens. A graph of hydraulic heads against the surface elevation gives an imaginary understanding of the aquifer behaviour (Figure 4.5) with a strong correlation of 0.98. Also, the slope (0.8) (Figure 4.5) and the direction of flow (Figure 4.4 a and 4.4 b) indicates that, the aquifer of the Birimian supergroup are likely a recharging zone whiles the aquifer of the Apollonian formation are likely a discharging zone. 96 University of Ghana http://ugspace.ug.edu.gh Figure 4.4a: Groundwater contour map of the study area in three dimensions. Figure 4. 4b: General groundwater flow direction of the study area 97 University of Ghana http://ugspace.ug.edu.gh Figure 4. 5: Empirical connection between surface elevation and hydraulic heads. 4.1.4 Transmissivity The rate of flow beneath a unit hydraulic gradient through a cross section of unit width and spreading over an entire saturated thickness of an aquifer defines aquifer transmissivity and the unit is m2/day (Akhter & Hasan, 2016). In this study, the estimated aquifer transmissivity values range from 1.73 m2/day to 1219.70 m2/day with an average of 205.96 m2/day. The average aquifer transmissivity value is high and this give an indication that the aquifer of the Apollonian formation and the Birimian supergroup within the Lower Tano River Basin are of good permeability. A borehole developed at Kwekukrom in the aquifer of the Birimian Supergroup records the minimum transmissivity (T) value of 1.73 m2/day. The yield for the borehole was 14 l/min and the aquifer saturated thickness was 47 m. The geological formations observed during drilling contain mostly clay and schist and that might not allow the aquifer to transmit enough water due to its low porous nature. A borehole developed at Sanzule in the aquifer of the Apollonian formation had the maximum transmissivity value of 1219.7 m2/day. The yield for that borehole was 400 l/min and the aquifer saturated thickness was 27.5 m. The geological formation observed during drilling was weathered sandstone and clay particles. The observed geological formation indicates that the 98 University of Ghana http://ugspace.ug.edu.gh Apollonian formation aquifer is highly porous, and its capable of yielding water and store water proficiently. The computed transmissivity values for the newly developed boreholes are grouped per Driscoll (1989) classification. Driscoll (1989) stated that “An aquifer with transmissivity value less than 12.4 m2 /day provides adequate amount of water for domestic use only”. He likewise stated that, “An aquifer with transmissivity value of 12.4 m2 /day or 10 times more was capable of supplying enough water for irrigation, domestic, and industrial uses”. Per Driscoll (1989), classification, 20% of the groundwater sampled from the aquifer of the Apollonian formation and the Birimian super group are yielding enough water for domestic use only and the remaining 80% are yielding more water for domestic, irrigation and industrial uses. An aquifer with least transmissivity (T<12) per Driscoll (1989), was described as an aquifer whose geological formations contain mostly clay or shale. For such an aquifer, low quantity of water is transferred from the aquifer and its only support domestic uses. Additionally, an aquifer with high transmissivity values (T>12) per Driscoll (1989), was characterized as am aquifer whose geological formation contain mostly sand. Such an aquifer produces large quantities of water, can support domestic, irrigational, and industrial uses. Even though, Driscoll (1989), classification was established for European apply countries where groundwater is in high demand, his classification can equally be used in the study area due to rise in population which might increase the growth of groundwater usage. The spatial distribution map (Fig 4.6) for the estimated aquifer transmissivity values shows that transmissivity values ranging from 191.83 to 489.09 m2/day, represented by shades of sea blue colour is dominant in the aquifer of the Birimian Supergroup with few representations in the aquifer of the Apollonian formation. Also, the least transmissivity values represented by shades of red are seen mostly in the aquifer of the Birimian Supergroup with few representations in the aquifer of the Apollonian formation. 99 University of Ghana http://ugspace.ug.edu.gh Figure 4. 6: Spatial distribution map of aquifer transmissivity values for the boreholes drilled in the major rock complexes of the study catchment. 4.1.5 Hydraulic Conductivity Hydraulic conductivity (K) is the ability of a material to transmit water and its dependent on the porosity, pore shape and size, degree of sorting, the physical properties of the fluid as well as the usefulness of the interconnection between the pores (Akhter & Hasan, 2016). The estimated hydraulic conductivity (K) values for the drilled boreholes range from 0.04 m/day to 44.35 m/day with an average of 5.70 m/day. The borehole with the least hydraulic conductivity value is the same borehole with the lowest transmissivity value. Similarly, the borehole with the highest hydraulic conductivity content is the same borehole with the maximum transmissivity value. The K values for 96.7% of the boreholes are less than 25 m/day (Fig. 4.7). The observed geological formations during drilling give an indication that the aquifer of the Apollonian formation and the Birimian supergroup are likely to yield large quantities of water, which could support both the growing population and the industries (mining, coconut oil and gas). The maximum K values represented by shades of lemon green (Fig 4.7) covers a few portions of the aquifer of the Birimian Supergroup and the Apollonian formation. 100 University of Ghana http://ugspace.ug.edu.gh Figure 4. 7: A Spatial distribution map of the aquifer hydraulic conductivity values in the major rock complexes of the study area. 4.1.6 Specific Capacity The specific capacity values range from 0.72 l/min/m to 122.24 l/min/m with an average of 18.80 l/min/m. The estimated specific capacity values of the boreholes, which is less than 12 l/min/m represented by shades of blue and ash colour covers mostly the aquifer of the Birimian supergroup with few representations in the aquifer of the Apollonian formation (Fig 4.8). This shows that part of the aquifers are less durable, slightly permeable, and yield enough water for domestic uses only (Johnson et al., 1966). The specific capacity values within a range of 12 l/min/m to 17 l/min/m represented by shades of yellow colour are seen mostly in the aquifer of the Birimian Supergroup with few representations in the aquifer of the Apollonian formations (Fig 4.8). These aquifers are moderately permeable, yields limited quantity of water, and are productive and durable (Johnson et al., 1966). The specific capacity values for the boreholes greater than 17 l/min/m represented by shades of orange and red colour (Fig 4.8) are seen mostly in the aquifer of the 101 University of Ghana http://ugspace.ug.edu.gh Apollonian formation. This aquifer is excellent, durable, highly permeable, and yields adequate amount of water for all socio-economic activities. Figure 4. 8: Spatial distribution map of the aquifer specific capacity in the major rock complexes of the study area. 4.1.7. Sub-Conclusion From the above discussed results, it is observed that the estimated aquifer hydraulic parameters are higher in the aquifer of the Apollonian formation due to high permeability and unconsolidated rocks. The attained results are like results accomplished by Water resources commission, 2012 for the Tano Basin as well as other areas outside the study location but in the same Birimian supergroup rocks (Asante-Annor & Ewusi, 2016; Ganiyu S et al., 2017; Asante-Annor, 2018). 102 University of Ghana http://ugspace.ug.edu.gh 4.2 Assessing the overall quality of surface water and groundwater together with the level of trace element contamination and groundwater suitability for domestic and agricultural purposes Under this specific objective, the results of surface water quality, and groundwater quality and its suitability for domestic and agricultural purposes are discussed. 4.2.1 Surface water chemistry and its suitability for drinking 4.2.1.1 Results of the field data The results of the descriptive statistical analysis of the field data for the sampled rivers and streams for each specific year are shown in Table 4.2 and Table 4.3. 103 University of Ghana http://ugspace.ug.edu.gh Table 4.2: Descriptive statistical summary of the field data measured in the River samples (Sampling year: 2016 and 2017). 2017 2016 Parameter TDS EC Salinity pH T(˚C) TH TDS EC µS/cm Salinity pH T(˚c) TH (mg/L) µS/cm (ppt) (mg/L) (mg/L) (ppt) (mg/L) Number of 14 14 14 14 14 14 9 9 9 9 9 9 samples Mean 650.21 972.79 1.01 6.10 27.81 124.90 74.11 110.37 0.01 6.58 25.93 48.20 Standard Error 518.61 735.54 0.65 0.21 0.76 96.02 24.72 36.90 0.01 0.17 0.32 24.43 Median 51.00 92.10 0.03 6.30 26.85 29.88 54.00 79.80 0.00 6.70 25.70 19.76 Standard 1940.46 2752.15 2.42 0.79 2.86 359.26 74.15 110.69 0.03 0.50 0.96 73.28 Deviation Sample 3765384.18 7574309.70 5.85 0.63 8.16 129064.67 5498.36 12252.02 0.00 0.25 0.92 5370.37 Variance Kurtosis 13.67 13.45 4.61 -1.52 2.48 13.89 7.54 7.57 9.00 0.13 1.18 8.06 Skewness 3.68 3.64 2.39 -0.32 1.83 3.72 2.68 2.69 3.00 0.06 1.26 2.80 Minimum 23.00 36.30 0.00 4.75 25.40 7.49 27.00 40.80 0.00 5.75 24.90 8.50 Maximum 7360.00 10460.00 7.58 7.02 34.20 1371.14 266.00 397.00 0.10 7.43 27.90 240.00 Sum 9103.00 13619.00 14.08 85.36 389.30 1748.65 667.00 993.30 0.10 59.18 233.40 433.82 Confidence 1120.39 1589.04 1.40 0.46 1.65 207.43 57.00 85.08 0.03 0.38 0.74 56.33 Level (95.0%) 104 University of Ghana http://ugspace.ug.edu.gh Table 4. 3: Descriptive statistical summary of the field data measured in the Stream samples (Sampling year: 2016 and 2017) 2016 2017 Parameter TDS EC µS/cm Salinity pH T(˚C) TH TDS EC µS/cm Salinity pH T (˚C) TH (mg/L) (ppt) (mg/L) (mg/L) (ppt) (mg/L) Number of 15 15 15 15 15 15 15 15 15 15 15 15 Samples Mean 58.07 86.55 0.00 6.25 26.70 20.42 77.73 132.62 0.04 6.22 26.82 37.78 Standard Error 7.95 11.88 0.00 0.08 0.31 5.21 14.97 24.78 0.01 0.12 0.37 8.97 Median 46.00 68.20 0.00 6.30 26.80 14.84 62.00 111.30 0.03 6.30 26.30 21.87 Standard 30.79 46.00 0.00 0.31 1.20 20.17 57.96 95.97 0.05 0.45 1.41 34.73 Deviation Sample 948.07 2116.17 0.00 0.10 1.43 406.97 3359.78 9209.41 0.00 0.20 2.00 1206.42 Variance Kurtosis 2.16 2.16 0.00 -1.10 -1.22 5.80 0.20 0.13 4.36 0.30 3.24 1.37 Skewness 1.67 1.67 0.00 0.07 0.06 2.37 1.15 1.10 1.98 -0.34 1.77 1.51 Minimum 28.00 42.00 0.00 5.78 24.70 4.20 21.00 38.70 0.00 5.40 25.00 6.30 Maximum 132.00 197.30 0.00 6.75 28.50 80.93 195.00 346.00 0.20 7.10 30.60 115.13 Sum 871.00 1298.20 0.00 93.76 400.50 306.29 1166.00 1989.30 0.66 93.30 402.30 566.70 Confidence 17.05 25.47 0.00 0.17 0.66 11.17 32.10 53.14 0.03 0.25 0.78 19.23 Level (95.0%) 105 University of Ghana http://ugspace.ug.edu.gh From the above tables (Table 4.2 and 4.3), the pH of the rivers and streams sampled during the rainy season in 2016 ranges from 5.75 to 7.43 with a median value of 6.70 and a mean of 6.58, and from 5.78 to 6.75 with 6.30 as the median value and 6.25 as the mean value, respectively. Also, the pH in the 2017 (dry season) sampled rivers and streams varies from 4.75 to 7.02 with a median of 6.30 and a mean of 6.10, and from 5.40 to 7.10 with a median value of 6.30 and a mean value of 6.22, respectively. The pH values for the rivers and streams sampled in 2016 and 2017 are acidic to neutral and are not close to the acceptable WHO (2011) pH value of 6.5 to 8.5 for drinking water. As such, they do not satisfy the standard requirement for domestic uses and aquatic life. The total dissolved solutes (TDS) in the rivers and streams sampled in 2016 during the rainy season ranges from 27 to 266 mg/L with a mean of 74.11 mg/L and a median of 54 mg/L, and from 28 to 132 mg/L with an average of 58.07 mg/L and a median of 46 mg/L, respectively. In 2017 during the dry season, the TDS content in the sampled rivers and streams varies from 23 to 7360 mg/L with a mean of 650.21 mg/L and a median of 51 mg/L, and from 28 to 132 mg/L with a mean of 58.07 mg/L and a median of 46 mg/L, respectively. All the sampled rivers and streams for both years and seasons had TDS values below WHO (2011) permissible limit of 500 mg/L for drinking water, except the Ankobra River and Eleneano River which was sampled during the dry season. Cañedo-Argüelles et al. (2013) stated that “Human activities such as water use, mining, industries and agricultural might increase TDS levels in water. From the above statement, agricultural practices are not rampant in the study area but gold mining especially illegal small-scale mining is rampant and most of these miners mine on most surface water or along the banks. This was evidenced during sampling especially the upstream section of the Ankobra river. Additionally, coconut oil industries (large and small) are rampant along the coast and some parts of the hinterlands especially Nkroful. Particles emanating from these 106 University of Ghana http://ugspace.ug.edu.gh industries into the atmosphere might likely settle on surrounding surface water bodies (Eleanor River) through natural process like the harmattan winds. Since air monitoring was not carried out in this study, further investigations must be conducted to ascertain the true cause of the elevated TDS concentration in these two rivers. The high TDS value for the Ankobra River is consistent with the TDS content measured in the Ankobra River in December 2011 by Edjah et al. (2015) The electrical conductivity (EC) content in the rivers and streams sampled in 2016 varies from 40.80 to 397 μS/cm with a mean of 110.37 µS/cm, and a median of 79.80 µS/cm, and from 42 to 197 µS/cm with a mean of 86.55 µS/cm, and a median of 68.20 µS/cm, respectively. In 2017, the EC concentration in the sampled rivers and streams varies from 36.30 to 10460 µS/cm with a mean of 972.27 µS/cm, and a median of 92.10 µS/cm, and from 38.70 to 346 µS/cm with a mean of 132.62 µS/cm, and a median of 111.30 µS/cm, respectively. All the rivers and stream samples are below the WHO (2011) permissible limit of 1500 mg/L for drinking water, apart from Eleneano River and Ankobra River sampled from the rock of the Apollonian formation. The possible reasons accounting for the low and high TDS contents in the rivers and streams as discussed previously holds for the low and elevated EC values in the rivers and streams. There was no significant difference between the values obtained for the TDS and EC concentration in this current study and the previous study {Edjah et al. (2015)} for the rivers and streams, despite the 12 years gap between sampling and seasonal variability. The variation in pH, EC and TDS might be attributed to the seasons and time in which the samples were taken as well as human activities. 4.2.1.2 Results of the Laboratory Data and Alkalinity (as in Bicarbonate) The results of the descriptive statistical analysis of the hydrochemical data for both sampled rivers and streams are summarized in table 4.4, 4.5, 4.6 and 4.7. 107 University of Ghana http://ugspace.ug.edu.gh Table 4. 4: Descriptive statistical summary of the hydrochemical data for the Rivers sampled in 2016 Parameters Ca2+ Mg2+ Na+ K+ Cl- HCO - SO 2- NO - 3 4 3 (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) Number of samples 9 9 9 9 9 9 9 9 Mean 15.76 2.15 20.18 6.57 22.88 34.14 58.70 3.62 Standard Error 10.02 0.79 5.71 2.70 7.20 7.60 24.29 2.86 Median 5.02 1.41 13.20 2.01 17.99 26.82 30.00 0.71 Standard Deviation 30.07 2.37 17.14 8.10 21.61 22.81 72.87 8.59 Sample Variance 904.04 5.59 293.88 65.67 466.82 520.24 5310.20 73.78 Kurtosis 8.56 5.93 1.08 -0.19 5.43 1.83 7.83 8.96 Skewness 2.91 2.34 1.42 1.15 2.19 1.22 2.75 2.99 Minimum 2.03 0.42 4.47 0.30 6.00 9.75 17.85 0.39 Maximum 95.26 8.04 55.14 22.00 75.98 82.90 248.52 26.51 Sum 141.84 19.34 181.63 59.12 205.94 307.23 528.30 32.57 Confidence Level (95.0%) 23.11 1.82 13.18 6.23 16.61 17.53 56.01 6.60 Table 4. 5: Descriptive statistical summary of the hydrochemical data for 2016 Stream samples Parameters Ca2+ Mg2+ Na+ K+ Cl- HCO - SO 2- NO - 3 4 3 (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) Number of samples 15 15 15 15 15 15 15 15 Mean 5.06 1.89 10.55 1.51 12.00 29.67 30.63 1.31 Standard Error 1.52 0.45 1.33 0.65 1.68 4.99 8.23 0.16 Median 2.87 1.37 9.73 0.68 10.00 24.38 34.10 1.27 Standard Deviation 5.89 1.75 5.14 2.54 6.50 19.32 31.87 0.64 Sample Variance 34.71 3.08 26.47 6.43 42.26 373.23 1015.72 0.41 Kurtosis 3.27 10.05 0.12 13.37 1.51 0.98 5.68 0.25 Skewness 2.06 2.95 0.85 3.59 1.40 1.25 1.93 0.28 Minimum 0.74 0.22 4.30 0.33 4.00 7.32 0.00 0.34 Maximum 19.63 7.75 21.29 10.47 27.99 75.59 126.56 2.56 Sum 75.95 28.32 158.23 22.67 179.94 445.00 459.50 19.59 Confidence Level (95.0%) 3.26 0.97 2.85 1.40 3.60 10.70 17.65 0.35 108 University of Ghana http://ugspace.ug.edu.gh Table 4. 6: Descriptive statistical summary of the hydrochemical data for the Rivers sampled in 2017. Parameters Ca2+ Mg2+ Na+ K+ Cl- HCO - 2- 3 SO4 NO - 3 (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) Number of samples 14 14 14 14 14 14 14 14 Mean 8.68 25.07 46.08 10.28 272.06 51.38 30.18 0.62 Standard Error 4.06 20.90 26.34 5.90 233.75 17.04 15.57 0.05 Median 3.61 3.73 12.67 1.82 13.00 29.26 2.95 0.58 Standard Deviation 15.21 78.21 98.57 22.09 874.63 63.77 58.27 0.20 Sample Variance 231.26 6116.39 9716.55 487.95 764973.81 4067.23 3395.94 0.04 Kurtosis 12.04 13.95 12.30 10.65 13.72 9.23 2.91 0.80 Skewness 3.39 3.73 3.45 3.19 3.69 2.88 1.98 1.07 Minimum 1.19 1.10 4.99 0.19 4.00 7.32 0.00 0.40 Maximum 59.97 296.60 380.00 83.06 3298.94 256.03 181.15 1.07 Sum 121.47 350.98 645.08 143.88 3808.79 719.32 422.59 8.63 Confidence Level (95.0%) 8.78 45.16 56.91 12.75 505.00 36.82 33.65 0.11 Table 4. 7: Descriptive statistical summary of the hydrochemical data for the Streams sampled in 2017 Parameters Ca2+ Mg2+ Na+ K+ Cl- HCO - SO 2- NO - 3 4 3 (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) Count 15 15 15 15 15 15 15 15 Mean 5.28 5.97 10.28 2.26 13.33 31.70 14.68 0.50 Standard Error 1.09 1.57 1.57 0.71 2.86 7.32 6.41 0.10 Median 4.19 2.94 7.70 1.22 10.00 24.38 2.62 0.44 Standard Deviation 4.21 6.06 6.09 2.73 11.07 28.35 24.83 0.38 Sample Variance 17.70 36.75 37.03 7.47 122.59 803.51 616.74 0.15 Kurtosis 0.62 1.42 -0.28 3.90 9.56 7.76 3.15 -0.42 Skewness 1.32 1.52 0.90 2.05 2.89 2.61 1.93 0.45 Minimum 0.95 0.95 2.83 0.30 4.00 9.75 BDL 0.00 Maximum 14.56 19.25 23.23 9.88 49.98 121.92 82.30 1.26 Sum 79.27 89.55 154.26 33.93 199.94 475.48 220.16 7.55 Confidence 2.33 3.36 3.37 1.51 6.13 15.70 13.75 0.21 Level(95.0%) 109 University of Ghana http://ugspace.ug.edu.gh From the above tables (4.4, 4.5, 4.6 and 4.7), the calcium (Ca2+) content in the rivers and streams sampled in 2016 varies from 2.03 to 95.26 mg/L with a mean of 15.76 mg/L, and from 0.74 mg/L to 19.63 mg/L with an average of 5.06 mg/L, respectively. In 2017 the calcium concentrations in the sampled rivers and streams varies from 1.19 to 59.97 mg/L with a mean of 8.68 mg/L, and from 0.95 mg/L to 14.56 mg/L with an average of 5.28 mg/L, respectively. All the calcium content recorded in the sampled rivers and streams for both years are all below WHO (2011) permissible limit of 75 mg/L for drinking water except the Ankobra River which was sampled from the rocks of the Apollonian during the rainy season in 2016. The high calcium content recorded for the Ankobra River indicates that the river might likely be in contact with limestones which exist in the rocks of the Apollonian formation (Fig 3.3 and 3.4). The magnesium (Mg2+) content in the rivers and streams sampled during the rainy season in 2016 varies from 0.42 to 8.08 mg/L with an average of 2.15 mg/L, and from 0.22 to 7.75 mg/L with a mean of 1.89 mg/L, respectively. During the dry season in 2017, the Mg2+ content in the sampled rivers and streams varies from 1.10 to 296.60 mg/L with a mean of 25.07 mg/L, and from 0.95 mg/L to 19.25 mg/L with a mean of 5.97 mg/L, respectively. All the sampled rivers and streams in both years are below WHO (2011) permissible limit of 50 mg/L for drinking water except the Ankobra River, which was sampled from the rocks of the Apollonian during the rainy season in 2016. The reasons accounting for the high calcium content for the Ankobra River as discussed previously is the same reason accounting for the high Mg2+ content in the Ankobra River. The total hardness (TH) concentration in the rivers and streams sampled during the rainy season in 2016 ranges from 8.50 to 240 mg/L with an average of 48.20 mg/L, and from 4.20 mg/L to 80.93 mg/L with a mean of 20.42 mg/L, respectively. In 2017, during the dry season, the sampled rivers and streams range from 7.49 to 1371.14 mg/L with a mean of 124.90 mg/L, and from 6.30 to 115.13 mg/L with a mean of 37.78 mg/L, respectively. All the sampled rivers and streams recorded values below WHO (2011) permissible limit of 500 mg/L for drinking water except the Ankobra River, which exceeded the limit. The high TH value for the Ankobra River 110 University of Ghana http://ugspace.ug.edu.gh sampled from the rocks of the Apollonian formation is possibly due to the elevated calcium and magnesium ion concentrations (Hunslow,1995) recorded for the river. The Sodium (Na+) content in the rivers and streams sampled during the rainy season in 2016 varies from 4.47 to 55.14 mg/L with a mean of 20.18 mg/L, and from 4.30 to 21.29 mg/L with a mean of 10.55 mg/L, respectively. In 2017 during the dry season, the sodium values in the rivers and streams ranges from 4.99 to 380 mg/L with an average of 46.08 mg/L, and from 2.83 to 23.23 mg/L with a mean of 10.28 mg/L respectively. The sodium content in all the sampled rivers and streams in both years are all below the WHO permissible limit of 200 mg/L for drinking water except the Ankobra river, which had sodium content above 200 mg/L. The chloride (Cl-) concentration in the rivers and streams sampled during the rainy season in 2016 varies from 6 to 75.98 mg/L with a mean of 22.88 mg/L, and from 4 to 27.99 mg/L with an average of 12 mg/L, respectively. In 2017 during the dry season, the chloride content in the rivers and streams ranges from 4 to 3298.94 mg/L with an average of 272.06 mg/L, and from 4 to 49.98 mg/L with an average of 13.33 mg/L, respectively. All the sampled rivers and streams for both years are all below the WHO permissible limit of 250 mg/L for drinking water, except the Ankobra river which exceeded the maximum allowable limit of 600 mg/L. The obtained results are like the sodium and chloride results obtained for the Ankobra River by Edjah et al. (2015). The source of the elevated sodium and chloride content in the Ankobra River sampled from the rocks of the Apollonian is unknown but it’s likely that the elevated sodium and chloride content depends on the season and location in which the Ankobra River was sampled . The Ankobra River was sampled at the downstream section which is in Sanwoma in the rocks of the Apollonian formation. The location where the Ankobra River was sampled was 50 m away from the sea. Assuming that the sodium and chloride in the Ankobra River was coming from the sea and that no chemical fractionation ensues between the measured cations, anions, and chloride after sea salt inoculation into the atmosphere. Hence, the proportion of sea salts in the Ankobra River is determined using 111 University of Ghana http://ugspace.ug.edu.gh the ion to chloride ratios in sea water sampled from Sanwoma. The sea water shares boundary with the downstream section of the Ankobra River at Sanwoma. The equation use is given as: 𝑁𝑎+ 𝑁𝑎+ 𝐹𝑖 = { } 𝑠𝑒𝑎𝑤𝑎𝑡𝑒𝑟 × { } 𝑟𝑖𝑣𝑒𝑟 (After Boatta et al. (2014)}. 𝐶𝑙− 𝐶𝑙− Where all units are in milli equivalents per liter and Fi represents marine fraction, Na+ and Cl- represent sodium and chloride content in both seawater and the Ankobra river. In this study the sodium content in the sampled seawater is 18500 mg/L (804.70 meq/L) and that of chloride is 29190.948 mg/L (823.44 meq/L). For the sampled Ankobra river, the sodium concentration is 380 mg/L (16.53 meq/L) and the chloride content is 3298.94 mg/L (93.06 meq/L). Putting the milli equivalent values in the above equation gives 0.17 meq/L as the marine fraction. The 0.17 meq/L represents the proportion of sea salt to the Ankobra river. Also, the Na/Cl molar ratio of the seawater is 0.98 meq/L and that of the Ankobra River is 0.18 meq/L. From the above analysis, it is likely that the elevated sodium and chloride content in the Ankobra River is not from sea water intrusion, but rather be coming from other sources such human activities or ion exchange processes. During sampling, we evidenced citizens from Sanwoma that is a town along the bank where the Ankobra river was sampled dumping their fecal waste into the Ankobra river and some citizens were washing their clothing’s in the river. These human activities might possibly elevate the sodium and chloride content in the Ankobra River. In addition, the Ankobra river is in a deposition environment, as such waste water from illegal small scale miners mining at the upstream section of the river as evidenced on the field might possibly be discharging into the upstream section of the Ankobra river and that might probably flow to the downstream section where the sample was taken. Since Na and Cl was not measured at the upstream section of the Ankobra River further investigation is required. Potassium (K+) concentrations in the rivers and streams sampled in 2016 varies from 0.30 to 22 mg/L with an average of 6.5 mg/L, and from 0.33 to 10.47 mg/L with a mean of 1.51 mg/L, 112 University of Ghana http://ugspace.ug.edu.gh respectively. In 2017 the potassium content in the sampled rivers and streams ranges from 0.19 to 83.06 mg/L with a mean of 10.28 mg/L, and from 0.30 to 9.88 mg/L with a mean of 2.26 mg/L, respectively. The stream and river samples for both years are all below WHO permissible limit of 12 mg/L for drinking water except Tano River, Amanzura River and Ankobra River. These rivers exceeded WHO (2011) permissible limits. The elevated potassium content in these rivers might probably be from domestic discharge (Skowron et al., 2018) which was evidenced during sampling. Another source of elevated K+ content indicates that the rivers might be in contact with silicate minerals (feldspars, biotite, and muscovite) which exist in the underlying geology of the study area (Fig 3.3 and 3.4). Potassium concentration in the same rivers and streams as recorded by Edjah et al. (2015) ranged from 0.8 to 590 mg/L and this compares favorably with the potassium results. The bicarbonate (HCO -3 ) concentration in the rivers and streams sampled during the rainy season in 2016 varies from 9.75 to 82.90 mg/L with an average of 34.14 mg/L, and from 7.32 to 75.59 mg/L with a mean of 29.67 mg/L, respectively. In 2017, during the dry season, the bicarbonate content in the rivers and streams varies from 7.32 to 256.03 mg/L with a mean of 51.38 mg/L, and from 9.75 to 121.92 mg/L with an average of 31.71 mg/L, respectively. The bicarbonate content in all the sampled rivers and streams are below WHO permissible limit of 500 mg/L for drinking water. The sulphate levels in the rivers and streams sampled during the rainy season in 2016 ranges from 17.85 to 248.52 mg/L with an average of 58.70 mg/L, and from 0.001 to 126.56 mg/L with a mean of 30.63 mg/L, respectively. In the dry season in 2017, the sampled rivers and streams, varies from 0.001 to 181.15 mg/L with a mean of 30.18 mg/L, and below detection limit {BDL (<0.001>)} to 82.30 mg/L with an average of 14.68 mg/L, respectively. The entire rivers and streams sampled in 2016 and 2017 are below WHO (2011) permissible limit of 250 mg/L for drinking water. The low sulphate concentrations indicate that sulphide minerals (Pyrites and chalcopyrite) which 113 University of Ghana http://ugspace.ug.edu.gh exist in the underlying geology of the study area have not oxidized or mobilized completely in the surface water. The nitrate (NO -3 ) levels recorded in the rivers and streams sampled during the rainy season in 2016 varies from 0.39 to 26.51 mg/L with a mean of 3.62 mg/L, and from 0.34 to 2.56 mg/L with an average of 1.31 mg/L, respectively. During the dry season in 2017, the nitrate concentrations in the rivers and stream ranges from 0.40 to 1.07 mg/L with an average of 0.62 mg/L, and from 0.001 to 1.26 mg/L with an average of 0.50 mg/L, respectively. The nitrate levels in all the 2016 and 2017 sampled rivers and streams are all below WHO (2011) permissible limit of 50 mg/L for drinking water. Based on the medians (Table 4.4 to 4.7), the cation and anion concentrations in the rivers and streams is in the order: Na+ > Ca2+ > K+ > Mg2+ and SO 2- 4 > HCO - 3 > Cl> NO - 3 (rivers sampled in 2016) Na+ > Ca2+ > Mg2+ > K+ and SO 2- - - -4 > HCO3 > Cl > NO3 (streams sampled in 2016) Na+ > Mg2+ > Ca2+ >K+ and HCO - > Cl- 3 > SO 2- 4 > NO - 3 (rivers sampled in 2017) Na+ > Mg2+ > Ca2+ > K+ > HCO - > Cl- > SO 2- > NO - 3 4 3 (streams sampled in 2017). During the dry season in 2017, both the rivers and streams had similar trend suggesting a hydraulic relationship between the two water bodies. Also, the dominance of sodium among the cations in the rivers and streams implies that the surface water might be in contact with silicate minerals (plagioclase, hornblende, etc.) (Mostafa et al., 2017) which exist in the underlying geology of the study area (fig 3.3 and 3.4). Another source of sodium dominance in the rivers and streams might probably be from the byproduct of rubber and coconut processes (Sultana, 2009) in the study catchment since most of the streams were sampled from the cocoa and rubber plantation zone of the study area and the rivers were sampled along the coast were production of coconut oil is rampant. Another source of Na+ in the rivers and streams is ion exchange processes (Apello and Postma,1999). 114 University of Ghana http://ugspace.ug.edu.gh Evaluation of the dominate sulphate content in the rivers and streams sampled in 2016 during the rainy season is computed from the iron to sulphate (Fe/SO 2-4 ) molar ratio (Stumm & Morgan, 1981) and the result is shown in Appendix 21. The calculated Fe/SO 2- 4 molar ratio for the surface water varies from 0.00 to 63.3. Additionally, two streams located at Nkroful and Aluku in the Birimian Super group rocks had Fe/SO 2 - 4 molar ratios to be 0.5. The value of the molar ratio is the same as the stoichiometry of pyrite (0.5) oxidation (Vaughan & Craig, 1978). This suggests that sulphate dominance in the rivers and streams sampled in 2016 during the rainy season might probably be originating from the oxidation or mobilization of pyrites which exist in the underlying geology of the study area. Iron pyrites was discovered in the Birimian Supergroup rocks by Leube et al. (1990) and Adjimah et al. (1993) and Keese,1985 discovered nodules of pyrites in the rocks of the Apollonian. Likewise, Fe/ SO 2 -4 molar ratio for the rest of the rivers and streams sampled during the rainy season in 2016 was not close to Fe/ SO 2-4 for stoichiometry of pyrite (0.5) and arsenopyrite (1.0) oxidation (Vaughan & Craig, 1978). This suggests that oxidation or mobilization of sulphide minerals do not contribute more to the concentration of sulphate in the surface water sampled during the rainy season in 2016. Additionally, organic substances breakdown from soils into the rivers and streams or human influences (Craig & Andeson, 1979) could probably contribute to the sulphate dominance among the ions in the rivers and streams. In 2017 during the dry season, bicarbonate was the dominant anion in both rivers and streams. The dominance of bicarbonate ion indicates that the surface water might be in contact with carbonate minerals (Gastmans et al., 2010) from the rocks of the Apollonian and silicate minerals (Gastmans et al., 2010) from the rocks of the Birimian supergroup of the study area. The variation in anion and cation results for the surface water sampled in 2016 and 2017 might probably be due to seasonal effects, the times in which the surface water was sampled, the lithology and human activities. 115 University of Ghana http://ugspace.ug.edu.gh 4.2.1.3 Occurrences and Distribution of Trace Elements in surface water (Assessment of surface water contamination) In this section the descriptive statistical results of the laboratory data for the trace element in the sampled rivers and streams is presented in table 4.8,4.9,4.10, and 4.11. 116 University of Ghana http://ugspace.ug.edu.gh Table 4. 8: Descriptive statistical summary of trace elements in the Rivers sampled in 2016. Parameters Al Cr Mn Fe Co Ni Cu Zn As Cd Pb (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) Number of samples 9 9 9 9 9 9 9 9 9 9 9 Mean 0.208 0.003 0.059 3.426 0.0003 0.002 0.006 0.037 0.002 0.002 2.29 Standard Error 0.074 0.001 0.028 1.276 0.0003 0.000 0.004 0.008 0.000 0.001 1.31 Median 0.127 0.003 0.028 2.119 0.0000 0.002 0.001 0.039 0.001 0.000 1.42 Mode N/A N/A 0.000 N/A 0.0000 N/A 0.000 N/A 0.001 0.000 0.00 Standard Deviation 0.222 0.002 0.085 3.828 0.0009 0.001 0.013 0.023 0.001 0.003 3.93 Sample Variance 0.049 0.000 0.007 14.657 0.0000 0.000 0.000 0.001 0.000 0.000 15.41 Kurtosis 1.364 -0.753 6.220 5.733 9.0000 1.367 8.643 -0.838 8.524 3.819 7.08 Skewness 1.399 0.105 2.418 2.261 3.0000 1.049 2.923 0.171 2.879 2.021 2.57 Minimum BDL BDL BDL 0.016 BDL BDL BDL 0.004 0.001 BDL BDL Maximum 0.672 0.005 0.273 12.907 0.0026 0.004 0.042 0.072 0.005 0.010 12.34 Sum 1.875 0.023 0.533 30.836 0.0026 0.014 0.052 0.332 0.014 0.018 20.62 Confidence Level 0.171 0.001 0.065 2.943 0.0007 0.001 0.010 0.018 0.001 0.003 3.02 (95.0%) Table 4. 9: Descriptive statistical summary of trace elements in the Streams sampled in 2016. Parameters Al Cr Mn Fe Co Ni Cu Zn As Cd Pb (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) Number of samples 15 15 15 15 15 15 15 15 15 15 15 Mean 0.382 0.003 0.080 3.933 0.002 0.002 0.001 0.022 0.003 0.002 2.725 Standard Error 0.096 0.001 0.029 1.098 0.001 0.001 0.001 0.005 0.002 0.001 1.087 Median 0.261 0.002 0.032 2.708 0.000 0.001 0.001 0.022 0.000 0.001 0.000 Standard Deviation 0.372 0.002 0.112 4.252 0.006 0.004 0.002 0.018 0.006 0.003 4.210 Sample Variance 0.139 0.000 0.013 18.082 0.000 0.000 0.000 0.000 0.000 0.000 17.724 Kurtosis 2.479 -1.017 4.514 -0.170 10.059 7.092 1.606 5.343 9.271 -0.552 0.610 Skewness 1.492 0.623 2.052 1.022 3.142 2.563 1.503 1.820 2.942 1.048 1.426 Minimum 0.009 BDL BDL 0.008 BDL BDL BDL BDL BDL BDL BDL Maximum 1.380 0.006 0.407 12.947 0.021 0.015 0.007 0.077 0.023 0.009 12.075 Sum 5.730 0.038 1.204 58.991 0.030 0.036 0.022 0.331 0.044 0.036 40.870 Confidence Level (95.0%) 0.206 0.001 0.062 2.355 0.003 0.002 0.001 0.010 0.003 0.002 2.331 117 University of Ghana http://ugspace.ug.edu.gh Table 4. 10: Descriptive statistical summary of trace elements in the Rivers sampled in 2017 Parameters Al Cr Mn Fe Co Ni Cu Zn As Cd Pb (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) Number of samples 14 14 14 14 14 14 14 14 14 14 14 Mean 0.418 0.002129 0.026 0.459 0.0005 0.002 0.006 0.080 0.0038 0.00079 0.00679 Standard Error 0.260 0.000914 0.013 0.239 0.0002 0.001 0.003 0.040 0.0023 0.00040 0.00174 Median 0.014 0.00092 0.002 0.163 0.0001 0.002 0.002 0.025 0.0010 0.00029 0.00519 Standard Deviation 0.973 0.003418 0.047 0.894 0.0007 0.003 0.011 0.148 0.0086 0.00150 0.00652 Sample Variance 0.947 1.17E-05 0.002 0.798 0.0000 0.000 0.000 0.022 0.0001 0.00000 0.00004 Kurtosis 4.036 8.029861 2.819 11.709 1.9430 9.182 7.825 7.435 12.5008 11.18207 2.12523 Skewness 2.317 2.795799 1.860 3.336 1.7057 2.845 2.773 2.729 3.4884 3.25846 1.47690 Minimum 0.0004 0.000248 0.0003 BDL 0.0001 0.001 0.001 0.002 0.0004 0.00004 0.00004 Maximum 2.921 0.01279 0.150 3.457 0.0021 0.011 0.041 0.535 0.0329 0.00579 0.02301 Sum 5.849 0.029809 0.369 6.425 0.0067 0.034 0.088 1.125 0.0534 0.01106 0.09512 Confidence Level 0.562 0.001974 0.027 0.516 0.0004 0.001 0.006 0.086 0.0049 0.00087 0.00377 (95.0%) Table 4. 11: Descriptive statistical summary of trace elements in the Streams sampled in 2017 Parameters Al Cr Mn (mg/L Fe Co Ni Cu Zn As Cd Pb (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) Number of samples 15 15 15 15 15 15 15 15 15 15 15 Mean 0.023 0.001 0.010 0.517 0.0002 0.002 0.002 0.022 0.002 0.0004 0.010 Standard Error 0.008 0.000 0.005 0.245 0.0001 0.000 0.000 0.006 0.000 0.0002 0.002 Median 0.009 0.001 0.001 0.219 0.0001 0.001 0.001 0.007 0.001 0.0001 0.009 Standard Deviation 0.031 0.001 0.019 0.950 0.0002 0.002 0.001 0.025 0.002 0.0009 0.007 Sample Variance 0.001 0.000 0.000 0.903 0.0000 0.000 0.000 0.001 0.000 0.0000 0.000 Kurtosis 0.989 1.571 4.453 12.438 9.6026 1.498 0.228 0.468 7.625 12.7637 0.399 Skewness 1.529 1.438 2.248 3.426 2.9947 1.477 0.957 1.315 2.706 3.5145 0.715 Minimum 0.001 0.0001 0.001 0.001 0.0001 0.001 0.001 0.003 0.0003 0.00004 0.0001 Maximum 0.093 0.002 0.063 3.825 0.0008 0.006 0.004 0.074 0.007 0.0037 0.025 Sum 0.352 0.011 0.147 7.749 0.0025 0.032 0.025 0.337 0.023 0.0061 0.150 Confidence Level (95.0%) 0.017 0.000 0.010 0.526 0.0001 0.001 0.001 0.014 0.001 0.0005 0.004 118 University of Ghana http://ugspace.ug.edu.gh 4.2.1.4 Metallic elements (Cu, Cd, Zn, Fe, and Cr) In this study, the concentration of copper (Cu) in the rivers and streams sampled during the rainy season in 2016 vary from below detection limit (BDL (<0.001>)) to 0.042 m/L with a mean of 0.006 m/L, and from BDL (<0.001>) to 0.007 m/L with a mean of 0.001 m/L, respectively. In 2017 during the dry season, the copper content in the rivers and streams vary from 0.001 to 0.041 mg/L with a mean of 0.006 mg/L, and from 0.001 to 0.004 mg/L with an average of 0.002 mg/L, respectively. The Cu content in all the sampled rivers and streams for both 2016 and 2017 are all below WHO (2011) permissible limit of 0.05 mg/L for drinking water. The cadmium (Cd) content in the rivers and streams sampled in 2016 during the rainy season ranges from below detection limit (BDL) (<0.001>) to 0.010 m/L with a mean of 0.002 mg/L, and from BDL (<0.001>) to 0.009 m/L with a mean of 0.002 mg/L, respectively. That of the dry season rivers and stream samples taken in 2017 ranges from 0.00 to 0.006 mg/L with a mean of 0.001 mg/L, and from 0.00 to 0.004 mg/L with an average of 0.0004 mg/L, respectively. The Cd content in all the sampled rivers and streams for both years are below WHO (2011) permissible limit of 0.003 mg/L for drinking water except Ankasa River, Ebi River, Tano River, Nobaya Stream, Franza Stream, Wowule Stream and a stream located at Ayinase. According to Water Quality Association (www.wqa.org), “Cadmium occurs naturally in zinc, lead, copper ores, coal, other fossil fuels, and shales and it is released during volcanic action. These deposits can serve as sources to surface waters and groundwater especially when in contact with low total dissolved solids (TDS) and acidic waters”. In this study, the pH values for Ankasa River, Ebi River, Tano River, Nobaya Stream, Franza Stream, Wowule Stream and the stream located at Ayinase are acidic to neutral with low TDS concentration, and the geologic formation contains limestones, marl with interclasted sandy beds, cenzoic, shales (Fig 3.3 and 3.4) and sulphide minerals (Luebe et al.,1990). Studies carried out by Gyasi (2017) shows fossils in the rocks of the Apollonian formation. From the above, it can be assumed that the source of cadmium in the above-mentioned rivers and streams is geogenic, but further investigations are required. 119 University of Ghana http://ugspace.ug.edu.gh Another contributing factor leading to the high Cd content in the above-mentioned rivers and streams is possibly from an anthropogenic source such as effluent discharge from the activities of illegal small-scale miners (Schwartz, 2000). In the study area, illegal small-scale mining and mining industries dominate areas surrounding the Ankasa River, Tano River, Nobaya Stream, Franza Stream, and Wowule Stream. Effluents from the activities of these miners might be discharged into the surrounding surface water bodies thereby elevating the Cd contents. The Cd content in the rivers and streams compares favorably to the Cd values in the same rivers and streams obtained by Edjah, 2012. The Zinc (Zn) content in the rivers and streams sampled during the rainy season in 2016 varies from 0.004 to 0.072 mg/L with an average of 0.037 mg/L, and from below detection limit {BDL (<0.001>)} to 0.077 mg /L with a mean of 0.022 mg/L, respectively. In 2017 during the dry season, the zinc concentration in the rivers and streams ranges from 0.002 to 0.535 mg/L with a mean of 0.08 mg/L, and from 0.003 to 0.074 mg/L with a mean of 0.022 mg/L, respectively. The zinc content in all the rivers and streams sampled in both 2016 and 2017 are below WHO (2011) permissible limits of 5 mg/L for drinking water. The iron (Fe) content in the rivers and streams sampled during the rainy season in 2016 vary from 0.016 to 12.91 mg/L with an average of 3.43 mg/L, and from 0.008 to 12.95 mg/L with a mean of 3.93 mg/L, respectively. That of the dry season in 2017 sampled rivers and streams range from below detection limit {BDL (<0.001>)} to 3.46 mg/L with an average of 0.46 mg/L, and from 0.001 to 3.83 mg/L with a mean of 0.52 mg/L, respectively. The Fe content for 11% of the rivers (n=9) and 26 % of the streams (n= 15) sampled in 2016 during the rainy season are below WHO (2011) permissible limit of 0.3 mg/L for drinking water. Similarly, 71.4% (n = 14) of the rivers and 53.3% of the streams (n=15) sampled during the dry season in 2017 are below the WHO (2011) permissible limits of 0.3 mg/L for drinking water. The elevated Fe content for the remaining rivers and streams indicates that silicate minerals (biotite, hornblende, etc.), from the underlying geology of the study catchment (fig 3.3 and 3.4) are dissolving completely in the surface water as it flows. Another source of elevated Fe concentrations in the rivers and streams is possibly from the oxidation of iron pyrites (Luebe 120 University of Ghana http://ugspace.ug.edu.gh et al., 1990; Adjimah et al., 1993) which exist in the rocks of the Apollonian and the Birimian supergroup of the study area. When these rocks are in contact with the surface water, the iron concentration rate is induced due to discharges from the rocks of the Birimian to the rocks of the Apollonian. The Chromium (Cr) content in the 2016 sampled rivers and streams vary from below detection limits {BDL (<0.001>)} to 0.005 mg/L with an average of 0.003 mg/L, and from below detection limit {BDL (<0.001>} to 0.006 mg/L with a mean of 0.003 mg/L, respectively. The rivers and streams sampled in 2017 range from 0.0002 to 0.013 mg/L with an average of 0.002 mg/L, and from 0.0001 to 0.002 mg/L with a mean of 0.001 mg/L respectively. The Cr content in all the sampled rivers and streams are below WHO (2011) permissible limit of 0.05 mg/L for drinking water. 4.2.1.5 Transition metals (Ni, Co, and Mn) The Nickel (Ni) concentration in the rivers and streams sampled during the rainy season in 2016 range from below detection limit {BDL (< 0.001>} to 0.004 mg/L with an average of 0.002 mg/L, and from BDL (<0.001>) to 0.015 mg/L with a mean of 0.002 mg/L, respectively. In 2017 during the dry season, the Ni content in the rivers and streams vary from 0.001 to 0.011 mg/L with an average of 0.002 mg/L, and from 0.001 to 0.006 mg/L with a mean of 0.002 mg/L, respectively. Nickel (Ni), concentration in the surface water sampled in both 2016 and 2017 are below WHO permissible limit of 0.006 mg/L for drinking water except Tano River and Assufofa Stream. Even though illegal small-scale mining activity was evidenced on these two water bodies, the elevated Ni content indicates that the Tano River and Assufofa stream might possibly be in contact with sulphide minerals (pyrites, chalcopyrite) from the rocks of the Birimian and the Apollonian formation. When the surface water is in contact with the sulphide minerals, the sulphide minerals oxidize or mobilize releasing Ni as a secondary mineral. Ni was one of the trace elements hosted in sulphide minerals (pyrites, arsenopyrites, chalcopyrite) discovered by Luebe et al., 1990 and Adijimah et al., 1993 in the rocks of the Birimian. 121 University of Ghana http://ugspace.ug.edu.gh The Cobalt (Co) content in the rivers and streams sampled during the rainy season in 2016 range from BDL (<0.001>) to 0.003 mg/L with a mean of 0.0003 mg/L and from BDL (<0.001>) to 0.021 mg/L with an average of 0.002 mg/L, respectively. In 2017 during the dry season, the Co concentration in the rivers and streams range from 0.0001 mg/L to 0.002 mg/L with an average 0.0005 mg/L, and from 0.0001 to 0.0008 mg/L with a mean of 0.0002 mg/L, respectively. The Co concentration in all the sampled surface water is below WHO (2011) permissible limit of 0.05 mg/L for drinking water. The Magnesium (Mn) content in the rivers and streams sampled during the rainy season in 2016 vary from BDL (<0.001>) to 0.27 mg/L with a mean of 0.059 mg/L, and from BDL (<0.001>) to 0.41 mg/L with an average of 0.08 mg/L, respectively. In 2017 during the dry season, the Mn content in the rivers vary from 0.0003 to 0.150 mg/L with a mean of 0.026 mg/L. That of the streams range from 0.001 to 0.063 mg/L with a mean of 0.010 mg/L. The Mn content in the surface water sampled in both 2016 and 2017 are all below the WHO permissible limit of 0.4 mg/L for drinking water. 4.2.1.6 Toxic Elements (Pb and As) The Lead (Pb) content in the rivers and streams sampled in 2016 during the rainy season vary from BDL (<0.001>) to 12.34 mg/L with a mean of 2.29 mg/L, and from BDL (<0.001>) to 12.08 mg/L with an average of 2.73 mg/L, respectively. The concentration of lead (Pb) in 5 rivers (n=10) and 8 streams (n=15) are below the WHO (2011) permissible limit of 0.01 mg/L and the remaining 5 rivers and 7 streams are above the permissible limits for drinking water. In 2017 during the dry season, the Pb content in the rivers and streams range from 0.00004 \to 0.023 mg/L with a mean of 0.007 mg/L, and from 0.0001 to 0.025 mg/L with a mean of 0.010 mg/L, respectively. The Pb content in all the sampled surface water are below WHO (2011) permissible limit of 0.01 mg/L for drinking water except for Amanzura river, Subly stream, Kodubaku stream and Nsugene stream which exceeded the permissible limit (Fig 4.9). Goel, 1997 stated that “lead (Pb) concentrations in natural water mainly generates from anthropogenic sources”. Looking at the activities (small- scall mining, fecal waste disposal, household waste disposal) surrounding the above-mentioned river and streams as evidenced on 122 University of Ghana http://ugspace.ug.edu.gh the field, it can be said that the elevated lead content measured in these rivers and streams might likely be coming from an anthropogenic source. Subly, Kodubaku and Nsugene streams are close to Adamus’s mining resources and there are rampant illegal small-scale mining activities at the upstream section of these streams. As such, wastewater from drains and effluent from the use of lead gasoline by these miners might possibly discharge into these streams through natural processes. like rainfall or runoffs. An extra source of elevated Pb in the river and streams might be geogenic due to the oxidation or mobilization of sulphide minerals (pyrite, chalcopyrite.) from the underlying geology to liberate Pb as a secondary mineral in the river and streams. These sulphide minerals hosted trace element like Pb which was used as a guide element for gold discovery in the rocks of Birimian {Adjimah et al. (1993)}. Figure 4. 9: Enhanced Pb levels in the rivers and streams sampled in both 2016 and 2017. The Arsenic (As) content in the rivers and streams sampled during the rainy season in 2016 varies from 0.001 to 0.005 mg/L with an average of 0.002 mg/L, and from BDL (<0.001>) to 0.023 mg/L with an average of 0.003 mg/L, respectively. In 2017 during the dry season, the 123 University of Ghana http://ugspace.ug.edu.gh sampled rivers and streams varies from 0.0004 to 0.033 mg/L with an average of 0.004 mg/L, and from 0.0003 to 0.007 mg/L with an average of 0.002 mg/L, respectively. The Arsenic concentration in the surface water sampled in 2016 and 2017 are all below the WHO (2011) permissible limit of 0.01 mg/L for drinking water apart from Ankobra River sampled from the rocks of the Apollonian formation and Franza Stream sampled from the rocks of the Birimian Supergroup. Edjah (2012) recorded enhanced levels of As in these two water bodies. The Birimian supergroup rocks of the study area contains sulphide minerals (Luebe et al., 1990). These sulphide minerals when they oxidize or mobilizes As is released. 4.2.1.7 Non-metallic elements (Al) The Aluminum (Al) content in the rivers sampled in 2016 during the rainy season varies from BDL (<0.001>) to 0.67 mg/L with a mean of 0.208 mg/L. That of the streams sampled in 2016 during the rainy season varies from 0.009 to 1.380 mg/L with an average of 0.382 mg/L. In 2017, during the dry season, the sampled rivers, and streams ranges from 0.0004 to 2.92 mg/L with a mean of 0.42 mg/L, and from 0.001 to 0.093 mg/L with an average of 0.023 mg/L. The Aluminum (Al) content in the sampled rivers for both 2016 and 2017 are below WHO (2011) permissible limit of 0.2 mg/L for drinking water except Ebi River, Fian River and Tano River. The Al content in 8 streams (n=15) sampled in 2016 are above WHO (2011) permissible limit of 0.2 mg/L and the remaining 7 streams are lower than the permissible limit. In 2017, the Al concentration in all the sampled streams is below WHO (2011) permissible limit of 0.2 mg/L for drinking water. The source of elevated Al content in few of the rivers and streams is geogenic. Its geogenic because the underlying geology contains silicate minerals (hornblende, muscovite, biotite etc.) {(www.healthycanadians.gc.ca; (Fig 3.3 and 3.4)}and when these silicate minerals dissolves, Al is probably released due to the acidity (pH = 4.0 to 6.4) of the above-mentioned elevated rivers and streams. Comparing the median concentrations of the measured trace elements in the rivers and streams sampled in 2016 and 2017, it is seen that iron (Fe) dominated among all the measured trace elements. This is due to the underlying geology containing silicate minerals and sulphide minerals. Most of the streams were sampled in areas underlain by the Birimian super group 124 University of Ghana http://ugspace.ug.edu.gh rocks and most rivers were taken in areas underlain by the rocks of the Apollonian. These surface water bodies flow from the hinterlands (Birimian super group rocks) to the coast (rocks of the Apollonian formation) and the areas underlain by the rocks of the Apollonian are more in a deposition environment (fig 3.3 and 3.4) than the areas underlain by the rocks of the Birimian Super group. The dominance of Fe among the measured trace elements in the rivers and streams in both 2016 and 2017 is like the results obtained by Edjah ,2012. 4.2.1.8. Existing Relationship between the cations, anions, and trace element in the surface water In this study, the relationship existing between the cations, anions and trace elements in the rivers and streams are investigated using Pearson correlation matrix and the results are shown in table 4.12,4.13.4.14 and 4.15. The elements that correlates are highlighted in red. 125 University of Ghana http://ugspace.ug.edu.gh Table 4. 12: Pearson correlation of chemical and trace elements data for the Rivers sampled in 2016. Ca2+ Mg2+ Na+ K+ Cl- HCO - SO 2- NO - 3 4 3 TDS EC pH TH Al Cr Mn Fe Co Ni Cu Zn As Cd Pb Ca2+ 1.0 Mg2+ -0.2 1.0 Na+ 0.5 0.6 1.0 K+ 0.4 0.1 0.7 1.0 Cl- 0.1 0.9 0.7 0.2 1.0 HCO - 3 0.8 0.1 0.7 0.7 0.4 1.0 SO 2- 4 1.0 -0.1 0.6 0.4 0.2 0.8 1.0 NO - 3 -0.2 0.0 -0.2 -0.3 0.01 0.01 0.01 1.0 TDS 0.1 0.9 0.9 0.4 1.0 0.4 0.2 0.01 1.0 EC 0.1 0.9 0.9 0.4 1.0 0.4 0.2 0.01 1.0 1.0 pH 0.6 -0.3 0.3 0.4 -0.3 0.4 0.5 -0.6 -0.2 -0.2 1.0 TH 1.0 -0.1 0.6 0.4 0.2 0.8 1.0 -0.2 0.2 0.2 0.6 1.0 Al -0.4 -0.1 -0.5 -0.6 -0.3 -0.3 -0.4 0.4 -0.4 -0.4 -0.2 -0.4 1.0 Cr -0.6 -0.2 -0.4 0.1 -0.6 -0.5 -0.6 0.01 -0.4 -0.4 0.01 -0.7 0.2 1.0 Mn -0.3 0.2 -0.2 -0.4 -0.2 -0.5 -0.2 0.2 -0.2 -0.2 -0.1 -0.3 0.2 0.4 1.0 Fe -0.2 0.1 -0.2 -0.4 -0.2 -0.5 -0.1 0.1 -0.2 -0.2 -0.1 -0.2 0.2 0.2 1.0 1.0 Co -0.2 0.0 -0.2 -0.3 0.01 0.01 0.01 1.0 -0.1 -0.1 -0.6 -0.2 0.4 0.01 0.2 0.1 1.0 Ni 0.8 -0.6 0.1 0.5 -0.3 0.6 0.7 0.1 -0.3 -0.3 0.4 0.7 -0.4 -0.2 -0.3 -0.2 0.1 1.0 Cu -0.2 0.0 -0.2 -0.3 0.01 0.01 -0.1 1.0 -0.1 -0.1 -0.6 -0.2 0.4 0.1 0.2 0.2 1.0 0.1 1.0 Zn -0.4 0.3 -0.3 -0.6 0.3 -0.4 -0.3 0.5 0.1 0.1 -0.8 -0.3 0.3 -0.3 0.3 0.4 0.5 -0.4 0.5 1.0 As -0.1 0.2 -0.1 -0.1 -0.2 -0.4 -0.1 -0.1 -0.1 -0.1 0.1 -0.1 -0.1 0.4 0.9 0.9 -0.1 -0.2 0.01 0.1 1.0 Cd -0.3 -0.3 -0.5 -0.3 -0.3 -0.1 -0.3 0.3 -0.3 -0.3 -0.2 -0.3 0.01 0.1 -0.1 -0.2 0.3 -0.1 0.3 0.1 -0.2 1.0 Pb -0.3 0.01 -0.2 -0.2 -0.4 -0.5 -0.2 -0.2 -0.3 -0.3 0.2 -0.3 0.01 0.6 0.9 0.8 -0.2 -0.3 -0.1 0.01 0.9 -0.1 1.0 126 University of Ghana http://ugspace.ug.edu.gh Table 4. 13: Pearson correlation of chemical and trace elements data for the Streams sampled in 2016. Ca2+ Mg2+ Na+ K+ Cl- HCO - 3 SO 2- 4 NO - 3 TDS EC pH TH Al Cr Mn Fe Co Ni Cu Zn As Cd Pb Ca2+ 1.0 Mg2+ 0.7 1.0 Na+ -0.1 0.1 1.0 K+ 0.1 0.1 0.6 1.0 Cl- -0.1 0.01 0.4 0.3 1.0 HCO - 3 0.3 0.5 0.1 0.3 0.4 1.0 SO 2- 4 0.7 0.8 0.01 0.01 0.1 0.5 1.0 NO - 3 0.2 0.6 0.01 0.1 -0.1 0.3 0.6 1.0 TDS 0.4 0.6 0.2 0.1 0.6 0.8 0.6 0.2 1.0 EC 0.4 0.6 0.2 0.1 0.6 0.8 0.6 0.2 1.0 1.0 pH -0.4 -0.5 -0.1 -0.3 -0.1 -0.2 -0.4 -0.4 -0.4 -0.4 1.0 TH 1.0 0.8 0.01 0.1 -0.1 0.4 0.8 0.4 0.5 0.5 -0.5 1.0 Al -0.3 -0.3 -0.4 -0.2 -0.3 -0.4 -0.4 0.2 -0.5 -0.5 0.2 -0.4 1.0 Cr -0.4 -0.4 0.3 0.4 0.2 0.2 -0.6 -0.2 -0.1 -0.1 0.2 -0.4 0.3 1.0 Mn -0.4 -0.4 0.0 -0.1 -0.2 0.1 -0.3 -0.1 -0.3 -0.3 0.6 -0.4 0.1 0.3 1.0 Fe -0.4 -0.5 -0.3 -0.3 -0.1 0.01 -0.2 -0.1 -0.4 -0.4 0.7 -0.5 0.2 0.1 0.8 1.0 Co -0.1 -0.1 0.2 0.01 -0.1 -0.1 0.01 0.01 0.01 0.01 -0.1 -0.1 0.01 -0.1 0.1 0.0 1.0 Ni -0.2 -0.2 -0.3 -0.2 -0.3 0.01 -0.2 -0.1 -0.3 -0.3 0.4 -0.3 0.01 0.01 0.4 0.7 -0.1 1.0 Cu 0.01 0.1 0.3 0.0 -0.3 0.2 -0.2 0.1 0.01 0.01 0.2 0.01 0.2 0.4 0.5 0.1 0.1 -0.1 1.0 Zn -0.2 -0.1 -0.3 -0.3 -0.1 0.2 0.01 0.2 -0.2 -0.2 0.4 -0.2 0.01 0.01 0.5 0.8 -0.3 0.8 0.1 1.0 As -0.2 -0.3 -0.3 -0.1 -0.3 -0.1 -0.4 0.1 -0.4 -0.4 -0.1 -0.3 0.4 0.5 0.3 0.2 0.01 0.3 0.3 0.1 1.0 Cd 0.1 -0.3 -0.4 -0.2 0.01 0.1 -0.5 -0.4 0.01 0.01 0.1 -0.1 0.4 0.5 -0.1 0.01 -0.2 0.2 0.2 0.1 0.5 1.0 Pb -0.3 -0.2 0.3 0.01 -0.2 -0.1 -0.6 -0.1 -0.2 -0.2 0.4 -0.3 0.5 0.6 0.4 0.1 0.1 -0.1 0.9 0.01 0.3 0.3 1.0 127 University of Ghana http://ugspace.ug.edu.gh Table 4. 14: Pearson correlation of chemical and trace elements data for the Rivers sampled in 2017. Ca2+ Mg2+ Na+ K+ Cl- HCO - 2- - 3 SO4 NO3 TDS EC pH TH Al Cr Mn Fe Co Ni Cu Zn As Cd pb Ca2+ 1.0 Mg2+ 1.0 1.0 Na+ 1.0 1.0 1.0 K+ 1.0 1.0 1.0 1.0 Cl- 1.0 1.0 1.0 1.0 1.0 HCO - 3 0.2 0.1 0.3 0.4 0.1 1.0 SO 2- 4 0.8 0.7 0.7 0.7 0.8 0.01 1.0 NO - 3 -0.1 -0.2 -0.3 -0.3 -0.2 -0.1 0.3 1.0 TDS 1.0 1.0 1.0 1.0 1.0 0.2 0.8 -0.2 1.0 EC 1.0 1.0 1.0 1.0 1.0 0.2 0.8 -0.2 1.0 1.0 pH 0.2 0.3 0.3 0.2 0.3 -0.2 0.1 -0.7 0.3 0.3 1.0 TH 1.0 1.0 1.0 1.0 1.0 0.1 0.8 -0.2 1.0 1.0 0.3 1.0 Al 0.7 0.6 0.6 0.5 0.6 0.01 0.7 0.3 0.6 0.6 -0.2 0.6 1.0 Cr 0.01 0.01 0.01 -0.1 0.0 -0.1 -0.1 -0.1 0.01 0.01 0.1 0.01 0.3 1.0 Mn 0.5 0.4 0.4 0.4 0.4 -0.1 0.7 0.2 0.4 0.4 0.3 0.4 0.5 0.01 1.0 Fe 0.01 -0.1 -0.1 -0.2 -0.1 -0.1 0.1 0.6 -0.1 -0.2 -0.4 -0.1 0.7 0.4 0.2 1.0 Co 0.8 0.7 0.7 0.6 0.7 0.01 0.7 0.1 0.7 0.7 0.1 0.7 0.9 0.4 0.7 0.5 1.0 Ni 0.3 0.1 0.1 0.1 0.1 -0.1 0.3 0.5 0.1 0.1 -0.3 0.1 0.8 0.5 0.4 0.9 0.7 1.0 Cu 0.01 -0.1 -0.1 -0.1 -0.1 -0.2 -0.1 0.01 -0.1 -0.1 0.1 -0.1 0.2 1.0 0.1 0.4 0.4 0.5 1.0 Zn 0.1 0.01 -0.1 -0.1 -0.1 -0.2 0.1 0.4 -0.1 -0.1 -0.3 0.01 0.7 0.7 0.2 0.9 0.6 0.9 0.7 1.0 As -0.1 -0.1 -0.1 -0.1 -0.1 -0.2 -0.2 -0.1 -0.1 -0.1 0.2 -0.1 0.01 1.0 -0.1 0.1 0.2 0.3 1.0 0.5 1.0 Cd 0.1 0.01 -0.1 -0.1 -0.1 -0.1 0.2 0.6 -0.1 -0.1 -0.4 0.01 0.7 0.3 0.5 1.0 0.6 0.9 0.3 0.8 0.1 1.0 pb 0.01 -0.1 -0.2 -0.2 -0.1 -0.3 0.1 0.6 -0.1 -0.2 -0.3 -0.1 0.5 0.01 0.4 0.7 0.4 0.6 0.1 0.5 -0.1 0.7 1.0 128 University of Ghana http://ugspace.ug.edu.gh Table 4. 15: Pearson correlation of chemical and trace elements data for the Streams sampled in 2017 Ca2+ Mg2+ Na+ K+ Cl- HCO - SO 2- NO - 3 4 3 TDS EC pH TH Al Cr Mn Fe Co Ni Cu Zn As Cd Pb Ca2+ 1.0 Mg2+ 0.9 1.0 Na+ 0.7 0.5 1.0 K+ 0.5 0.2 0.6 1.0 Cl- 0.01 -0.1 -0.1 0.2 1.0 HCO - 3 0.4 0.3 0.7 0.8 0.1 1.0 SO 2- 4 0.7 0.9 0.3 0.1 -0.1 0.2 1.0 NO - 3 0.4 0.2 0.01 0.4 0.5 0.3 0.4 1.0 TDS 0.8 0.7 0.7 0.8 0.1 0.8 0.6 0.6 1.0 EC 0.9 0.8 0.7 0.7 0.0 0.7 0.7 0.5 1.0 1.0 pH 0.5 0.6 0.4 0.2 -0.3 0.3 0.4 -0.4 0.3 0.4 1.0 TH 1.0 1.0 0.6 0.3 -0.1 0.3 0.8 0.3 0.7 0.8 0.6 1.0 Al -0.1 -0.2 0.2 0.3 0.4 0.5 0.1 0.3 0.3 0.2 -0.1 -0.1 1.0 Cr 0.1 0.01 0.4 0.3 0.7 0.4 -0.1 0.5 0.4 0.2 -0.4 0.01 0.5 1.0 Mn -0.1 -0.3 0.01 0.3 0.8 0.3 -0.2 0.4 0.2 0.1 -0.4 -0.2 0.6 0.7 1.0 Fe 0.01 0.01 -0.2 0.01 0.9 -0.1 0.01 0.6 0.1 0.01 -0.4 0.01 0.4 0.7 0.7 1.0 Co 0.01 -0.1 -0.1 -0.1 0.9 0.0 0.01 0.3 0.1 0.01 -0.4 -0.1 0.3 0.7 0.9 0.9 1.0 Ni 0.4 0.6 0.3 0.01 0.0 0.3 0.4 0.01 0.3 0.4 0.4 0.5 0.1 0.2 0.01 0.1 0.1 1.0 Cu 0.01 -0.1 0.4 0.2 0.6 0.4 -0.1 0.3 0.2 0.1 -0.1 -0.1 0.5 0.9 0.7 0.6 0.7 0.3 1.0 Zn 0.2 0.1 0.4 0.5 0.6 0.6 0.2 0.6 0.5 0.4 -0.2 0.1 0.6 0.9 0.8 0.5 0.7 0.3 0.8 1.0 As 0.8 0.9 0.4 0.2 -0.1 0.2 0.9 0.4 0.7 0.8 0.3 0.9 -0.2 0.01 -0.2 0.01 0.01 0.3 -0.1 0.2 1.0 Cd 0.1 -0.1 0.4 0.7 0.3 0.9 -0.1 0.4 0.6 0.4 0.01 -0.1 0.7 0.5 0.6 0.1 0.2 0.1 0.5 0.7 -0.1 1.0 Pb 0.5 0.3 0.01 0.4 0.1 0.01 0.3 0.3 0.5 0.5 0.1 0.4 -0.1 -0.2 0.1 0.1 0.01 -0.3 -0.3 -0.1 0.4 0.01 1.0 129 University of Ghana http://ugspace.ug.edu.gh The use of Pearson correlation matrix can help understand the distribution of anions, cations, and trace elements in the sampled surface water. It is also one of the essential tests that identify the relationship between two independent variables in water samples and shows how one parameter guesses the other variable (Howlader et al., 2014). The correlation coefficient (r) varies from − 1 to + 1. When r is close to − 1, the relationship is delineated as a negative slope or anti-correlated. The linkage is considered to have a positive slope or correlation when r is close to + 1. If the value of r inclines to be zero, the points are considered uncorrelated (Srivastava & Ramanathan, 2008; Howlader et al., 2014). From Table 4.13,4.14 and 4.15, it is seen that Mg2+ correlated strongly with Ca2+ for the streams sampled during the rainy season in 2016 and the rivers and streams sampled during the dry season in 2017. The perfect relationship between Mg2+ and Ca2+ for the streams and rivers suggests that the rivers and streams are likely in contact with limestones and granitic rocks from the underlying geology (fig 3.3 and 3.4). Also, there was a strong correlation between Na+ and (Ca2+ and Mg2+) for the rivers sampled during the rainy season in 2016 (Table 4.12) and the dry season in 2017 (Table 4.14) as well as the streams sampled during the dry season in 2017 (Table 4.15). The above relationship suggests that the rivers and streams are possibly in contact with silicate minerals (feldspars, hornblende etc.) from the underlying geology (fig 33 and 3.4) of the study area. Also, the good relationship between Na+ and (Ca2+ and Mg2+) reveals cation- exchange processes (Guo & Wang, 2004) among the rivers and streams. From table 4.12 and 4.13 it is observed that K+ correlated strongly with Na+ for the rivers and streams sampled during the dry rainy season in 2016. In addition, K+ correlated perfectly with (Ca2+, Mg2+ and Na+) for the rivers (Table 4.14) sampled during the dry season in 2017 and K+ correlated strongly with (Ca2+, Na+) for the streams sampled during the dry season in 2017 (Table 4.15). The relationship between K+ and (Ca2+, Mg2+ and Na+) for the rivers and streams suggests that the rivers and streams might be in contact with silicate minerals (feldspars, hornblende, plagioclase etc.) (Drever, 1988) from the underlying geology (Fig 3.3 and 3.4). 130 University of Ghana http://ugspace.ug.edu.gh Cl- correlated perfectly with (Mg2+ and Na+) for the rivers sampled in 2016 (Table 4.12) and Cl- correlated strongly with (Ca2+, Mg2+, Na+ and K+) for the rivers sampled in 2017 (Table 4.14). The above relationships suggest an anthropogenic source. In the study area, peasant farming and coconut farming is common and the application of excessive fertilizer by theses farmers might possibly lead to MgCl2, CaCl2, NaCl, and KCl concentrations (Sriniyasamoorty et al., 2008) in the soil which requires further investigations. HCO - 2+ + +3 correlated perfectly with (Ca , Na and K ) for the rivers sampled in 2016 (Table 4.12) and correlated strongly with Mg2+ for the streams sampled in 2016 (Table 4.13). In addition, there was a perfect correlation between HCO - and (Na+3 and K +) for the streams sampled in 2017 (Table 4.15). The relationship existing between HCO -3 and (Ca 2+ and Mg2+) for the rivers and streams suggests that the alkalinity of the surface water might possibly has a direct bearing on the composition of limestones and granites from the underlying geology of the Lower Tano River basin. The good relationship between HCO3 and (Na + and K+) for the rivers and streams indicate a possible occurrence of ion exchange processes. Additionally, the good connection indicates that the alkalinity of the rivers and streams probably has a direct bearing on the composition of silicate minerals from the underlying geology of the study area. Further, there was a perfect relationship between SO 2-4 and (Ca 2+, Na+ and HCO -3 ) for the rivers sampled in 2016 (Table 4.12) and (Ca2+, Mg2+ and HCO -3 ) for the streams sampled in 2016 (Table 4.13). For 2017 samples, SO 2-4 correlated perfectly with (Ca 2+, Mg2+, Na+, K+ and Cl-) for the rivers (Table 4.14) and (Ca2+ and Mg2+) for the streams (Table 4.15). The good relationship between SO 2-4 and (Ca 2+ and Mg2+) for the surface water suggests the possible occurrence of ion exchange processes (Mariotti, 1994). The good relationship between SO 2-4 and (Na+ and K+) for the rivers and streams suggest a possible anthropogenic source {Sophocleous et al. (2002)} and the probable source could be linked to untreated sewage disposal which was evidenced during sampling. Also, the good relationship between SO 2-4 and Mg2+ for the rivers and streams suggests a possible occurrence of ion exchange processes or the existence of magnesium calcareous materials in the study catchment which needs further 131 University of Ghana http://ugspace.ug.edu.gh investigations. Additionally, the relationship between SO 2-4 and HCO - 3 for the rivers and streams suggests that anthropogenic or geogenic sources probable affects the alkalinity of the rivers and streams or a possible occurrence of reverse ion- exchange processes. NO -3 correlated strongly with (Mg 2+ and SO 2-4 ) for the streams sampled in 2016 (Table 4.13) and correlated perfectly with Cl- for the streams sampled in 2017 (Table 4.15). The relationship between NO -3 and Cl - for the streams is probably linked to reverse ion exchange processes or anthropogenic sources. Also, human activities such as fertilizer application and sewage disposal could be the possible reason accounting for the good relationship between NO -3 and (Mg2+ and SO 2-4 ) for the streams. The streams were mostly located in the forested zone of the study area where cocoa farming and rubber plantation is practiced. In 2016, TDS and EC correlated perfectly with (Mg2+, Na+, and Cl-) for the rivers (Table 4.12) and (Mg2+, Cl-, HCO -3 and SO 2- 4 ) for the streams (Table 4.13). Also in 2017, TDS and EC correlated perfectly with (Ca2+, Mg2+, Na+, K+, Cl- and SO 2-4 ) for the rivers (Table 4.14) and correlated strongly with (Ca2+, Mg2+, Na+, K+, SO 2-4 , NO - 3 and HCO - 3 ) for the streams (Table 4.15). The existing relationship between TDS /EC and the above-mentioned ions in both rivers and streams suggest the likelihood of the ions being involved in physiochemical reactions and one such reactions is ion exchange processes and oxidation – reduction processes (Subba Rao, 2002). For the rivers sampled in 2016, pH correlated strongly with (Ca2+ and SO 2-4 ) and negatively with NO - 3 (Table 4.12). Also, pH correlated negatively with Mg 2+ for the streams sampled in 2016 (Table 4.13). In 2017, pH correlated negatively with NO - 3 for the rivers (Table 4.14) and strongly with (Ca2+ and Mg2+) for the streams (Table 4.15). The good relationship between pH and Ca2+ for the rivers and Ca2+ and Mg2+ for the streams indicates carbonate mineral dissolution and weathering of silicate minerals from the underlying geology of the study area. The relationship between pH and SO 2-4 for the rivers specifies the oxidation of sulphide minerals (pyrites, chalcopyrite) (Hunslow, 1995) from the underlying geology. The negative 132 University of Ghana http://ugspace.ug.edu.gh relationship between pH and NO -3 for the rivers suggests the likely absence of fertilizer application in the study area. In addition, the negative relationship between pH and Mg2+ for the streams suggests the acidity of the streams does not influence the weathering of ferromagnesium mineral (Biotite) from the underlying geology. In 2016, TH in the sampled rivers correlated perfectly with (Ca2+, Na+, HCO -, SO 2-3 4 and pH) (Table 4.12). Also, TH correlated strongly with (Ca2+, Mg2+, SO 2-4 , EC, TDS) and negatively correlated with pH for the streams sampled in 2016 (Table 4.13). In 2017, there was a perfect correlation between TH and (Ca2+, Mg2+, Na+, K+, Cl-, SO 2-4 , EC and TDS) for the rivers (Table 4.14) and TH correlated strongly with (Ca2+, Mg2+, Na+, SO 2-4 , EC, TDS, and pH) for the streams (Table 4.15). The relationship between TH and (Ca2+ and Mg2+) for the rivers and streams reveals calcium and magnesium ion concentration in the rivers and streams. Also, the relationship between TH and (EC and TDS) for the rivers and streams suggests a possible modification of surface water chemistry and the amount of dissolved calcium and magnesium probably contributes to the components of EC and TDS in the surface water of the study area. The relationship between TH and HCO -3 for the rivers suggest the possibility of carbonate hardness (Drever, 1988) due to dissolution of limestones from the underlying geology. The connection between TH and (Na+, K+) for the rivers and TH and K+ for the streams indicates the presence of silicate hardness or the possibility of cation-exchange (Drever, 1988). The link between TH and SO 2-4 for the rivers and streams suggests sulphide hardness.The good relationship between TH and pH for the rivers and streams sampled in 2016 and 2017, respectively suggests a probable geochemical reaction. In 2016, the Al content for the rivers and streams correlated negatively with (Na+ and K+) and (TDS and EC), respectively (Table 4.12 and 4.13). In addition, the Al concentration for the rivers and streams sampled in 2017 (Table 4.14 and 4.15) correlated strongly with (Ca2+, Mg2+, Na+, K+, Cl-, SO 2-4 , TDS, EC, and TH) and HCO - 3 , respectively. The negative relationship between Al and (Na+ and K+) indicates that the presence of sodium and potassium in the rivers and streams does not influence the Al concentrations. Also, the negative linkage between Al 133 University of Ghana http://ugspace.ug.edu.gh and (TDS and EC) suggests that Al is probably not involved in the physiochemical reactions of the streams. The good relationship between Al and (Ca2+, Mg2+, Na+, and K+ ) for the rivers sampled in 2017 suggests the weathering of silicate minerals (feldspar, hornblende, plagioclase etc.) from the underlying geology and granitic rocks (Fig 3.3 and 3.4). The good linkage between Al and TH is from a geogenic source. Additionally, the good connection between Al and Cl- for the rivers sampled in 2017 is likely from an anthropogenic source, but studies have shown that biotite which is present in the underlying geology (Fig 3.3 and Fig 3.4) releases chloride {Henry & Diagle. (2018)}. The good relationship between Al and SO 2-4 for the rivers is possibly geogenic due to the oxidation or mobilization of sulphide minerals (pyrites, chalcopyrite etc.) (Luebe et al., 1990) and weathering of silicate minerals (plagioclase, feldspar, hornblende etc.) from the underlying geology of the study area. The good relationship between Al and (TDS and EC) suggests the Al being one of the major constituents of EC and TDS in the rivers sampled in 2017. Further, the good relationship between Al and HCO -3 suggest the weathering of silicate minerals (feldspar, hornblende, plagioclase etc.) and granitic rock from the underlying geology (Fig 3.3 and 3.4). For the rivers sampled in 2016, Cr correlated negatively with (Ca2+, HCO -3 , SO 2- 4 ,TH). In 2017, Cr in the streams correlated strongly with (Cl-, NO -3 and Al). The good relationship between Cr and Cl- indicates that the streams might be in contact with ultra-mafic rocks from the underlying geology. These rocks when it weathers, it releases Cr which might interacts with Cl- in the rivers and streams which have been rain fed. Dampare et al. (2008) recorded high concentration of Cr in ultra-mafic rock of the Birimian Supergroup rocks of south western Ghana and the Lower Tano River Basin records high rainfall amount (WRC,2012). The good relationship between Cr and NO -3 is from an anthropogenic source or possibly the occurrence of rock- water interaction which requires further investigations. The good relationship between Cr and Al suggests a possible weathering of ultra-mafic rocks and silicate minerals from the underlying geology. 134 University of Ghana http://ugspace.ug.edu.gh Further in 2016, Mn negatively correlated with HCO -3 for the rivers (Table 4.12). This suggests the possible non- weathering of ferromagnesian minerals like biotite from the underlying geology. Also in 2016, Mn correlated strongly with pH for the streams (Table 4.13) and this suggest a possible weathering of banded manganese or ferromagnesian minerals from the underlying geology of the study area. In 2017, Mn correlated strongly with (Ca2+ and Al) for the rivers (Table 4.14) suggesting a possible weathering of monzonite rocks or silicate minerals (hornblende, plagioclase etc.) from the underlying geology. Also, there was a strong relationship between Mn and SO 2–4 for the rivers (Table 4.14). Since low values of Mn and SO 2-4 in the rivers was recorded in the chemical and trace element analysis, the good correlation could be coming from an anthropogenic source which requires further investigation. Also, in 2017 Mn correlated strongly with (Cl-, Al, Cr) for the streams (Table 4.15). The good relationship between Mn and Al suggests a possible weathering of Monzonite rocks from the underlying geology. Additionally, the good relationship between Mn and Cl- might possibly be from anthropogenic sources or rock-water interaction but further investigation is required. In addition, the good linkage between Mn and Cr is from the weathering of ferromagnesium minerals and ultra-mafic rocks of the underlying geology of the study area. A highly negative correlation exists between Fe and HCO -3 for the rivers sampled in 2016 (Table 4.12). This indicates the absence of Fe geochemical processes in the rivers. The perfect relationship between Fe and Mn for the rivers and streams sampled in 2016 (table 4.12 and 4.13) suggests that weathering of Monzonite rocks or ferromagnesium mineral like biotite from the underlying geology (Fig 3.3 and Fig 3.4). A good relationship between Fe and pH for the streams sampled in 2016 (Table 4.13) suggests a possible geochemical processes or weathering of silicate minerals and sulphide minerals {pyrite (FeS2) and chalco- pyrite (CuFeS2)} oxidation from the underlying geology The strong correlation between Fe and TH for the streams sampled in 2016 (Table 4.13) suggest Fe hardness. 135 University of Ghana http://ugspace.ug.edu.gh In 2017, Fe correlated strongly with (NO -3 and Al) for the rivers (Table 4.14) and (Cl -, NO -3 , Cr and Mn) for the streams (Table 4.15). When sulphide mineral oxidizes, the oxidation possibly induces an increase in the rates of sulphates and this also persuades other trace elements (Mariotti, 1994). This probably constitutes the good conditions for the flow of oxidant elements especially nitrates. According to Mariotti, 1994, pyrite intervenes as an electron exchanger in a de-nitrification reaction given by the equation: FeS +14NO - + 4H+ → 7N (g) +10SO 2-2 3 2 4 + 5Fe 2+ + 2H2O …. Eq 4.1 In the oxidizing part, the ferrous iron is unstable in solution and precipitates in the form of hydroxide or oxide. In the mist of elevated nitrate contents, the above equation can be reduced depending on the overall reaction {Strebel et al. (1990)}: 5Fe2+ + NO -3 + 7H2O → 5FeOOH + ½ N2(g) + 9H + … Eq 4.2 The decrease of nitrates is formed by electron exchange with powerful reducers like pyrite (FeS2) organic carbon. Its therefore assumed that the above deductions might possibly be the reason why Fe correlated strongly with NO - 3 in the rivers and streams but further investigations are required. Also, the good relationship between Fe and Al for the rivers suggests the weathering of granites, monzonites, and silicate minerals (hornblende, biotite, etc.) from the underlying geology of the study area. Additionally, the good connection between Fe and Cl- for the streams suggests a possible rock-water interaction which requires further investigation. The good relationship between Fe and Cr suggests rock weathering. For the rivers sampled in 2016 (Table 4.12), Co correlates perfectly with NO -3 and its possibly from an anthropogenic source. Also, Co negatively correlated with pH for the rivers (Table 4.12). Also, for the rivers sampled in 2017 (Table 4.14), Co correlated strongly with (Ca2+, Mg2+, Na+, K+, Cl-, SO 2-4 , TDS, EC, TH, Al, Mn, and Fe) and for the streams (Table 4.15), Co correlated perfectly with (Cl-, Cr, Mn, and Fe). The relationship between Co and (Ca2+ and Mg2+ ) for the rivers suggest a possible dissolution of carbonate minerals or shales from the 136 University of Ghana http://ugspace.ug.edu.gh underlying geology to release Co as a secondary mineral (Hitzman et al., 2017). The good relationship between Co and TH suggests that Co possibly contributes to the TH of the rivers. Uren, 2013 stated that “In sedimentary rocks Co and Mn are very variable, but as a rule of thumb, they are lowest in coarse - grained sediments e.g., sandstones and highest in fine- grained sediments e.g., shales”. In the study area even though rock outcrops were not sampled and analyzed for mineral composition, the underlying geology is made up of sedimentary rocks with sand stones and shales and the concentration of Co and Mn in the rivers and streams were minimal hence the statement made by Uren, 2013 possibly holds for the strong correlation existing between Co and Mn in the rivers and streams. The good linkage between Co and (Na+, K+, and Al) might possibly be from a geogenic source and the probable source must be investigated in future works. The good relationship between Co and Fe in the rivers and streams suggest sulphide mineral oxidation or mobilization to release Co as a secondary mineral. The good relationship between Co and (SO 2-4 ) for the rivers and streams also suggests the oxidation or mobilization of sulphide minerals to release Co as a secondary mineral. The good relationship between Co and Cl reveals rock-water interactions which requires further investigations. The good relationship between Co and (TDS and EC) indicates that Co possibly contributes to the river water mineralization of the study area. In 2016, Ni correlated strongly with (Ca2+, K+, HCO -3 , SO 2- 4 , and TH) for the rivers (Table 4.12) and Fe for the streams (Table 4.13). The good relationship between Ni and (Ca2+, K+) suggests a possible rock-water interaction. The good linkage between Ni and (TH, HCO -3 ) indicates the probability of sulphide mineral hardness and same geochemical processes respectively. The good correlation between Ni and (Fe, SO 2-4 ) for the streams and rivers, respectively, specifies sulphide mineral oxidation or mobilization to release Ni as a secondary mineral. Studies carried out by Adjimah et al (1993) reveals that the sulphide minerals in the rocks of the Birimian hosted Ni as one of the pathfinder elements for the exploration of gold . Likewise, Ni highly correlated negatively with Mn for the rivers sampled in 2016. In 2017, Ni correlated 137 University of Ghana http://ugspace.ug.edu.gh strongly with (NO -3 , Al, Cr, Fe, Co) for the rivers and correlated strongly with TH for the streams. The good relationship between Ni and NO -3 for the rivers suggests a possible rock- water interaction which requires further investigation. In addition, the good relationship between Ni and Al for the rivers suggests rock weathering. But this requires further investigations since studies have shown nickel incorporation into silicate minerals (Manceau & Calas, 1985; Decarreau et al., 1987; Hseu, 2006). The good linkage between Ni and Cr for the rivers suggest rock weathering. Studies carried out by Hseu (2006), and Oze et al. (2004) shows that Ni and Cr are present in elevated concentration in soils produced from ultramafic rocks. The good relationship between Ni and Co shows sulphide mineral oxidation or mobilization to release Ni and Co as secondary minerals. Cu correlated perfectly with NO -3 for the rivers sampled in 2016. This suggest a likely rock- water interaction but further investigations are required. The perfect relationship between Cu and Co for the rivers suggest a possible sulphide mineral (chalcopyrite) mobilization to release Co as a secondary mineral. The exceedingly negative correlation between Cu and pH for rivers indicates that the pH of the rivers possibly has no significant influence on the mobilization of sulphide minerals. In 2016, Cu correlated strongly with Mn for the streams. This indicates a geogenic origin and its possibly linked to the existence of sulphide mineral (chalcopyrite etc.) mobilization to release Mn as a secondary mineral. In 2017, there was a perfect correlation between Cu and Cr and a strong correlation between Cu and Ni for the rivers. For the streams, there was a strong correlation between Cu and (Cl-, Al, Cr, Mn, Fe, Co). The good relationship between Cu and (Fe, Co, and Ni) suggest the probability sulphide minerals (chalcopyrite, pyrites) mobilization to release Co, and Ni as a secondary mineral. Fe, Cu, Co, and Ni have been discovered as path finder trace elements used in the exploration of gold in the Birimian supergroup rocks (Leube et al., 1990; Adjimah et al., 1993). In addition, the good linkage between Cu and Cr suggests a possible geogenic source. The good relationship between Cu and Cl is probably from rock-water interaction which requires further investigations. 138 University of Ghana http://ugspace.ug.edu.gh Zn correlated negatively with (K+ , pH) but correlated strongly with NO -3 for the rivers sampled in 2016 (Table 4.12). The relationship between Zn and NO -3 suggest a possible rock- water interaction which requires further investigations. Also, in 2016, Zn correlated strongly with (Ni and Fe) for the streams (Table 4.13) suggesting that the streams are possible in contact with sulphide mineral (pyrites and chalcopyrite) where Zn, Ni and Fe are released into the rivers. Adjimah et al., 1993 discovered sulphide minerals hosting trace elements like Zn, Ni etc. which were used as pathfinder elements for the exploration of gold in the Birimian super group rocks. In addition, Zn correlated strongly with Mn for the sampled streams suggesting the likelihood of a high stream discharge (Khan et al., 1998) from the upstream environment (Birimian supergroup rocks) to the downstream environment (Apollonian formation), since the study area is in a deposition environment. In 2017, Zn correlated strongly with (Fe, Co, Ni and Cu) for the sampled rivers (Table 4.14) suggesting that the rivers are in contact with sulphide minerals from the underlying geology. Also, the good relationship between Zn and Al (Table 4.14) for the rivers is possibly from geogenic sources which requires further investigations. The strong relationship between Zn and Cr for the rivers (Table 4.14) is from a geogenic source. Additionally, for the streams sampled in 2017 (Table 4.15), Zn correlated strongly with (K+, Cl- and NO -3 ) suggesting the possible presence of anthropogenic sources or rock-water interaction, but further investigations are required. Also, there was a good relationship between Zn and HCO -3 for the streams (Table 4.15) suggesting a probable geochemical processes. The good relationship between Zn and TDS for the streams suggests that Zn is contributing to the mineralization of the stream. The good relationship between Zn and (Al, Cr, Mn, Fe, Co, and Cu) for the streams might likely be derived from geogenic sources. In 2016, As in the sampled rivers correlated perfectly with Fe and Mn (Table 4.12) suggesting that the rivers might likely be in contact with ferromagnesium minerals or sulphide minerals (Pyrites, Chalcopyrite etc.) where trace elements such as As, Mn, Fe, Cu, Ag etc. are hosted as pathfinder elements for the discovery of gold (Luebe et al., 1990) in the rocks of the Birimian. 139 University of Ghana http://ugspace.ug.edu.gh Also, in 2016 and 2017, As correlated strongly with Cr for the streams and rivers, respectively suggesting a geogenic source. Also, there was a perfect and a strong correlation between As and (Cu and Zn) for the rivers sampled in 2017 indicating a geogenic source like sulphide mineral mobilization. Additionally, in 2017, As correlated perfectly with (Ca2+, Mg2+, HCO -3 ) for the streams (Table 4.15) indicating that the streams might possibly be in contact with sulphide minerals, silicate minerals (hornblende etc.) and monzonite rocks of the study area. Works carried out by Alam et al. (2014) suggests that “the weathering of silicate minerals is an essential Arsenic releasing mechanism and that elevated pH and low redox potential promotes the weathering of silicate minerals and release As concentration. The good relationship between As and TH suggest a likely arsenic hardness in the rivers and streams. In addition, the perfect relationship between As and SO 2-4 for the streams (Table 4.15) suggests a probable oxidation of sulphide minerals. The perfect correlation between As and (EC and TDS) for the streams indicates that As is one of the major elements that contribute to the mineralization of the streams. In 2016, the Cd in the sampled rivers (Table 4.12) correlated negatively with Na+. Also, for the streams, Cd negatively correlated with SO 2-4 (Table 4.13) suggesting that SO 2- 4 liberated from anthropogenic or geogenic sources is possibly not contributing to Cd content in the streams. In addition, Cd in the streams correlated strongly with (Cr and As) suggesting a probable geogenic source. In 2017, Cd correlated strongly with NO -3 for the rivers (Table 4.14) indicating a possible anthropogenic source. Also, Cd correlated strongly and perfectly with (Al, Cr, Mn, Fe, Co, Ni, Zn and Cu) suggesting a possible geogenic source. Also, Cd correlated strongly with K+ for the streams (Table 4.15) suggesting a possible anthropogenic source. In addition, Cd correlated perfectly with HCO -3 for the streams indicating a possible geochemical process but further investigations are required. Likewise, Cd correlated strongly with TDS for the streams suggesting that Cd in the streams might possibly be involved in physiochemical reactions of the streams. Pb in the rivers sampled in 2016 (Table 4.12) negatively correlated with HCO -3 indicating the absence of Pb geochemical processes. In addition, there was a perfect correlation between Pb 140 University of Ghana http://ugspace.ug.edu.gh and (Fe, Mn, Co and As) suggesting rock weathering {sulphide minerals (pyrites, arsenopyrites, chalcopyrite) oxidation}. Additionally, Pb correlated perfectly with Cr suggesting a possible rock-water interaction which requires further investigations. For the stream sampled in 2016 (Table 4.13), Pb correlated negatively with SO 2-4 but correlated strongly with (Al, Cr, and Cu). The negative relationship between Pb and SO 2-4 indicates that SO 2-4 might possible not influence the presence of Pb in the rivers and streams. The good relationship between Pb and (Al and Cr) for the streams sampled in 2016 suggests a possible geogenic or anthropogenic source. Additionally, the perfect relationship between Pb and Cu for the streams suggests the mobilization of sulphide minerals (Chalcopyrite’s) to release Pb as a secondary mineral. In 2017, the Pb content in the rivers (Table 4.14) correlated strongly with NO -3 suggesting a possible anthropogenic source. Also, a good relationship was observed between Pb and Al in the stream suggesting a possible geogenic source. Also, the good relationship between Pb and (Fe, Ni and Zn) is from a geogenic source (sulphide mineral oxidation or mobilization) The good linkage between Pb and Cd suggests a probable anthropogenic source, which requires further investigation. For the streams sampled in 2017 (Table 4.15), Pb correlated strongly with Ca2+. This possibly indicate rock-water interaction which requires further investigation. Also, Pb correlated strongly with (EC and TDS) signifying that Pb contributes to the stream mineralization. The above correlated parameters being negative or positive, shows that the measured ions and trace elements in the rivers and streams are coming from the same geochemical processes and have a strong to moderate influence on each other. Also from the above correlation, it can be said that the chemistry of surface water in the Lower Tano River Basin is possibly controlled by rock weathering with few being controlled by anthropogenic sources. In addition, it can be concluded that the Nickel (Ni) content (Table 4.12) in the rivers sampled in 2016, the Total hardness (TH) concentration in the stream sampled in 2016 (Table 4.13), the Cobalt (Co) content in the rivers sampled in 2017 and the Zinc (Zn) content in the streams sampled in 2017 are important drinking water parameters that exists in the rivers and streams of the Lower Tano River Basin. This is because Ni, TH, Co and Zn, significantly correlated with 6, 6, 12, and 11 parameters, respectively out of the 23 measured variables. Additionally, the measured 141 University of Ghana http://ugspace.ug.edu.gh parameters showing moderate to weak correlation indicates that multiple sources and flow are likely responsible for the surface water (rivers and streams) quality in the Lower Tano River Basin. 4.2.2 Groundwater chemistry and its suitability for drinking 4.2.2.1 Results of the field data The results of the descriptive statistical analysis of the field data for the hand dug wells and boreholes sampled in each specific year are shown in table 4.16, 4.17, 4.18,4.19,4.20 and 4.21, respectively. Table 4. 16: Descriptive statistics of field parameters for the Boreholes drilled in 2013 Field Parameters T°c pH EC (µS/cm) TDS (mg/L) Number of samples 30 30 30 30 Mean 24.73 6.94 219.22 114.42 Standard Error 0.08 0.02 7.85 5.21 Median 24.90 6.98 218.00 108.30 Mode 24.90 6.99 219.00 108.00 Standard Deviation 0.44 0.10 43.02 28.55 Sample Variance 0.19 0.01 1850.86 815.15 Kurtosis -0.59 1.43 2.18 1.90 Skewness -0.59 -1.21 -0.66 0.49 Minimum 24.00 6.67 103.00 52.00 Maximum 25.50 7.11 301.00 194.00 Sum 742.00 208.22 6576.70 3432.70 Confidence Level (95.0%) 0.16 0.04 16.06 10.66 Table 4. 17: Descriptive statistics of the field parameters for the Boreholes drilled in 2014 to 2015 Field Parameters EC(μS/cm) Salinity TDS (mg/L) pH Number of Samples 18 18 18 18 Mean 268.22 0.09 113.58 6.27 Standard Error 57.48 0.02 27.56 0.15 Median 168.50 0.08 70.90 6.20 Mode N/A 0.08 70.90 6.00 Standard Deviation 243.86 0.09 116.93 0.65 Sample Variance 59469.01 0.01 13673.20 0.42 Kurtosis 10.84 16.28 11.62 -0.04 Skewness 3.08 3.95 3.22 0.23 Minimum 101.00 0.04 34.20 5.20 Maximum 1150.00 0.43 542.20 7.70 Sum 4828.00 1.61 2044.40 112.80 Confidence Level (95.0%) 121.27 0.04 58.15 0.32 142 University of Ghana http://ugspace.ug.edu.gh Table 4. 18: Descriptive statistics of field parameters for the Hand dug wells sampled in 2016. Field Parameters T°C Salinity pH TDS (mg/L) EC (µS/cm) Number of samples 36 36 36 36 36 Mean 27.48 0.17 6.42 298.78 454.05 Standard Error 0.23 0.04 0.07 34.27 50.40 Median 27.35 0.10 6.41 224.00 345.50 Mode 27.70 0.00 6.20 215.00 321.00 Standard Deviation 1.35 0.22 0.44 205.64 302.38 Sample Variance 1.82 0.05 0.20 42286.15 91432.69 Kurtosis -0.25 4.68 1.42 -0.97 -0.94 Skewness -0.21 1.86 0.79 0.68 0.68 Minimum 24.00 0.00 5.63 30.00 44.20 Maximum 29.90 1.00 7.80 709.00 1063.00 Sum 989.20 6.00 230.94 10756.25 16345.90 Confidence Level (95.0%) 0.46 0.07 0.15 69.58 102.31 Table 4. 19: Descriptive statistics of field parameters for the Boreholes sampled in 2016 Parameters TDS mg/L EC µS/cm Salinity T°C pH Number of Samples 44 44 44 44 44 Mean 164.34 261.47 0.05 27.75 6.33 Standard Error 16.15 25.27 0.01 0.15 0.09 Median 145.00 245.50 0.00 27.65 6.27 Mode 85.00 127.60 0.00 27.50 6.80 Standard Deviation 107.10 167.62 0.09 1.00 0.61 Sample Variance 11469.39 28095.86 0.01 1.00 0.37 Kurtosis 0.74 -0.06 6.22 0.63 2.37 Skewness 1.03 0.75 2.36 -0.16 0.88 Minimum 27.00 39.70 0.00 25.30 5.26 Maximum 484.00 721.00 0.40 30.00 8.51 Sum 7231.00 11504.80 2.10 1220.90 278.50 Confidence Level (95.0%) 32.56 50.96 0.03 0.30 0.19 Table 4. 20: Descriptive statistics of field parameters for the Hand dug wells sampled in 2017 Parameters T° C pH TDS mg/L EC µS/cm Salinity Number of samples 30 30 30 30 30 Mean 28.31 5.98 220.07 396.41 0.17 Standard Error 0.35 0.16 27.16 48.22 0.03 Median 28.20 5.97 181.00 328.50 0.11 Mode 28.40 5.60 375.00 682.00 0.00 Standard Deviation 1.83 0.89 148.79 264.12 0.16 Sample Variance 3.35 0.80 22137.10 69759.48 0.03 Kurtosis 7.67 -0.22 -0.70 -0.62 0.60 Skewness -1.75 -0.46 0.70 0.71 1.03 Minimum 21.40 4.10 24.00 43.20 0.00 Maximum 31.70 7.40 546.00 994.00 0.63 Sum 764.50 179.27 6602.00 11892.30 5.24 Confidence Level (95.0%) 0.72 0.33 55.56 98.62 0.06 143 University of Ghana http://ugspace.ug.edu.gh Table 4. 21: Descriptive statistics of field parameters for the Boreholes sampled in 2017 Parameters TDS mg/L EC µS/cm T˚C PH Salinity Number of samples 53 53 53 53 53 Mean 150.06 252.82 28.46 6.02 0.06 Standard Error 13.65 21.48 0.22 0.11 0.01 Median 113.00 206.00 28.00 6.05 0.03 Mode 85.00 127.60 27.50 6.20 0.00 Standard Deviation 99.38 156.35 1.57 0.78 0.08 Sample Variance 9875.75 24444.14 2.48 0.61 0.01 Kurtosis 1.46 0.22 -0.32 1.40 5.43 Skewness 1.28 0.93 0.80 0.03 2.08 Minimum 39.00 70.00 26.00 4.10 0.00 Maximum 484.00 721.00 32.02 8.51 0.40 Sum 7953.20 13399.50 1508.42 319.13 3.10 Confidence Level (95.0%) 27.39 43.09 0.43 0.22 0.02 From table 4.16, the temperature for the boreholes drilled in 2013 vary from 24° C to 25.50° C with a mean of 24.73° C. The temperature for the boreholes drilled from 2014 to 2015 was not measured due to faulty meters. In 2016 during the rainy season, the temperature of the hand dug well and boreholes sampled from the aquifer of the Apollonian formation and the Birimian Supergroup (Table 4.18 and 4.19) range from 24° C to 29.90° C with a mean of 27.48° C and from 25.30° C to 30° C with a mean of 27.75° C, respectively. For the hand dug wells and boreholes sampled in 2017 during the dry season, the temperature varies from 21.40° C to 31.70° C with an average of 28.31° C and from 26° C to 32.02° C with a mean of 28.46° C (Table 4.20 and 4.21), respectively. From table 4.16, the pH of the boreholes drilled in 2013 vary from 6.67 to 7.11 with a mean of 6.94. The least pH value is recorded for a borehole drilled at Kamgbunli in the aquifer of the Apollonian formation and the maximum pH value is recorded for a borehole drilled at Bobrama also in the aquifer of the Apollonian formation. The pH of the entire borehole water is slightly acidic to neutral but falls within WHO (2011) permissible limit of 6.5 to 8.5 for drinking water. For the boreholes drilled from 2014 to 2015 (Table 4.17), the pH varies from 5.2 to 7.7 with a mean of 6.27. The minimum and maximum pH is recorded for a borehole drilled at Kengen and Newtown, respectively and both boreholes are in the aquifer of the Apollonian formation. 144 University of Ghana http://ugspace.ug.edu.gh The pH of the borehole water is acidic to neutral with 80 % (n=18) below WHO (2011) permissible limit of 6.5 to 8.5 for drinking water. For the hand dug wells sampled in 2016 (Table 4.18), the minimum pH value (pH = 5.63) is recorded for a hand dug well sampled at Nkroful in the aquifer of the Birimian Supergroup and the maximum pH (pH = 7.80) is recorded for a hand dug well sampled at Ankobra in the aquifer of the Apollonian formation. 67% (n = 36) of the sampled hand dug wells are below WHO (2011) permissible limit of 6.5 to 8.5 for drinking water and the remaining 33% are within the acceptable limits. Out of the 26 acidic hand dug well (n=36) water, 19 hand dug wells were sampled from the aquifer of the Apollonian formation and the remaining 7 were sampled from the aquifer of the Birimian Supergroup rocks. The minimum pH (pH = 5.26) of the borehole water sampled in 2016 (Table 4.19) is recorded for a borehole sampled at Salman in the aquifer of the Birimian Supergroup and the maximum pH (pH = 8.51) is measured for a borehole sampled at Ankobra in the aquifer of the Apollonian formation. 68.18% of the sampled boreholes (n=44) are below WHO (2011) permissible limit of 6.5 to 8.5 for drinking water. Out of the 27 (n=44) acidic borehole water, 18 boreholes were sampled from the aquifer of the Apollonian formation and the remaining 9 were taken from the aquifer of the Birimian Super group. For the hand dug wells sampled in 2017 (Table 4.20), the minimum and maximum pH is recorded (pH = 4.10 and 7.40) for hand dug wells sampled at Elubo in the aquifer of the Apollonian formation (fig 3.54). 66.7% of the hand dug wells (n=30) all sampled from the aquifer of the Birimian supergroup are below WHO (2011) permissible limit of 6.5 – 8.5 for drinking water. Also, for the 2017 borehole samples, the minimum and maximum pH (pH = 4.0 and 8.51) values is recorded for boreholes sampled at Atwinbaso and Ampaim, respectively. These boreholes are all located in the aquifer of the Apollonian formation. 81.48% of the boreholes (n=54) are below WHO (2011) permissible limit of 6.5 – 8.5 for drinking water and out of the 44 acidic borehole water, 28 boreholes were taken from the aquifer 145 University of Ghana http://ugspace.ug.edu.gh of the Apollonian formation and the remaining 16 are taken from the aquifer of the Birimian Supergroup. The acidity of most groundwater samples is attributed to clay minerals like silica and kaolin which exist in the rocks of the Apollonian and the Birimian supergroup . These clay minerals act as H+ buffers (Sjostrom, 1993). Another source of low pH in the groundwater is attributed to the oxidation and hydrolysis of sulphide minerals {Preda and Cox (2000, 2001)}. In the study area, Luebe et .al (1990) discovered sulphide minerals like pyrites in the rocks of the Birimian and Keese,1985 also discovered nodules of pyrites in the rocks of the Apollonian. When these pyrites interact with the groundwater, H+ concentration in the groundwater increases lowering the pH of the groundwater. Infiltration of rainwater also lowered the pH of the groundwater. The study area records high amount of rainfall and Edjah et al. (2015) observed that the source of groundwater recharge in the study area was of meteoric origin. Also, the pH of the sampled rainwater for this study ranges from 5.2 to 6.5 and the TDS varies from 8.9 to 20 mg/L In the study area, there are lots of trees and during cellular respiration by the trees, CO2 gas is released and that dissolves in the groundwater resulting in the formation of H2CO3. When H2CO3 dissociates it leads to an increase in HCO - + 3 and H (Isa et al., 2012). Once H+ increases, the pH of the groundwater is lowered. Also, parts of the Lower Tano River Basin are composed of granites, phyllites and schists (Fig 3.3 and 3.4) and according to Wright et al.1985, these types of rocks produce acidic water. From figure 4.10, it is seen that the aquifer of the Apollonian formation produces most acidic groundwater. The results of the pH values for the groundwater sampled from 2013 to 2017 are like the results obtained by Edjah et al. (2015) who worked in parts of the Lower Tano 146 University of Ghana http://ugspace.ug.edu.gh river basin. In addition, WRC (2012) recorded low pH values (< 7) for some groundwater across the Tano Basin. Figure 4. 10: Spatial distribution map of pH in groundwater of the Lower Tano River Basin. TDS is an important parameter that can influence the major compositions in groundwater quality (Paznand & Javanshir, 2014). From table 4.16, the minimum TDS concentration (TDS = 52 mg/L) for the boreholes drilled in 2013 is recorded at Kegyina in the aquifer of the Birimian Supergroup and the maximum TDS concentration (TDS= 194 mg/L) is measured at Mpeasem in the aquifer of the Apollonian formation. Also, from table 4.17, the minimum TDS concentration (TDS= 34. 2 mg/L) for the boreholes drilled from 2014 to 2015 is measured in a borehole developed at Alumatuope in the aquifer 147 University of Ghana http://ugspace.ug.edu.gh of the Apollonian formation and the maximum TDS concentration (TDS=542.2 mg/L) occurs in a borehole drilled at Newtown, also in the aquifer of the Apollonian formation. In 2016, the minimum TDS concentration (TDS = 30 mg/L) is recorded for a hand dug well sampled at Gyegyekrom in the aquifer of the Birimian Supergroup and the maximum TDS (TDS= 709 m/L) content is recorded for a hand dug well sampled at Esiama in the aquifer of the Apollonian formation. Also in 2016, the minimum and maximum TDS concentrations (TDS= 27 mg/L and 484 mg/L) are recorded for boreholes sampled at New Nzulezu and Asanda, respectively. Both boreholes were taken from the aquifer of the Apollonian formation. In 2017, the minimum and maximum TDS (TDS = 24 m/L and 546 m/L, respectively) content is recorded for hand dug wells sampled (Table 4.20) at Gyegyekrom in the aquifer of the Birimian Supergroup and Esiama in the aquifer of the Apollonian formation, respectively. For the borehole samples, the minimum and maximum TDS concentrations (TDS= 39 mg/L and 484 mg/L) is measured in boreholes sampled at Tiekobo no 1 and Esiama respectively. Both boreholes are in the aquifer of the Apollonian formation. The degree of groundwater quality can be classified as fresh if the TDS is < 1000 mg/L; brackish if the TDS is between 1000 to 10,000 mg/L; saline if the TDS i s ranged from 10,000 to 1,000,000 mg/L ( Todd, 1980). Accordingly, the entire quality of the sampled groundwater (n=211) is fresh. The spatial distribution map of TDS (Fig 4.11) indicates that all the sampled groundwater are below WHO (2011) desirable limit of 500 mg/L and maximum permissible limit of 1500 mg/L. The low TDS content in the groundwater reveals a that the groundwater has short residence time which will be explained further in the 5th specific objective. 148 University of Ghana http://ugspace.ug.edu.gh Figure 4. 11: Spatial distribution map of TDS values in groundwater in the Lower Tano River Basin. For the boreholes, the electrical conductivity (EC) values in 2013 samples (Table 4.16) had the maximum value (EC = 301 µS/cm) recorded for a borehole drilled at Mpeasem in the aquifer of the Apollonian formation and the minimum value (EC = 103 µS/cm) recorded for a borehole drilled at Kegyina in the aquifer of the Birimian Supergroup. From 2014 to 2015 (Table 4.17), the minimum and maximum EC concentration (EC = 101 µS/cm and 1150 µS/cm) is recorded in boreholes drilled at Alumatupe and Newtown respectively. Both towns are in the aquifer of the Apollonian formation. The EC content in the hand dug wells sampled in 2016 (Table 4.18) had the minimum value (EC = 44.20 µS/cm) recorded for a hand dug well sampled at Gyegyekrom in the aquifer of the Birimian Supergroup and the maximum value (EC = 1063 µS/cm) recorded for a hand dug well sampled at Esiama in the aquifer of the Apollonian formation. In 2016, the minimum and 149 University of Ghana http://ugspace.ug.edu.gh maximum EC (EC = 39.70 µS/cm and 721 µS/cm) (Table 4.19) content are recorded in boreholes sampled at New Nzulezu and Asanta, respectively. Both boreholes are in the aquifer of the Apollonian formation. The EC content in the hand dug wells sampled in 2017 (Table 4.20) had the minimum EC value (EC = 43.20 µS/cm) recorded for a hand dug well sampled at Gyegyekrom in the aquifer of the Birimian Supergroup and the maximum value (EC = 994 µS/cm) recorded for a hand dug well sampled at Esiama in the aquifer of the Apollonian formation. Also in the same year, the minimum EC value (EC = 70 µS/cm) is measured in a borehole sampled at Tiekobo no 1 and the maximum EC (EC = 721 µS/cm) value is recorded in a borehole sampled at Esiama. Both boreholes are in the aquifer of the Apollonian Formation. Per WHO (2011), the most desirable limit of EC in drinking water is 1500 µS/cm. EC in groundwater can be classified as type I, if the enrichments of salts are low (EC<1500 µS/cm); type II, if the enrichment of salts are medium (EC: 1,500 and 3000 µS/cm); and type III, if the enrichments of salts are high (EC > 3000 µS/cm) (Sarath Prasanth et al, 2012). According to the above classification of EC, 100% of the total groundwater samples (n=211) fall under type I (low enrichment of salts). The low EC values (EC< 1500 µS/cm) recorded for the groundwater is an indication of short residence time (Hunslow, 1995) which will be explained in the 5th specific objective. Also, from Fig (4.12), the minimum EC values in the groundwater represented by shades of green colour is concentrated mostly in the aquifer of the Birimian supergroup with few representations in the aquifer of the Apollonian formation. The results obtained for TDS and EC for the groundwater samples is like the results obtained by Edjah et al. (2015) and WRC (2012). 150 University of Ghana http://ugspace.ug.edu.gh Figure 4. 12: Spatial distribution map of EC (µS/cm) concentrations in groundwater in the Lower Tano River Basin. 4.2.2.2 Results of the Laboratory analysis (Hydrochemical data) and Alkalinity (as in Bicarbonate) in groundwater The results of the descriptive statistical summaries of the hydrochemical data are shown in table 4.22,4.23 and 4.24,4.25, and 4.26. Table 4. 22: Descriptive statistics of the hydrochemical data for the Boreholes drilled in 2013 Parameters (mg/L) Ca2+ Mg2+ TH Cl- SO 2- 4 NO - 3 Number of samples 30 30 30 30 30 30 Mean 70.70 42.30 110.77 39.21 6.77 1.20 Standard Error 4.16 3.77 7.19 5.50 0.43 0.08 Median 67.50 41.50 104.00 31.50 6.86 1.09 Mode 53.00 23.00 111.00 12.00 10.00 1.09 Standard Deviation 22.81 20.63 39.39 30.12 2.37 0.42 Sample Variance 520.22 425.60 1551.63 907.46 5.61 0.18 Kurtosis 2.08 -1.33 -0.39 -0.79 1.13 1.74 Skewness 1.05 0.18 0.63 0.52 -0.32 1.37 Minimum 35.00 12.00 58.00 0.04 0.01 0.54 Maximum 143.00 79.00 205.00 96.00 11.00 2.31 Sum 2121.00 1269.00 3323.00 1176.38 202.96 34.83 Confidence Level (95.0%) 8.52 7.70 14.71 11.25 0.88 0.16 151 University of Ghana http://ugspace.ug.edu.gh Table 4. 23: Descriptive statistics of the hydrochemical data for the Boreholes drilled in 2014 to 2015 Parameters (mg/L) Ca2+ Mg2+ Na+ K+ TH HCO - Cl- 3 SO 2- 4 Number of samples 18 18 18 18 18 18 18 18 Mean 22.83 4.84 22.49 3.08 76.00 55.83 32.42 8.82 Standard Error 4.93 1.51 8.37 0.91 15.37 14.41 11.50 1.95 Median 15 2.65 14 1.8 45 26 24.1 8 Mode 15 2.6 N/A 1.1 37 162 5.5 2 Standard Deviation 20.91 6.39 35.51 3.85 65.22 61.15 48.79 8.05 Sample Variance 437.21 40.84 1261.15 14.86 4253.41 3739.09 2380.02 64.78 Kurtosis 1.27 5.49 16.38 4.65 -0.38 -0.21 16.35 4.24 Skewness 1.47 2.57 3.97 2.24 1.14 1.25 3.96 1.78 Minimum 4 0.7 3.4 0.2 19 5 5.5 1 Maximum 71 22.6 162 14.6 196 171 224 33 Sum 411 87.1 404.8 55.4 1368 1005 583.6 150 Count 18 18 18 18 18 18 18 17 Confidence Level(95.0%) 10.40 3.18 17.66 1.92 32.43 30.41 24.26 4.14 Table 4. 24: Descriptive statistics of the hydrochemical data for the Hand dug wells sampled in 2016 Parameters (mg/L) Ca2+ Mg2+ TH Na+ K+ Cl- HCO - SO 2- NO - 3 4 3 Number of samples 36 36 36 36 36 36 36 36 36 Mean 19.56 3.86 64.73 44.97 13.50 47.76 38.72 54.64 2.13 Standard Error 2.48 0.90 7.85 5.13 2.94 6.82 5.81 6.54 0.47 Median 17.44 2.18 56.49 32.36 7.46 30.99 26.82 46.53 1.27 Mode N/A N/A N/A N/A 0.63 19.99 12.19 N/A 0.36 Standard Deviation 14.89 5.41 47.09 30.79 17.63 40.90 34.84 39.26 2.83 Sample Variance 221.57 29.31 2217.48 947.78 310.75 1672.97 1213.72 1541.10 8.03 Kurtosis 2.07 19.36 0.86 0.19 5.99 2.62 5.14 1.46 5.10 Skewness 1.20 4.01 1.11 1.02 2.28 1.67 1.97 1.37 2.43 Minimum 1.47 0.41 7.13 5.20 0.32 6.00 4.88 6.23 0.27 Maximum 69.21 31.31 191.73 125.10 81.61 171.95 170.69 149.51 11.06 Sum 704.12 138.94 2330.34 1619.09 485.99 1719.47 1393.74 1967.19 76.58 Confidence Level(95.0%) 5.04 1.83 15.93 10.42 5.96 13.84 11.79 13.28 0.96 Table 4. 25: Descriptive statistics of the hydrochemical data for the Boreholes sampled in 2016 Parameters (mg/L) Ca2+ Mg2+ TH Na+ K+ Cl- HCO - SO 2- 3 4 NO - 3 Number of samples 44 44 44 44 44 44 44 44 44 Mean 13.01 3.91 48.60 25.97 3.57 26.54 37.05 34.85 1.04 Standard Error 1.75 0.52 4.94 2.51 0.65 2.81 6.22 5.14 0.13 Median 9.74 2.57 40.38 24.61 1.61 22.99 24.38 25.47 0.87 Mode N/A N/A N/A N/A 2 6.00 26.82 N/A 0.29 Standard Deviation 11.64 3.42 32.78 16.67 4.34 18.67 41.27 34.07 0.87 Sample Variance 135.40 11.70 1074.23 277.76 18.80 348.50 1703.34 1161.01 0.76 Kurtosis 4.09 3.37 0.95 3.08 2.84 0.88 5.49 4.35 5.16 Skewness 1.73 1.67 0.95 1.41 1.86 1.03 2.26 1.98 1.90 Minimum 0.52 0.17 7.77 3.78 0.23 4.00 2.44 0.23 0.29 Maximum 58.10 16.46 154.98 86.30 17.07 83.97 182.88 148.16 4.60 Sum 572.32 172.19 2138.19 1142.80 156.90 1167.64 1630.39 1533.37 45.92 Confidence Level(95.0%) 3.54 1.04 9.96 5.07 1.32 5.68 12.55 10.36 0.27 152 University of Ghana http://ugspace.ug.edu.gh Table 4. 26: Descriptive statistics of the hydrochemical data for the Hand dug well sampled in 2017 Parameters (mg/L) Ca2+ Mg2+ TH Na+ K+ Cl- HCO - 2- 3 SO4 NO - 3 Number of Samples 30 30 30 30 30 30 30 30 30 Mean 23.26 5.95 82.57 40.37 11.18 44.19 94.07 27.53 1.11 Standard Error 3.63 0.74 11.21 5.32 1.89 6.88 16.58 5.17 0.16 Median 16.45 5.28 67.00 31.35 7.82 26.99 60.96 16.20 0.76 Mode 22.47 4.67 75.34 26.58 6.94 23.99 60.96 0.00 3.16 Standard Deviation 19.88 4.06 61.41 29.14 10.35 37.69 90.79 28.33 0.89 Sample Variance 395.14 16.52 3771.18 849.25 107.13 1420.73 8242.28 802.87 0.80 Kurtosis 0.18 -0.21 0.38 0.09 1.35 0.74 1.33 0.39 1.92 Skewness 1.10 0.72 1.13 1.04 1.42 1.24 1.34 1.09 1.59 Minimum 1.39 0.65 9.95 5.94 0.66 4.00 2.44 0.00 0.28 Maximum 72.21 15.02 232.69 110.20 39.72 133.96 353.56 97.76 3.60 Sum 697.73 178.44 2477.04 1211.15 335.44 1325.59 2822.20 826.04 33.21 Confidence Level(95.0%) 7.42 1.52 22.93 10.88 3.86 14.07 33.90 10.58 0.33 Table 4. 27: Descriptive statistics of the hydrochemical data for the Boreholes sampled in 2017 Parameters(mg/L) Ca2+ Mg2+ TH Na+ K+ Cl- HCO - 2- 3 SO4 NO - 3 Number of Samples 53 53 53 53 53 53 53 53 53 Mean 9.50 7.38 46.91 24.40 3.32 20.48 55.50 31.34 0.89 Standard Error 1.34 0.98 4.89 2.24 0.72 2.24 6.43 5.57 0.11 Median 6.44 5.22 38.68 17.96 1.79 17.99 43.89 12.62 0.76 Mode 20.09 N/A 12.00 34.59 3.28 19.99 26.82 0.00 0.38 Standard Deviation 9.78 7.11 35.63 16.32 5.27 16.28 46.80 40.53 0.78 Sample Variance 95.65 50.62 1269.20 266.49 27.73 265.06 2190.30 1643.07 0.61 Kurtosis 4.71 4.50 3.65 2.50 31.43 5.59 2.69 3.57 5.92 Skewness 2.02 1.93 1.59 1.41 5.13 1.95 1.57 1.85 2.03 Minimum 0.78 0.20 4.63 3.58 0.19 2.00 2.44 0.00 0.05 Maximum 48.03 36.07 186.07 85.67 36.59 89.97 219.45 165.76 4.06 Sum 503.53 391.06 2486.17 1293.23 175.70 1085.69 2941.73 1660.97 44.58 Confidence Level (95.0%) 2.70 1.96 9.82 4.50 1.45 4.49 12.90 11.17 0.22 In 2013 (Table 4.22), the minimum calcium (Ca =35 mg/L) content in the borehole water is recorded for a borehole drilled at Nyamebekyere in the aquifer of the Birimian Supergroup and the maximum (Ca = 143 mg/L) value is recorded for a borehole drilled at Dadwen (Table 4.22) also in the aquifer of the Birimian Supergroup. In 2014 and 2015 (Table 4.23), the minimum calcium concentration (Ca = 4 mg/L) is recorded for a borehole drilled at Elloyin and the maximum calcium value (Ca = 71 mg/L) is recorded for a borehole drilled at Ehoaka, all in the aquifer of the Apollonian formation. In 2016, the lowest and highest calcium values (Ca= 1.47 mg/L and 69.21 mg/L) in the hand dug well water (Table 4.24) is recorded for hand dug wells sampled at Bobrama and Esiama, respectively. Both hand dug wells are in the aquifer of the Apollonian formation. For 153 University of Ghana http://ugspace.ug.edu.gh the boreholes samples (Table 4.25), the minimum and maximum calcium concentration (Ca = 0.52 mg/L and 58.10 mg/L) is measured in boreholes sampled at Atwibanso and Ankobra new site. Both towns are in the aquifer of the Apollonian formation. In 2017 (Table 4.26), the minimum calcium content (Ca = 1.39 mg/L) is measured in a hand dug well sampled at Gyegyekrom in the aquifer of the Birimian Supergroup and the maximum calcium (Ca = 72.21 mg/L) content is measured in a hand dug well sampled at Esiama in the aquifer of the Apollonian formation. For the borehole samples (Table 4.27), the minimum calcium concentration (Ca = 0.78 mg/L) is measured in a borehole sampled at Nglekazo in the aquifer of the Apollonian formation and the maximum value (Ca =48.03 mg/L) is recorded for a borehole sampled at Salman in the aquifer of the Birimian Supergroup. Figure 4.13 shows the spatial distribution map of Ca2+ in the groundwater of the study area. From the map, high calcium content represented by shades of red is seen in groundwater sampled from the aquifer of the Birimian Supergroup (NE and SE) of the study catchment. The source of the elevated calcium in the groundwater is attributed to carbonate mineral dissolution and the chemical breakdown of feldspars and plagioclase. In the study area, carbonate minerals like limestones exist in the rocks of the Apollonian and silicate minerals (feldspars and plagioclase) exist in the rocks of the Birimian Supergroup (Fig 3.3 and 3.4). The low calcium content for the groundwater might probably be derived from the occurrence of slow chemical weathering of silicate minerals (hornblende, etc.), granitic rocks and the dissolution of carbonate minerals {Goldich, 1938; Appello and Postma (1999); Fig 3.3 and 3.4} from the underlying geology. This might be due some of the groundwater having high pH (pH = 6.3 to 8.5) values. 154 University of Ghana http://ugspace.ug.edu.gh Figure 4.13: Spatial distribution map of calcium concentrations in groundwater in the Lower Tano River Basin In 2013, the minimum (Mg2+ = 12 mg/L) magnesium concentration is recorded for boreholes drilled at Ankyernin in the aquifer of the Birimian Supergroup, and Akpendue in the aquifer of the Apollonian formation. The maximum Mg2+ value (Mg2+ = 79 mg/L) is measured in a borehole drilled at Kutukrom, in the aquifer of the Birimian Supergroup. From 2014 to 2015 (Table 4.23), the minimum and maximum Mg2+ concentration (Mg2+ = 0.7 mg/L and 22.6 mg/L) is measured for boreholes drilled at Effasu and Newtown, respectively. Both boreholes are in the aquifer of the Apollonian formation. In 2016, the minimum magnesium (Mg2+) concentration (Mg2+ = 0.41 mg/L) is measured in a hand dug well (Table 4.24) sampled at Half Assini in the aquifer of the Apollonian formation and the maximum (Mg2+= 31.31 mg/L) is recorded in a hand dug well sampled at Ankobra also in the same aquifer. In that same year, the minimum and maximum Mg2+ concentration (Mg2+= 0.17 mg/L and 16.46 mg/L) (Table 4.25) is measured in boreholes 155 University of Ghana http://ugspace.ug.edu.gh sampled at Tiekobo 1 and Azelenuano, respectively. Both boreholes are in the aquifer of the Apollonian formation. In 2017 (Table 4.26), the minimum Mg2+ content (Mg2+= 0.65 mg/L) is recorded in a hand dug well sampled at Elubo in the aquifer of the Birimian formation and the maximum concentration (Mg2+=15.02 mg/L) is measured in a hand dug well sampled at Nkroful also in the aquifer of the Birimian formation. Also, in 2017, the minimum Mg2+ concentration (Mg2+= 0.20 mg/L) (Table 4.27) is recorded in a borehole sampled at Ngelekyi in the aquifer of the Apollonian formation and the maximum (Mg2+= 0.41 mg/L) is measured in a borehole sampled at Kamgbunli also in the aquifer of the Apollonian formation. The spatial distribution map of magnesium (Fig 4.14) reveals that groundwater located in the aquifer of the Birimian Supergroup (SE and NE zone) represented by shades of red colour is above WHO (2011) permissible limit of 50 mg/ L for drinking water. The high Magnesium content in groundwater from the aquifer of the Birimian Supergroup (SE and NE zone) might be derived from the high weatherability of hornblende (CaMgSi2O22(OH)2), biotite [K (Mg, Fe)3(AlSi3) O (O10 H, F)2] etc., which exist in the Birimian Supergroup rocks of the study area (See, fig 3.3 and 3.4). The rest of the groundwater mostly situated in the aquifer of the Apollonian formations with few in the aquifer of the Birimian supergroup of the study catchment (Fig 4.14) are below WHO permissible limit of 50 mg/L for drinking water. The reasons accounting to the low Mg2+ values recorded for the groundwater is the same reasons for the low calcium values in the aquifer of the Apollonian formation and the Birimian supergroup as discussed in previous chapters. 156 University of Ghana http://ugspace.ug.edu.gh Figure 4. 14: Spatial distribution map of magnesium concentrations in groundwater in the Lower Tano River Basin. For the total hardness, the maximum allowable limit for drinking purpose is 500 mg/L and the most desirable limit is 100 mg/L per the WHO (2011) permissible limit. Groundwater exceeding the limit of 300 mg/L is considered very hard. The sampled groundwater is classified based on McCarly and Sawyer (1967). The classification is shown in Table 4.28 to 4.30. Table 4. 28: Classification of Total hardness concentration in the Boreholes drilled in 2013 and 2014 to 2015{After McCarly and Sawyer (1967)} Concentration as Water Type 2013 (n=30) 2014 -2015 (n=18) CaCO3(mg/L) 0 - 75 Soft 5 13 75 - 150 Moderately Hard 20 1 150-300 Hard 5 4 >300 Very Hard Table 4. 29: Classification of Total hardness concentration in the groundwater sampled in 2016 {After McCarly and Sawyer. (1967)} Concentration as Water Type Hand dug wells (n=36) Boreholes (n=44) CaCO3 (mg/L) 0 - 75 Soft 25 33 75 - 150 Moderately Hard 10 10 150-300 Hard 1 1 >300 Very Hard Table 4. 30: Classification of Total hardness concentration in the groundwater sampled in 2017 {After McCarly and Sawyer. (1967)} Concentration as CaCO3 Water Type Hand dug wells (n=30) Boreholes (n=53) (mg/L) 0 - 75 Soft 16 44 75 - 150 Moderately Hard 9 8 150-300 Hard 5 1 >300 Very Hard 157 University of Ghana http://ugspace.ug.edu.gh Out of 30 boreholes drilled in 2013 and 18 boreholes drilled from 2014 to 2015, 5 and 13 boreholes are soft water (Table 4.28), respectively, 20 and 1 borehole are moderately hard water, respectively and 5 and 4 boreholes produce hard water, respectively. In 2016, 25 hand dug wells and 33 boreholes produce soft water (Table 4.29). Also 10 hand dug wells and 10 boreholes produce moderately hardwater and one hand dug well and a borehole produces hard water (Table 4.29). In 2017, 16 hand dug wells and 44 boreholes gives soft water. 9 hand dug wells and 8 boreholes produces moderately hardwater and the water for 5 hand dug wells and a borehole gives hard water (Table 4.30) The moderately hard to hard water produced by fewer hand dug wells and boreholes might be coming from the dissolution of carbonate minerals and weathering of silicate minerals from the aquifer of the Apollonian formation and Birimian supergroup. From Table 4.23, the minimum and maximum sodium (Na+) concentrations (Na+ = 3.40 mg/L and 162 mg/L) in the boreholes drilled from 2014 to 2015 is measured at Ehoaka and Newtown respectively. Both boreholes are in the aquifer of the Apollonian formation. Also, in 2016, the minimum Na+ content (Na+ = 5.20 mg/L) is measured in a hand dug well sampled at Ampaim in the aquifer of the Apollonian formation and the maximum (Na+ = 125.10 mg/L) is measured in a hand dug well sampled at Nkroful in the aquifer of the Birimian Supergroup. For the 2016 borehole samples, the least sodium concentration (Na+ = 3.78 mg/L) (Table 4.25) is measured for a borehole sampled at New Nzulezo, in the aquifer of the Apollonian formation and the highest is recorded (Na+ = 86.30 mg/L) for a borehole sampled at Aluku in the aquifer of the Birimian supergroup. 158 University of Ghana http://ugspace.ug.edu.gh In 2017 (Table 4.26), the minimum Na+ concentration (Na+ = 5.94 mg/L) is measured in a hand dug well sampled at Gyegyekrom in the aquifer of the Birimian Supergroup and the maximum (Na+ = 110.20 mg/L) is recorded in a hand dug well sampled at Nkroful also in the aquifer of the Apollonian formation. In that same year, the minimum and maximum sodium concentration (Na+ = 3.58 mg/L and 85.67 mg/L) (Table 4.27) is recorded in boreholes sampled at Tiekobo 1 and Esiama, respectively. Both boreholes are in the aquifer of the Apollonian formations. Looking at the spatial distribution map (Fig 4.15), it is seen that high sodium content represented by shades of red colour are mostly seen in the aquifer of the Apollonian formation with few representations in the aquifer of the Birimian Supergroup. The sources of elevated sodium are attributed to the weathering of silicate minerals like plagioclase and hornblende {Freeze and Cherry (1979)}, which exist in the underlying geology of the study area. Additionally, ion exchange processes {Apello and Postma, 1999; Zereg et al., (2018)} is another factor behind the elevated Na+ in the groundwater but will be explained further in the third specific objective. In general, the sodium content in the entire groundwater samples is below WHO (2011) permissible limit of 200 mg/L for drinking water. 159 University of Ghana http://ugspace.ug.edu.gh Figure 4. 15: Spatial distribution map of sodium concentration in groundwater in the Lower Tano River Basin The potassium (K+) content, in the boreholes drilled from 2014 to 2015 (Table 4.23), recorded the minimum and maximum K+ concentrations (K+= 0.2 mg/L and 14.60 mg/L) in boreholes drilled at Allengenzule and Newtown, respectively. Both boreholes are in the aquifer of Apollonian formation. In 2016, the minimum and maximum potassium (Table 4.24), concentrations (K+= 0.32 mg/L and 81.61 mg/L) are recorded in hand dug wells sampled at Gyegyekrom and Elubo, respectively. Both hand dug wells are in the aquifer of the Birimian Supergroup. Likewise, in 2016 the minimum K+ concentration (K+= 0.23 mg/L) is measured (Table 4.25) in a borehole sampled at Salman in the aquifer of the Birimian Supergroup and the maximum potassium content (K+ = 17.07 mg/L) is measured in a borehole sampled at Nyanzinli in the aquifer of the Apollonian formation. 160 University of Ghana http://ugspace.ug.edu.gh In 2017, the minimum and maximum potassium content (0.66 mg/L and 39.72 mg/L) (Table 4.26) is measured in hand dug wells sampled at Nkroful in the aquifer of the Birimian Supergroup. Also, in that same year, the minimum potassium concentration (K+= 0.19 mg/L) is measured in a borehole (Table 4.27) sampled at Salman in the aquifer of the Birimian Supergroup and the maximum potassium concentrations (K+= 36.5 9 mg/L) is measured in a borehole sampled at Esiama in the aquifer of the Apollonian formation. The spatial distribution map of potassium (Fig 4.16) reveals high potassium (> 12 mg/L) values in groundwater sampled from the aquifer of the Apollonian formation (Southern and southwestern) with few sampled from the aquifer of the Birimian (Northwestern zone of the study catchment) Supergroup. The elevated potassium content is represented by shades of red and orange colour. Potassium is known to be very low in groundwater (Apello & Postma, 2005) but the high recorded potassium concentrations might probably be derived from the weathering of silicate minerals (biotite, muscovite, hornblende etc.) from the underlying geology. Another source of elevated potassium in the groundwater is linked to anthropogenic sources and one such source is the application of KCl (Potassium chloride) fertilizer by coconut farmers in the study area. Another anthropogenic source might be from domestic wastewater and sewage water disposal (Skowron et al., 2018) which was evidenced during sampling. Also, most houses had no proper drainage systems and toilet facilities. Additional contributing factor for the elevated potassium content is cation-exchange processes (Drever, 1988). Clay minerals and limestones exist in the underlying geology of the study area (Fig 3.3 and 3.4) and these minerals are appropriate cation-exchange sites (Appelo & Postma, 2005). 161 University of Ghana http://ugspace.ug.edu.gh Figure 4.16: Spatial distribution map of K+ concentration in groundwater in the Lower Tano River Basin. In 2013 borehole samples (Table 4.22), the minimum and maximum chloride value (Cl = 0.04 mg/L and 96 mg/L) is recorded in boreholes drilled at Nyamebekyere and Kutukrom, all in the aquifer of the Birimian Supergroup, respectively. In 2014 and 2015, the minimum and maximum concentrations of chloride (Cl = 5.5 mg/L and 224 mg/L) (Table 4.23) is recorded in two separate boreholes drilled at Ehoaka and Newtown, respectively. Both boreholes are in the aquifer of the Apollonian formation. In 2016, the minimum chloride concentration (Cl= 6 mg/L) is recorded for a hand dug well sampled at Gyegyekrom in the aquifer of the Birimian Supergroup and the maximum (Cl = 171.95 mg/L) (Table 4.24) is recorded for a hand dug well sampled at Ankobra in the aquifer of the Apollonian formation. In 2016, the minimum chloride content (Cl= 4 mg/L) (Table 4.25) is measured in a borehole sampled at Tiekobo no1 in the aquifer of the Apollonian formation and Salman, in the aquifer 162 University of Ghana http://ugspace.ug.edu.gh of the Birimian Supergroup. The maximum Cl concentration (Cl= 83.97 mg/L) is recorded in a borehole sampled at New Nzulezo in the aquifer of the Apollonian formation. In 2017, the minimum chloride content (Cl = 4 mg/L) is measured in hand dug wells sampled at Asemda, Ampaim, Atuabo and Gyegyekrom (Table 4.26). These towns are in the aquifer of the Apollonian formation, except for Gyegyekrom, which is in the aquifer of the Birimian Supergroup. Likewise, the maximum chloride concentration (Cl = 133.96 mg/L) is measured in a hand dug well sampled at Elubo in the aquifer of the Birimian Supergroup. For the borehole samples, the minimum Cl- concentration (Cl = 2.00 mg/L) is measured in a borehole sampled at New Nzulezu and the maximum (Cl = 89.97 mg/L) is recorded in a borehole sampled at Esiama. Both boreholes are in the aquifer of the Apollonian formation. The spatial distribution map of chloride is illustrated in Figure 4.17. From the map, the highest chloride values represented by shades of red colour are seen mostly in groundwater sampled from the aquifer of the Apollonian formation (some parts of the coastal area) with few groundwater sampled from the aquifer of the Birimian Supergroup (some parts of the NE and NW). All the sampled groundwater within the basin is below WHO (2011) permissible limit of 250 mg/L for drinking water. Normally, chloride is not a significant component in the underlying rock formation of the study area (Fig 3.3 and 3.4). Therefore, chloride will only be present in minimal quantity in the groundwater through possible organic matter decomposition in the soil, ion exchange processes, and atmospheric sources (Freeze & Cherry, 1979). 163 University of Ghana http://ugspace.ug.edu.gh Figure 4. 17: Spatial distribution map of Chloride concentrations in groundwater in the Lower Tano River basin. For the boreholes drilled from 2014 to 2015, the minimum (HCO -3 = 5 mg/L) and maximum (HCO -3 = 171 mg/L) bicarbonates levels (Table 4.23) is recorded for boreholes drilled at Elloyin and Kamgbunli, respectively. Both boreholes are drilled in the aquifer of the Apollonian formation. In 2016, the minimum and maximum bicarbonate concentration (HCO -3 = 4.88 mg/L and 170.69 mg/L) is measured (Table 4.24) in hand dug wells sampled from Ampaim and Asanta, respectively. Both towns are underlain by the Apollonian formation. Also, for the borehole samples the minimum (HCO - 3 = 2.44 mg/L) and maximum (HCO - 3 = 182.88 mg/L) bicarbonates content (Table 4.25) is measured in boreholes sampled from Salman in the aquifer of the Birimian Supergroup. In the same way, the minimum bicarbonate concentration (HCO - 3 = 2.44 mg/L) for 2017 hand dug well samples is measured in a hand dug well sampled at Elubo in the aquifer of the Birimian Supergroup and the maximum (HCO -3 = 353.56 mg/L) is recorded for a hand dug well sampled 164 University of Ghana http://ugspace.ug.edu.gh at Esiama in the aquifer of the Apollonian formation. Also, for the 2017 boreholes samples, the minimum bicarbonate concentration (HCO -3 = 2.44 mg/L) is recorded for a borehole sampled at Atwinbanso in the aquifer of the Apollonian formation and the maximum concentration (HCO -3 = 219.45 mg/L) (Table 4.27) is recorded for a borehole sampled at Salman in the aquifer of the Birimian Supergroup. The spatial distribution map of bicarbonate concentrations in groundwater within the study area (Fig 4.18) shows high bicarbonate content in groundwater sampled from the aquifer of the Birimian Supergroup (Southeastern Zone). The high bicarbonate content is represented by shades of red colour. There is fewer representation of elevated bicarbonate concentration in groundwater sampled from the aquifer of the Apollonian formation (coastal). The groundwater with elevated bicarbonate concentration in the aquifer of the Birimian Supergroup and the Apollonian formation is attributed to the dissolution of carbonate minerals and weathering of silicate minerals (Stumm and Morgan 1996) from the underlying geology of the study area. In general, the bicarbonate content in the groundwater is all below WHO (2011) permissible limit of 500 mg/L for drinking water. 165 University of Ghana http://ugspace.ug.edu.gh Figure 4. 18: Spatial distribution map of bicarbonate content in groundwater in the Lower Tano River Basin. The sulphate levels in the groundwater sampled from 2013 to 2017 are all below WHO (2011) permissible limit of 250 mg/L for drinking water. The spatial distribution map (Fig 4.19) of sulphate in the sampled groundwater shows slightly high sulphate (>80 mg/L) values represented by shades of red colour taken from the aquifer of the Apollonian formation with fewer representations sampled from the aquifer of the Birimian Supergroup. According to Berner and Berner (1987), sulphate ion concentration in natural water must 4 4 generally be in the range of 2 mg/L to 80 mg/L. However, in the study area, some groundwater in the aquifer of the Apollonian formation (Fig 4.19) and the Birimian Supergroup were greater than 80 mg/L. The high sulphate values measured in the groundwater may possibly be attributed to anthropogenic and geogenic sources. To confirm the possible sources being geogenic, Fe/SO 2 -4 molar ratio for groundwater is calculated. The results from the calculations (Appendix 21 to 26) show that a hand dug well sampled from Nkroful in the aquifer of the Birimian Supergroup fall under the stoichiometry of pyrite oxidation. The rest of the groundwater samples did not satisfy the Fe /SO 2-4 molar ratios of 0.5 and 1.0 for the 166 University of Ghana http://ugspace.ug.edu.gh stoichiometry of pyrite oxidation, respectively. This reveals that pyrite oxidation is probably not responsible for the mass production of sulphate (Stumm & Morgan, 1981) in the groundwater sampled from the aquifer of the Apollonian formation and the Birimian supergroup. of the study area. In the study area, farming is not done on a large scale, hence, ammonium sulphate fertilizer might not be applied ruling out ammonium sulphate fertilizers as a possibly anthropogenic contributor to the elevated sulphate content measured in the groundwater. In the study catchment legal and illegal small-scale mining are rampant. Hence, in the processes of gold, these miners use sulphuric acid. The use of sulphuric acid will possibly lead to acid-mine drainage. The acid-mine drainage may not eliminate the sulphate ion leading to elevated sulphate ion content in some of the groundwater. This must be investigated further using isotopes of sulphide-34 and oxygen-18. Figure 4. 19: Spatial distribution map of sulphate concentration in groundwater in the Lower Tano River Basin. 167 University of Ghana http://ugspace.ug.edu.gh For the boreholes drilled in 2013 (Table 4.21), the minimum and maximum nitrate concentration (NO -3 = 0.54 mg/L and 2.31 mg/L) is measured in a borehole drilled at Asanta and Ellonye, respectively. Both boreholes are in the aquifer of the Apollonian formation. In 2016, the minimum nitrate concentration (NO -3 = 0.27 mg/L) is measured in a hand dug well sampled in Aniwa and the maximum value (NO -3 = 11.06 mg/L) is measured in a hand dug well sampled at Elubo. Both hand dug wells are in the aquifer of the Birimian Supergroup. Also in that same year, the minimum nitrate concentrations (NO -3 = 0.29 mg/L) are measured in boreholes sampled at Kamgbunli, Sawoman, Aluku and Nyanzinli and the maximum nitrate content is recorded in a borehole (NO -3 = 4.60 mg/L) sampled at New Nzulezu. All these boreholes are in the aquifer of the Apollonian formation except a borehole sampled at Aluku which is in the aquifer of the Birimian Supergroup. Equally, in 2017, the minimum concentration of nitrate (NO - 3 = 0.28 mg/L) is measured in a hand dug well sampled at Esiama in the aquifer of the Apollonian formation and the maximum (NO - 3 = 3.60 mg/L) is recorded in a hand dug well sampled at Elubo in the aquifer of the Birimian Supergroup. For the borehole samples, the minimum and maximum nitrate - concentration ( NO3 = 0 .05 mg/L and 4.06 mg/L) is measured in boreholes sampled at Ampaim and Ngelekyi, respectively. Both boreholes are in the aquifer of the Apollonian formation. From the spatial distribution map of nitrate (Fig 4.20), it is observed that all the groundwater sampled in the study area are below the WHO (2011) permissible limit of 50 mg/L. The low nitrate content in the groundwater is possibly attributed to less vigorous anthropogenic activities. 168 University of Ghana http://ugspace.ug.edu.gh Figure 4. 20: Spatial distribution map of nitrate content in groundwater in the Lower Tano River Basin. Based on the medians (Table 4.21 to 4.27), the cation and anion concentrations in the groundwater is in the order: 2+ 2+ Ca > Mg and Cl - > SO 2-4 > NO - 3 (Boreholes drilled in 2013). 2+ g2+Ca > M > Na+ > K+ and Cl-> SO 2-> HCO - 4 3 > NO - 3 (Boreholes drilled in 2014 to 2015). Na+ > Ca2+ > K+ > Mg2+ and SO 2- > Cl-4 > HCO - 4 3 > NO -3 (Hand dug well sampled in 2016) Na+ > Ca2+ > Mg2+ > K+ and SO 2- 4 > HCO - 3 > Cl - > NO - 3 (Boreholes sampled in 2016). Na+ > Ca2+ > Mg2+ > K+ and HCO - >. Cl- 3 > SO 2- 4 > NO - 3 (Hand dug wells sampled in 2017). + 2+ 2+ + and HCO - > Cl- > SO 2- - Na > Ca > Mg > K 3 4 > NO3 (Boreholes sampled in 2017). 169 University of Ghana http://ugspace.ug.edu.gh The rivers and streams sampled in 2016 had Na+ as the dominant cation and SO 2-4 as the dominant anion. In the same way, the hand dug wells and the boreholes sampled in 2016 had Na+ as the dominant cation and SO 2-4 as the dominant anion. These samples were taken during the wet seasons. The rivers, streams, hand dug wells and boreholes sampled in 2017 had Na+ as the dominant cation and HCO -3 as the dominant anion. These samples were taken during the dry seasons. Also, a hydraulic relationship existed between the streams sampled in 2016 and the boreholes sampled in 2016 and this is due to their similar trends which will be explained further in the fourth specific objective. Also, a relationship existed between the hand dug wells and the boreholes sampled in 2017. The variation of cations and anions in the sampled groundwater is attributed to the seasons in which the samples were taken, the time, lithology, and human activities. 4.2.2.3 Occurrences and Distribution of Trace Elements in Groundwater of the Lower Tano River Basin (Assessment of groundwater contamination) Under this section, the results for the measured trace elements in the groundwater is discussed. Statistical comparison for trace elements including minimum, maximum, median, mean, standard deviation etc. in the groundwater samples are presented in Table 4.31,4.32,4.33,4.34,4.35 and 4.36. 170 University of Ghana http://ugspace.ug.edu.gh Table 4. 31: Descriptive statistical summary of trace elements in the Boreholes drilled in 2013 Parameters Cu (mg/L) Mn(mg/L) Fe(mg/L) Cr(mg/L) Pb(mg/L) As(mg/L) Al(mg/L) Zn(mg/L) Number of samples 30 30 30 30 30 30 30 30 Mean 0.002 0.028 0.108 0.008 0.000 0.000 0.004 0.004 Standard Error 0.001 0.008 0.030 0.008 0.000 0.000 0.002 0.002 Median 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Mode 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Standard Deviation 0.006 0.045 0.166 0.042 0.000 0.000 0.011 0.009 Sample Variance 0.000 0.002 0.028 0.002 0 .000 0 .000 0.000 0.000 Kurtosis 14.922 0.684 0.209 30.000 22.217 4.822 Skewness 3.913 1.460 1.276 5.477 4.514 2.375 Minimum 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Maximum 0.030 0.140 0.520 0.230 0.000 0.000 0.060 0.030 Sum 0.050 0.830 3.240 0.230 0.000 0.000 0.110 0.110 Count 30.000 30.000 30.000 30.000 30.000 29.000 29.000 29.000 Confidence Level (95.0%) 0.002 0.017 0.062 0.016 0.000 0.000 0.004 0.003 Table 4. 32: Descriptive statistical summary of trace elements in the Boreholes drilled from 2014 to 2015 Parameters Co(mg/L) Cu(mg/L) Pb(mg/L) Cd(mg/L) Cr (mg/L) Mn(mg/L) Ni(mg/L) Zn(mg/L) Al(mg/L) Fe(mg/L) As(mg/L) Number of samples 18 18 18 18 18 18 18 18 18 18 18 Mean 0.002 0.019 0.068 0.000 0.004 0.057 0.006 0.069 0.358 0.578 0.008 Standard Error 0.001 0.014 0.011 0.000 0.001 0.017 0.003 0.003 0.171 0.277 0.005 Median 0.001 0.001 0.054 0.000 0.002 0.028 0.003 0.066 0.130 0.250 0.001 Mode 0.000 0.000 0.049 0.000 0.002 0.028 0.002 0.059 0.110 0.300 0.001 Standard Deviation 0.004 0.060 0.045 0.000 0.005 0.072 0.011 0.013 0.725 1.174 0.021 Sample Variance 0.000 0.004 0.002 0.000 0.000 0.005 0.000 0.000 0.525 1.377 0.000 Kurtosis 2.119 14.436 -0.915 -0.736 8.824 4.361 8.576 -0.901 16.230 13.413 12.731 Skewness 1.825 3.736 0.672 1.121 2.792 2.150 2.910 -0.001 3.957 3.572 3.504 Minimum 0.000 0.000 0.010 0.000 0.000 0.005 0.000 0.044 0.050 0.000 0.000 Maximum 0.013 0.250 0.150 0.001 0.020 0.270 0.045 0.090 3.200 5.000 0.087 Sum 0.044 0.350 1.221 0.004 0.067 1.029 0.115 1.235 6.450 10.400 0.149 Confidence Level (95.0%) 0.002 0.030 0.022 0.000 0.002 0.036 0.006 0.007 0.360 0.584 0.011 171 University of Ghana http://ugspace.ug.edu.gh Table 4. 33: Descriptive statistical summary of trace elements for Hand dug wells sampled in 2016. Parameters Al Cr Mn Fe Co Ni Cu Zn As Cd Pb mg/L) (mg/L) (mg/L)) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) Number of samples 35.00 35.000 35.00 35.00 35.00 35.00 35.00 35.00 35.00 35.00 36.00 Mean 0.065 0.030 0.048 0.642 0.000 0.002 0.005 0.812 0.007 0.007 0.96 Standard Error 0.017 0.026 0.021 0.252 0.000 0.000 0.003 0.779 0.006 0.003 0.53 Median 0.032 0.002 0.010 0.273 0.000 0.001 0.000 0.019 0.000 0.000 0.00 Mode N/A N/A 0.000 N/A 0.000 0.000 0.000 N/A 0.000 0.000 0.00 Standard Deviation 0.102 0.155 0.124 1.488 0.001 0.002 0.016 4.672 0.035 0.020 3.19 Sample Variance 0.010 0.024 0.015 2.215 0.000 0.000 0.000 21.832 0.001 0.000 10.17 Kurtosis 14.424 34.471 13.931 27.682 32.878 7.348 17.863 35.996 35.682 17.140 17.48 Skewness 3.484 5.854 3.726 5.094 5.639 2.452 4.229 5.999 5.962 4.061 4.14 Minimum 0.004 0.0004 BDL 0.013 BDL BDL BDL 0.0002 BDL BDL BDL Maximum 0.545 0.917 0.594 8.743 0.006 0.011 0.080 28.067 0.213 0.105 16.30 Sum 2.281 1.060 1.677 22.455 0.009 0.057 0.171 29.229 0.247 0.253 34.67 Confidence Level (95.0%) 0.035 0.053 0.042 0.511 0.000 0.001 0.005 1.581 0.012 0.007 1.08 Table 4. 34: Descriptive statistical summary of trace elements for Boreholes sampled in 2016. Parameters Al Cr Mn Fe Co Ni Cu Zn As Cd Pb (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) Number of samples 44 44 44 44 44 44 44 44 45 44 44 Mean 0.08 0.00 0.78 2.94 0.00 0.02 0.05 0.41 0.00 0.001 0.46 Standard Error 0.02 0.00 0.69 1.42 0.00 0.01 0.03 0.33 0.00 0.000 0.16 Median 0.01 0.00 0.04 0.17 0.00 0.00 0.00 0.04 0.00 0.000 0.00 Mode N/A 0.00 0.00 0.00 0.00 0.00 0.00 N/A 0.00 0.000 0.00 Standard Deviation 0.15 0.00 4.60 9.42 0.01 0.08 0.19 2.22 0.00 0.002 1.05 Sample Variance 0.02 0.00 21.14 88.76 0.00 0.01 0.04 4.93 0.00 0.000 1.10 Kurtosis 9.45 -0.07 43.90 17.95 34.89 43.04 36.85 43.74 7.96 11.840 6.30 Skewness 2.94 0.98 6.62 4.29 5.71 6.53 5.91 6.60 2.91 3.339 2.63 Minimum BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL Maximum 0.76 0.01 30.57 47.42 0.08 0.53 1.23 14.78 0.01 0.012 4.25 Sum 3.39 0.06 34.52 129.49 0.14 0.76 2.07 18.20 0.03 0.038 20.15 Confidence Level (95.0%) 0.05 0.00 1.40 2.86 0.00 0.02 0.06 0.67 0.00 0.001 0.32 172 University of Ghana http://ugspace.ug.edu.gh Table 4. 35: Descriptive statistical summary of trace elements for Hand dug wells sampled in 2017. Parameters Al Cr Mn Fe Co Ni Cu Zn As Cd Pb (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) Number of samples 30 30 30 30 30 30 30 30 30 30 30 Mean 0.128 0.001 0.009 0.158 0.000 0.001 0.002 0.018 0.001 0.0005 0.035 Standard Error 0.089 0.000 0.004 0.033 0.000 0.000 0.000 0.004 0.000 0.000 0.006 Median 0.005 0.001 0.001 0.101 0.000 0.001 0.002 0.008 0.001 0.000 0.026 Mode N/A N/A 0.000 0.000 N/A N/A N/A N/A N/A N/A N/A Standard Deviation 0.485 0.001 0.020 0.155 0.000 0.001 0.001 0.024 0.001 0.001 0.032 Sample Variance 0.235 0.000 0.000 0.024 0.000 0.000 0.000 0.001 0.000 0.000 0.001 Kurtosis 20.848 0.646 11.147 1.696 7.077 0.317 0.543 9.235 5.544 9.328 0.462 Skewness 4.483 1.015 3.186 1.250 2.702 0.943 0.858 2.801 1.921 3.050 1.173 Range 2.484 0.004 0.092 0.605 0.002 0.003 0.006 0.118 0.004 0.004 0.114 Minimum BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL BDL Maximum 2.484 0.004 0.09 0.605 0.002 0.003 0.006 0.118 0.004 0.004 0.114 Sum 3.838 0.042 0.261 3.480 0.009 0.038 0.070 0.550 0.035 0.015 1.055 Confidence Level(95.0%) 0.181 0.000 0.007 0.069 0.000 0.000 0.001 0.009 0.000 0.000 0.012 BDL = Below detection limit (<0.001>) Table 4. 36: Descriptive statistical summary of trace elements for Boreholes sampled in 2017. Parameters Al Cr Mn Fe Co Ni Cu Zn As Cd Pb (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) Number of samples 55 55 55 55 55 55 55 55 55 55 55 Mean 0.053 0.001 0.069 0.087 0.001 0.004 0.027 0.052 0.002 0.002 0.003 Standard Error 0.018 0.000 0.016 0.012 0.000 0.001 0.015 0.015 0.001 0.001 0.001 Median 0.003 0.001 0.013 0.067 0.000 0.002 0.002 0.021 0.001 0.000 0.000 Mode 0.001 0.001 0.471 0.038 0.006 0.011 0.004 0.013 0.003 0.000 0.000 Standard Deviation 0.133 0.001 0.117 0.069 0.002 0.008 0.110 0.113 0.005 0.009 0.005 Sample Variance 0.018 0.000 0.014 0.005 0.000 0.000 0.012 0.013 0.000 0.000 0.000 Kurtosis 13.573 4.559 4.451 0.265 5.891 16.048 40.775 20.882 24.307 50.209 10.462 Skewness 3.560 1.901 2.233 0.809 2.532 3.757 6.149 4.331 4.891 6.970 2.909 Minimum 0.0002 0.0001 0.0003 0.004 0.00003 0.0004 0.001 0.002 0.0004 0.00002 0.00003 Maximum 0.715 0.005 0.471 0.277 0.008 0.046 0.772 0.690 0.031 0.069 0.026 Sum 2.919 0.064 3.791 3.028 0.056 0.242 1.504 2.834 0.135 0.108 0.147 Confidence Level (95.0%) 0.036 0.000 0.032 0.024 0.001 0.002 0.030 0.030 0.001 0.003 0.001 173 University of Ghana http://ugspace.ug.edu.gh 4.2.2.4 Metallic elements (Cu, Cd, Zn, Fe, and Cr) The measured Copper (Cu) content in the boreholes drilled in 2013 (Table 4.31) varies from 0.00001 mg/L to 0.03 mg/L with a mean of 0.002 mg/L. For the boreholes drilled from 2014 to 2015 (Table 4.32), the Cu content ranges from 0.00001 mg/L to 0.25 mg/L with an average of 0.019 mg/L. In 2016, the Cu content in the hand dug wells and boreholes varies from below detection limit (BDL) to 0.08 mg/L with a mean of 0.05 mg/L, and from below detection limit (BDL) to 1.23 mg/L with an average of 0.005 mg/L, respectively (Table 4.33 and 4.34). In 2017, the Cu content for both hand dug wells and boreholes ranges from BDL to 0.01 mg/L with a mean of 0.02 mg/L and from 0.001 mg/L to 0.77 mg/L with a mean of 0.027 mg/L, respectively (Table 4.35 and 4.36). The spatial distribution map of copper for the sampled groundwater shows that few of the groundwater represented by shades of red and orange colour (Fig 4.21) are above WHO (2011) permissible limit of 0.05 mg/L for drinking water. This groundwater was mostly sampled from the aquifer of the Birimian Supergroup with few samples taken from the aquifer of the Apollonian formation. The sources of the elevated copper content are linked to the oxidation of sulphide minerals {chalcopyrite (CuFeS2)} from the underlying geology of the study area (Luebe et al., 1990; Adjimah et al., 1993). Another possible factor responsible for the high Cu content in groundwater sampled from the aquifer of the Apollonian formation and the Birimian supergroup might possibly be from anthropogenic sources. Examples of such sources are mining activities, application of sewage sludge, fungicides, fertilizers in agricultural application and waste emission (Flemming & Trevors, 1989). In the study catchment, illegal and legal small-scale mining activities is rampant and studies carried out by Kabata-Pendias, 2001, indicated that catchments with extensive mining activities have Cu content in soils to be as high as 2000 mg/kg. Cocoa farming are rampant in the upper parts of the study area and it is likely that the cocoa farmers use Cu containing fungicides to control mildew on their farms but further studies must be carried out. Also, studies carried out by Addo-Fordjour et al. (2013) indicates that cocoa farmers in Ghana uses copper-based fungicide on their farms. Hence, the 174 University of Ghana http://ugspace.ug.edu.gh application of Cu fungicides might probably lead to Cu accumulation in soils and through natural processes like rainfall and runoffs, Cu might leach into the aquifers leading to elevated Cu content in groundwater. Since Cu in soils was not measured in this study, the impact of Cu fungicides applications on groundwater in the Lower Tano River Basin must be investigated in future. Figure 4. 21: Spatial distribution map of copper (Cu) content in groundwater in the study catchment. The Cadmium (Cd) content in boreholes drilled from 2014 to 2015 varies from 0 to 0.001 mg/L with an average of 0.0002 mg/L. All the newly drilled boreholes are below WHO (2011) permissible limit of 0.003 mg/L for drinking water. 175 University of Ghana http://ugspace.ug.edu.gh For the hand dug wells sampled in 2016, the Cd content ranges from below detection limit (BDL <0.001>) to 0.11 mg/L with a mean of 0.007 mg/L. 21.6% of the hand dug wells (n= 35) are lower than WHO (2011) permissible limit of 0.003 mg/L and the remaining 78.4% are above the permissible limit. For the boreholes sampled in 2016, the Cd content varies from below detection limit (BDL<0.001) to 0.01 mg/L with an average of 0.001 mg/L. 11.1% of the boreholes (n= 44) exceeded WHO (2011) permissible limits for drinking water. In 2017, the Cd concentrations in the sampled hand dug wells varies from below detection limit (BDL<0.001) to 0.004 mg/L with a mean of 0.0005 mg/L. All the hand dug wells are below WHO (2011) permissible limit of 0.003 mg/L except a hand dug well sampled at Elubo in the aquifer of the Birimian super group. In addition, the Cd content in the boreholes sampled in 2017 ranges from 0.00002 to 0.07 mg/L with a mean of 0.002 mg/L. Cd content in boreholes sampled at Tiekobo number 1, Bonyere and Atwinbanso all in the aquifer of the Apollonian formation exceeded the WHO (2011) permissible limit of 0.003 mg/L. Spatial distribution map of Cd (Fig 4.22) shows that groundwater samples with elevated Cd content represented by shades of red colour are dominant in the aquifer of the Birimian supergroup with few representations in the aquifer of the Apollonian formation. These elevated Cd values might possibly be derived from anthropogenic factors probably from effluent discharge from mining activities finding their way into the aquifers through natural processes like rainfall. Common sources of cadmium involve the disposal of cadmium containing wastes, plating operation, corrosion of galvanized pipes, discharge from metal refineries, erosion of natural deposits and runoff from paints and waste batteries (Smith et al., 1995). In the study catchment, the above factors are rare except “erosion of natural deposits, discharge from metal refineries like the mining industries and corrosion of galvanized fitting used in the construction of boreholes”. These three might be the probable sources through which cadmium could be released in significant quantities into the groundwater, especially the hand dug wells since it is exposed. Nevertheless, since there are no previous cadmium data on rocks, soil, surface 176 University of Ghana http://ugspace.ug.edu.gh water, and groundwater and this study did not measure Cd in soils and rocks, further studies must be carried out to define the actual sources of high Cd groundwater within the Lower Tano River Basin. Also, the elevated Cd content in the groundwater might possibly be geogenic. Liu et al. (2017), stated that “marine primary production of shale might increase the Cd content in groundwater. Looking at the underlying geology of the zones represented by shades of red (Fig. 3.3 and 3.4), the aquifer of the Apollonian formation contains shale and that might probably dissolve in the groundwater releasing Cd but further investigations is required. According to ATSDR, 2012 and UNEP, 2010, “anthropogenic sources of cadmium are fossil fuel combustion, phosphate fertilizer manufacturing, iron production, cement production, steel production, road dust, municipal and sewage sludge incineration, and emissions from non-ferrous metal production. From the above given factors, it is likely that the Cd content in groundwater sampled from the aquifer of the Apollonian formation is possibly from the production of cement since there is a cement production company at Nawulley and Half Assini. In addition, there is a municipal sewage sludge incineration at Old Kablazuazo and the town is underlain by the rocks of the Apollonian formation. Figure 4. 22: Spatial distribution map of Cd concentrations in groundwater drawn in the Lower Tano River Basin. 177 University of Ghana http://ugspace.ug.edu.gh The concentration of Zinc (Zn) in the boreholes drilled in 2013 varies from 0.00001 m/L to 0.03 m/L with a mean of 0.004 mg/L. That of the boreholes drilled from 2014 to 2015 had a Zn content varying from 0.04 mg/L to 0.09 mg/L with a mean of 0.069 mg/L. In 2016, the Zn content in the hand dug wells and the boreholes varies from 0.0002 mg/L to 28.07 mg/L with a mean of 0.81 mg/L, and from below detection limit (BDL <0.001) to 14.78 mg/L with an average of 0.41 mg/L, respectively. In 2017, the Zn content in the hand dug wells varies from BDL to 0.12 mg/L with a mean of 0.02 mg/L. That of the boreholes varies from 0.002 mg/L to 0.69 mg/L with an average of 0.05 mg/L. All the hand dug wells sampled in both 2016 and 2017 are below WHO (2011) permissible limit of 5 mg/L, except for a hand dug well sampled at Elubo in the aquifer of the Birimian Supergroup. For the boreholes, all the samples are below the WHO (2011) permissible limits of 5 mg/L, except for a borehole sampled at Salman also in the aquifer of the Birimian supergroup. At Salman, virtually all the gold mining industries as well as illegal small-scale mining activities are concentrated in and around the town. In areas underlain by the Birimian supergroup rocks, Luebe et al. (1990) and Adjimah et al. (1993) discovered sulphide minerals (pyrites, chalcopyrite’s) hosting trace elements like Cu, Pb, As, Zn, Ni etc. as pathfinder element for the exploration of gold. It is therefore possible that the oxidation of these sulphide minerals from the aquifer of the Birimian supergroup might release Zn as a secondary mineral into the groundwater elevating the Zn content. The spatial distribution map of Zinc in groundwater within the basin is presented in figure 4.23. 178 University of Ghana http://ugspace.ug.edu.gh Figure 4. 23: Spatial distribution map of Zn content in groundwater in the Lower Tano River Basin. The chromium (Cr) concentration for the boreholes drilled in 2013 varies from 0.00001 to 0.23 m/L with a mean of 0.008 m/L. That of the boreholes drilled from 2014 to 2015 ranges from 0.00001 to 0.02 m/L with an average of 0.004 mg/L. In 2016, the Cr in the sampled hand dug wells varies from 0.0004 mg/L to 0.92 mg/L with an average of 0.03 mg/L. That of Cr in the sampled boreholes varies from BDL to 0.01 mg/L with a mean of 0.001 mg/L. In 2017, Cr in the sampled hand dug wells and boreholes varied from BDL to 0.004 mg/L with a mean of 0.001 mg/L and from 0.0001 m/L to 0.005 mg/L with an average of 0.001 mg/L, respectively. The Cr content in two hand dug wells (n=36) sampled in 2016 are above the WHO (2011) permissible limit of 0.05 mg/L and the remaining 34 hand dug wells and all the hand dug wells sampled in 2017 are below the WHO permissible limit for drinking water. Likewise, the Cr 179 University of Ghana http://ugspace.ug.edu.gh content in the boreholes sampled in 2013, 2014 to 2015, 2016, and 2017 are all lower than the WHO permissible limit of 0.05 mg/L except for a borehole sampled at Ayisakro in the aquifer of the Birimian Supergroup. From the results, the high Cr content in groundwater sampled at Nkroful, Bomuakpole and Ayisakro, in the aquifer of the Birimian Supergroup is linked to the weathering of ultra-mafic rocks from the underlying geology. Dampare et al. (2008) discovered high Cr content in ultra- mafic rocks of the Birimian superroup. Also, the high Cr values is attributed to anthropogenic sources. This is because the above-mentioned three towns fall within the mining zone and during combustion process at the mining sites, particles emanating from the sites might be distributed into the atmosphere and on the soil. This particle might settle at the bottom of a cell floatation and that could directly be discharged unto the onsite wetlands, thus possibly leaching into the aquifer resulting in an elevated Cr concentration in the groundwater. Since there are no data on the Cr content in soils and rocks of the study area and these two were not sampled in this study, proper geochemical studies just like works undertaken by Izbicki et al. (2008a) should be conducted in future. The concentration of iron (Fe) in the boreholes drilled in 2013 varies from 0.00001 mg/L to 0.52 mg/L with an average of 0.11 mg/L. For the boreholes drilled from 2014 to 2015, the Fe content ranges from 0.00001 mg/L to 5 mg/L with a mean of 0.58 mg/L. For the hand dug wells sampled in 2016, the Fe content varies from 0.01 mg/L to 8.74 mg/L with a mean of 0.64 mg/L. For the boreholes sampled in 2016, the Fe content varies from below detection limit (BDL<0.001) to 47.4 mg/L with a mean of 2.94 mg/L. In 2017 the Fe concentration in the sampled hand dug wells and boreholes varied from BDL to 0.61 mg/L with an average of 0.16 mg/L, and from 0.004 mg/L to 0.28 mg/L with an average of 0.087 mg/L, respectively. The sampled groundwater shows that 40.5% (n=35) of the hand dug wells sampled in 2016 had Fe content lower than the WHO (2011) permissible limit of 0.3 mg/L and the remaining 180 University of Ghana http://ugspace.ug.edu.gh 59.5% are higher than the permissible limits. In 2017, 96.7% of the hand dug wells (n=30) are lower than the WHO permissible limit of 0.3 mg/L and the remaining 3.33% are higher than the permissible limit. For the boreholes, 13.3% (n=30) had Fe values greater than WHO (2011) permissible limit in 2013 and the remaining 86.7% of the boreholes are lower than the permissible limits. 16.7% of the boreholes sampled from 2014 to 2015 are greater than the WHO (2011) permissible limits and the remaining 83.3% are lower than the permissible limits. In 2016 and 2017, the Fe content in 65.9% and all the boreholes (n=55) in both respective years are lower than the WHO (2011) permissible limits and the remaining 34.1% of the boreholes sampled in 2016 are higher than the WHO permissible limit of 0.3 mg/L for drinking water. The high Fe content in most groundwater is attributed to the oxidation or mobilization of sulphide minerals (pyrite, chalco- pyrite etc.) from the underlying geology of the study area (Luebe et al., 1990). Oxidation of sulphide minerals by oxygen through proton production is also a significant sulphate and iron source in groundwater ( Kortatsi, 2004) of the study area. The reaction equation for oxidation of sulphide minerals by oxygen through proton production is given by: FeS2 + O2 + H2O → SO 2- + Fe2+ + H+4 ……………. Eq 4.3 In the presence of ferrous iron, Pyrite is oxidized as: FeS 2+ 2- + 2 + 7/2O2 + H2O = Fe + 2 SO4 + 2H ……… Eq 4.4 Equation 4.3 is the primary rate determining the step of acid drainage formation (Stumm & Morgan, 1981). The development of equations 4.3 and 4.4 depends on the pH of the groundwater. If the pH is higher than 3.0, (as in the case of the study area where the groundwater pH is between 4.5 to 6.8 pH unit), then there is precipitation of ferric hydroxide [Fe (OH)3] and this is given by the equation, Fe 3+ + 3H2O = Fe(OH)3 + 3H+... Eq 4.5. 181 University of Ghana http://ugspace.ug.edu.gh This equation (eq 4.5) gives an idea of possible acid- mine drainage reactions in groundwater (hand dug wells and boreholes) of the study area. This produces iron (III) hydroxide {Fe (OH)3} which is possibly a secondary source of Fe for the basin groundwater. Conversely, if pH of the groundwater is less than 3.0 and Fe3+ is in contact with unoxidized pyrite, then Fe3+ consumed by the oxidation of pyrite due to the strong oxidant of Fe3+. This is presented by the equation, FeS 3+ 2+ 2- +2 + 14Fe + 8H2O = 15Fe + 2SO4 + 16H …. Eq 4.6 The above equations suggests that oxygen is necessary to start the oxidation of pyrite and to recycle Fe2+ to Fe3+ {Stumm & Morgan. (1981)} However, if an accumulation of mine waste products contains high amount of dissolved Fe3+ from the previous oxidation period, then the oxidation of pyrite will continue for a long time even in the absence of oxygen supply. When both precipitation of ferric hydroxide and oxidation of ferrous iron take place, the coupled reaction is described as Fe2+ + ¼ O2 + 5/2 H2O = Fe (OH) + 3 + 2H …Eq 4.7 Ideally, the above reactions produce high sulphate concentrations, low pH and Fe / SO 2-4 molar 4 ratios of 1.0 (for arsenopyrite oxidation) and 0.5 (for pyrite oxidation) (Kortatsi, 2004) Generally, the low sulphate content in the groundwater coupled with the fact that no groundwater satisfied the Fe /SO 2-4 molar of 1.0 and 0.5 for the stoichiometry of arsenopyrite and pyrite respectively (Appendix 21 to 26) suggests the possibility of arsenopyrite and pyrite oxidation processes in groundwater being partially responsible for the concentration of iron in the groundwater of the study area. Another source of elevated Fe in the groundwater is attributed to ferromagnesium mineral like biotite which exist in the underlying geology of the study area. 182 University of Ghana http://ugspace.ug.edu.gh Additional reason accounting for the high Fe concentration in the groundwater might be from the removal of dissolved oxygen by organic matter, leading to reduced conditions. Under reducing conditions, the solubility of Fe-bearing minerals (hornblende, biotite, mica etc.) which exist in the underlying geology increases, leading to enrichment of dissolved iron in the groundwater. Further, the presence of elevated Fe content in the groundwater could possibly be associated with chemical weathering of silicate minerals (hornblende, and plagioclase) which possibly dissolve or percolate through the fractures to enrich the aquifers, (Darko, 2006). Though organic matter content in the soil zone of the groundwater was not measured in this study, the brown colorization of groundwater evidenced during sampling is an indication of a possible presence of organic matter in the soil zone of the study area. Hence, at a comparatively lower pH, higher Fe concentrations in the groundwater might have resulted from organic matter, interaction of oxidized Fe minerals and subsequent dissolution of Fe2CO3. This type of water was clear when first drawn from the hand dug wells and boreholes, but soon became cloudy and changed to brownish by the precipitation of Fe (OH)3. This was a common problem evidenced in most parts of the study region during the sampling campaign. Figure 4.24 presents the spatial distribution map of iron concentration in groundwater within the study area. From the map (Fig 4.24), higher concentrations of iron were seen in the aquifer of the Birimian super group. 183 University of Ghana http://ugspace.ug.edu.gh Figure 4. 24: Spatial distribution map of iron content in groundwater in the study catchment. 4.2.2.5 Transition Metals (Ni, Mn, and Co) For the boreholes drilled from 2014 to 2015, nickel (Ni) content in the boreholes ranges from 0.0001 to 0.05 mg/L with a mean of 0.006 mg/L. In 2016, the Ni content in the sampled hand dug wells and boreholes varies from BDL to 0.01 mg/L with a mean of 0.002 mg/L, and from BDL to 0.53 mg/L with an average of 0.02 mg/L, respectively. In 2017, the Ni concentration in the hand dug wells and the boreholes ranges from BDL to 0.003 mg/L with a mean of 0.001 mg/L, and from 0.0004 to 0.046 mg/L with an average of 0.004 mg/L, respectively. Figure 4.25 shows the spatial distribution map of nickel content in the groundwater of the Lower Tano River Basin. From the map, groundwater represented by shades of red and orange colour, mostly seen in the aquifer of the Birimian Supergroup with few observed in the aquifer of the Apollonian formation are above WHO (2011) permissible limit of 0.006 mg/L for drinking water. The rest of the groundwater represented by shades of different colours are below the acceptable range. Even though legal and illegal small-scale mining activities is rampant in the study area, the elevated Ni content might possibly be from the oxidation of 184 University of Ghana http://ugspace.ug.edu.gh sulphide minerals to release Ni as a secondary mineral. In the study area, Luebe et al., 1990 Adjimah et al., 1993 discovered Ni as one of the trace elements hosted in sulphide minerals in the underlying geology of the study area. Figure 4. 25: Spatial distribution map of Ni concentrations in groundwater in the study area. The manganese (Mn) content in the boreholes drilled in 2013 varies from 0 to 0.14 mg/L with a mean of 0.03 mg/L. That of the boreholes drilled from 2014 to 2015 varied from 0.01 to 0.27 mg/L with a mean of 0.06 mg/L. In 2016, the Mn concentration in the hand dug wells and the boreholes ranges from BDL to 0.59 mg/L with an average of 0.05 mg/L, and from BDL to 30.57 mg/L with a mean of 0.78 mg/L, respectively. Also in 2017, the Mn content in the hand dug wells and the boreholes ranges from BDL to 0.09 mg/L with a mean of 0.009 mg/L and from 0.0003 to 0.47 mg/L with an average of 0.069 mg/L, respectively. The spatial distribution map of manganese in the groundwater is presented in Fig 4.26. From the map, the Mn content represented by shades of blue and grey are below the WHO (2011) permissible limit of 0.4 mg/L. The rest of the groundwater, represented by shades of orange 185 University of Ghana http://ugspace.ug.edu.gh and red are above the WHO (2011) permissible limit of 0.4 mg/L. Also, from the map the elevated Mn content dominated the aquifer of the Birimian Supergroup with fewer representations in the aquifer of the Apollonian formation. In the Birimian Supergroup rocks, studies conducted by Junner et al. (1942) and Kesse (1985) identified occurrences of manganiferrous oxide. In addition, Melcer (1995), Nsuta deposit, service (1943), Kleinscrot el al. (1994), Dzibodi-Adjimah and Sorbor (1993), Mucke et al. (1999), Nyame and Beukes (2006), Dzibodi-Adjimah (2003) etc. identified various sources of Mn in the Birimian Supergroup rocks. The natural sources of Mn mention by the above authors could possibly be one of the contributing factors leading to the high recorded Mn content in the groundwater. Also, the Birimian supergroup rocks contains banded manganese and monzonite rocks (Fig 3.3 and 3.4) which when weathers might release Mn content into the groundwater. Figure 4. 26: Spatial distribution map of Mn in the groundwater in the study area. The Cobalt (Co) content in the boreholes drilled from 2014 to 2015 varies from 0.00001 to 0.01 mg/L with an average of 0.002 mg/L. In 2016, the Co concentration in the sampled hand dug wells and the boreholes ranges from BDL to 0.006 mg/L with an average of 0.0003 mg/L, and from BDL to 0.08 mg/L with a mean of 0.003 mg/L, respectively. For 186 University of Ghana http://ugspace.ug.edu.gh 2017 samples, the Co content in the sampled hand dug wells and the boreholes ranges from BDL to 0.002 mg/L with a mean of 0.0003 mg/L, and from 0.00001 to 0.3 mg/L with a mean of 0.001 mg/L, respectively. The Co content in all the groundwater is lower than WHO permissible limit of 0.05 mg/L except for a borehole sampled at Old Kablazuaso in the aquifer of the Apollonian formation. The source of the Co content in the borehole might be geogenic or anthropogenic but further investigations are required. 4.2.2.6 Toxic Elements (Pb and As) The lead (Pb) content in the boreholes drilled in 2013 are very minimal. That of the boreholes drilled from 2014 to 2015 ranges from 0.01 to 0.15 mg/L with an average of 0.07 mg/L. In 2016, the Pb content in the hand dug wells and the boreholes varies from BDL to 16. 30 mg/L with a mean of 0.96 mg/L, and from BDL to 4.25 mg/L with an average of 0.46 mg/L, respectively. In 2017, the Pb concentration in the hand dug wells and the boreholes ranges from BDL to 0.11 mg/L with an average of 0.04 mg/L, and from 0.00003 to 0.03 mg/L with a mean of 0.003 mg/L, respectively. Figure 4.27 shows the spatial distribution map of lead content in groundwater of the study area. From the map, it is seen that groundwater represented by shades of blue, seen mostly in the aquifer of the Birimian Supergroup is below WHO (2011) permissible limit of 0.01 mg/L. The rest are higher than the permissible limit of 0.01 mg/L. The sources of elevated lead in the groundwater might be anthropogenic or geogenic. The anthropogenic source of Pb could possibly be linked to plumbing fixtures (Lee et al., 1989) used for the borehole construction and effluent discharge from rampant illegal small-scale mining. The use of lead as a smelter metal for the purification of gold by these miners produce by products. When these byproducts settle on top of soils or drains, they will be discharged into surrounding surface water bodies through natural process like rainfall or runoff. These surface water bodies could probably recharge the groundwater leading to elevated Pb content in the groundwater. 187 University of Ghana http://ugspace.ug.edu.gh Another source of elevated Pb concentration in the groundwater is anthropogenic activities. In this research, during sampling, we evidenced the citizens unsanitary disposing off their sewage into the rivers especially the Tano River and the Ankobra River. Also, most houses in the study area built after 1970 uses pit latrine, and these houses are still in existence without any modern toilet facilities. An extra source of anthropogenic lead content in the groundwater might probably be from past oil seepages seen by early explorers in 1896 (Ghana geological survey, bulletin number 40). These seepages might probably be existing in the rock matrixes of the study catchment. The geogenic sources of Pb in the study area include the oxidation of sulphide minerals (arsenopyrite (FeAsS), chalco- pyrite (CuFeS2) and pyrite (FeS2)) to release Pb as a secondary mineral. Luebe et al. (1990) and Adjimah et al. (1993) discovered trace element like As, Pb, Cu, Zn, Ni etc. as host elements in sulphide minerals (pyrites, arsenopyrites, chalcopyrite) in the Birimian Super group rocks. Figure 4. 27: Spatial distribution Map of lead content in the groundwater in the study catchment. The arsenic (As) content in boreholes drilled in 2013 are very minimal but that of the boreholes drilled from 2014 to 2015 ranges from 0.00001 to 0.09 mg/L with an average of 0.008 mg/L. In 2016, the As content in the hand dug wells varies from BDL to 0.21 mg/L with a mean of 0.007 mg/L. For the boreholes sampled in 2016, the As concentration varies from BDL to 0.01 188 University of Ghana http://ugspace.ug.edu.gh mg/L with a mean 0.001 mg/L. In 2017, the As concentration in both the hand dug wells and the boreholes varies from BDL to 0.004 mg/L with an average of 0.001 mg/L, and from 0.0004 to 0.031 mg/L with a mean of 0.002 mg/L, respectively. Hand dug wells sampled in 2016 and 2017 had arsenic content below the WHO permissible limit of 0.01 mg/L, except a hand dug well located at Asanta in the aquifer of the Apollonian formation. For the boreholes drilled in 2013, the arsenic content is below the WHO permissible limit of 0.01 mg/L. From 2014 to 2015, 16 boreholes (n= 18) are below the WHO (2011) permissible limits and the remaining 2 boreholes situated at Asanta and Newton in the aquifer of the Apollonian formation are above the permissible limits. In 2016 and 2017, the arsenic levels in all the boreholes are below the WHO (2011) permissible limit of 0.01 mg/L with the exclusion of a borehole situated at Salman, in the aquifer of the Birimian Supergroup. The main source of Arsenic in an environment is attributed to chemical manufacturing, application of pesticides, metal smelting, and coal combusting (Diaz-Barringa et.al., 1993). However, in the study area, apart from metal smelting and the application of pesticides, the rest of the above- mentioned sources are not common. Another source of elevated As in the groundwater is related to the oxidation of sulphide minerals from the underlying geology. When these sulphide minerals oxidize As is mobilized as a primary mineral in the groundwater. Smedley et al. (2007) and Kortatsi et al. (2008b) revealed mineralized volcano- sedimentary Birimian supergroup rocks as common sources of Arsenic. 4.2.2.7 Non-Metallic Elements (Al) Aluminum (Al) concentrations in the boreholes drilled in 2013 varies from 0.00001 to 0.06 mg/L with a mean of 0.004 mg/L. From 2014 to 2015, the Al content in the drilled boreholes ranges from 0.05 to 3.2 mg/L with an average of 0.36 mg/L. In 2016, the Al content in the sampled hand dug wells and boreholes varies from 0.004 mg/L to 0.55 mg/L with an average of 0.07 mg/L, and from BDL to 0.76 mg/L with an average of 0.08 mg/L, respectively. In 2017, the Al content in the sampled hand dug wells and the boreholes ranges from BDL to 2.48 mg/L 189 University of Ghana http://ugspace.ug.edu.gh with an average of 0.13 mg/L, and from 0.0002 to 0.72 mg/L with a mean of 0.05 mg/L, respectively. The Al content in the hand dug well sampled in 2016 and 2017 are all below WHO permissible limit of 0.2 mg/L, except four hand dug wells sampled at Esiama, Elubo and Azelenuano all in the aquifer of the Apollonian formation. The Al content in this hand dug wells are above the WHO (2011) permissible limit of 0.2 mg/L for drinking water. The boreholes sampled from 2013 to 2017 had Al content in most of the boreholes below the permissible limit of 0.2 mg/L. Correspondingly, fewer boreholes sampled at Effasu, Mangyea, Alumatupe, Jawey, Twenen, Kengen, Esiama, Azulenuano, all in the aquifer of the Apollonian formation and Aluku Alabokazo, Aniwafuto (chips), and Elubo all in the aquifer of the Birimian Supergroup had Al content above the WHO (2011) permissible limit of 0.2 mg/L. The source of high Al content in the groundwater is linked to the chemical weathering of silicate minerals (Hornblende, Biotite etc.) and granitic rocks which exist in the underlying geology of the study area. The variation in trace elements in the groundwater is linked to the seasons in which the samples were taken, the time, the lithology, and human activities. Among the measured trace elements Fe had the highest occurrences. This is due to Fe being among the most abundant trace elements in the earth’s crust and Fe being released through inter blended processes such as water–rock interaction (Melegy et al., 2013). The increased Fe concentration in the groundwater is linked to natural sources such as biological processes and chemical processes in the rocks. The trace element results obtained for the groundwater in the aquifer of the Birimian supergroup and the Apollonian formation is like that of the surface water discussed in previous chapters as well as studies carried out by Edjah 2012 and Doyi et al. (2018) in the Lower Tano River Basin. 4.2.3. Pearson Correlation Matrix Under this section, Pearson correlation matrix is used to establish the relationship between the cations, anions, and trace elements in the groundwater. The obtained results are shown in Table 4.37,4.38,4.39,4.40,4.41 and 4.42, respectively. The ions that correlated are highlighted in red. 190 University of Ghana http://ugspace.ug.edu.gh Table 4. 37: Pearson correlation matrix of hydrochemical data and trace element data for the Boreholes drilled in 2013. Ca2+ Mg2+ TH No - SO 2- Cl- 3 4 pH EC TDS As Al Zn CU Mn Fe Cr Pb Ca2+ 1.0 Mg2+ 0.7 1.0 TH 0.9 0.9 1.0 NO - 3 0.2 0.3 0.3 1.0 SO 2- 4 0.3 0.2 0.3 -0.2 1.0 Cl- 0.4 0.5 0.6 0.0 0.2 1.0 pH 0.0 0.0 0.0 0.3 -0.2 -0.3 1.0 EC 0.4 0.5 0.5 0.1 0.4 0.4 -0.4 1.0 TDS 0.5 0.5 0.5 0.1 0.3 0.5 -0.4 0.9 1.0 As 1.0 Al 0.2 0.1 0.2 0.01 0.1 0.01 0.2 0.01 0.01 1.0 Zn -0.2 -0.3 -0.3 -0.2 -0.5 -0.1 0.1 -0.2 -0.2 0.1 1.0 CU -0.1 -0.3 -0.2 0.0 -0.5 -0.1 0.3 -0.2 -0.2 0.1 0.4 1.0 Mn 0.1 0.2 0.1 -0.1 0.1 0.3 -0.8 0.4 0.5 -0.1 -0.1 -0.1 1.0 Fe 0.1 0.1 0.1 -0.2 0.3 0.4 -0.8 0.5 0.5 -0.2 -0.2 -0.1 0.9 1.0 Cr -0.2 -0.1 -0.1 0.4 0.01 0.01 0.2 -0.1 -0.1 0.1 -0.1 0.0 -0.1 -0.1 1.0 Pb 1 191 University of Ghana http://ugspace.ug.edu.gh Table 4. 38: Pearson correlation matrix of hydrochemical data and trace element data for the Boreholes drilled from 2014 to 2015. Ca2+ Mg2+ TH Na+ K+ HCO - 3 SO 2- 4 Cl- pH EC TDS Al Zn Cu Mn Fe Cr Pb Co Cd Ni As Ca2+ 1 Mg2+ 0.3 1.0 TH 0.9 0.7 1.0 Na+ 0.1 0.8 0.4 1.0 K 0.1 0.6 0.3 0.8 1.0 HCO - 3 0.9 0.6 1.0 0.4 0.3 1.0 SO 2- 4 0.4 0.3 0.4 0.3 0.5 0.3 1.0 Cl- 0.1 0.7 0.4 1.0 0.8 0.4 0.3 1.0 pH 0.7 0.5 0.8 0.5 0.6 0.8 0.3 0.5 1.0 EC 0.5 0.8 0.8 0.9 0.7 0.7 0.4 0.9 0.7 1.0 TDS 0.5 0.8 0.7 0.9 0.7 0.7 0.4 0.9 0.7 1.0 1.0 Al -0.3 -0.1 -0.3 0.01 -0.1 -0.2 0.01 0.01 -0.3 -0.2 -0.1 1.0 Zn 0.2 0.2 0.2 -0.1 0.1 0.2 0.3 -0.1 0.01 0.01 0.01 0.3 1.0 Cu 0.1 0.7 0.4 1.0 0.9 0.4 0.3 0.9 0.6 0.9 0.9 -0.1 0.01 1.0 Mn 0.5 0.5 0.6 0.01 0.01 0.6 0.1 0.01 0.3 0.3 0.2 -0.2 0.3 -0.1 1.0 Fe -0.2 -0.1 -0.2 -0.1 -0.1 -0.1 0.1 0.01 -0.3 -0.1 -0.1 0.3 0.3 -0.1 -0.2 1.0 Cr -0.3 0.2 -0.1 0.4 0.2 -0.1 0.1 0.4 -0.1 0.2 0.2 0.9 0.3 0.3 -0.2 0.4 1.0 Pb -0.1 0.0 -0.1 -0.1 0.1 -0.2 -0.2 -0.1 0.1 -0.1 -0.1 -0.3 -0.1 0.01 0.2 -0.5 -0.4 1.0 Co 0.3 0.7 0.5 0.6 0.8 0.5 0.2 0.5 0.6 0.7 0.6 -0.2 0.3 0.7 0.4 -0.2 0.0 0.2 1.0 Cd -0.3 -0.2 -0.3 -0.2 -0.2 -0.3 -0.2 -0.2 -0.2 -0.3 -0.3 -0.2 -0.3 -0.2 -0.1 0.3 -0.1 0.3 -0.2 1.0 Ni 0.5 0.9 0.7 0.9 0.7 0.7 0.3 0.8 0.7 1.0 1.0 -0.2 0.1 0.8 0.4 -0.1 0.2 -0.1 0.7 -0.2 1.0 As 0.01 0.2 0.1 0.4 0.8 0.01 0.1 0.3 0.4 0.3 0.3 -0.1 0.3 0.6 -0.1 -0.1 0.0 0.2 0.8 -0.2 0.3 1.0 192 University of Ghana http://ugspace.ug.edu.gh Table 4. 39: Pearson correlation matrix of hydrochemical data and trace element data for the Hand dug wells sampled in 2016. Ca2+ Mg2+ TH Na+ K+ HCO - 3 SO Cl NO PH EC TDS Al Zn Cu Mn Fe Cr Pb Co Cd Ni As Ca2+ 1 Mg2+ 0.2 1.0 TH 0.9 0.6 1.0 Na+ 0.4 0.4 0.5 1.0 K+ 0.3 -0.1 0.2 0.7 1.0 HCO - 3 0.3 0.1 0.3 0.5 0.2 1.0 SO 2- 4 0.5 0.01 0.4 0.5 0.7 0.0 1.0 Cl- 0.5 0.6 0.7 0.8 0.5 0.3 0.3 1.0 NO - 3 0.4 0.01 0.3 0.5 0.6 0.3 0.3 0.5 1.0 PH 0.1 0.1 0.1 0.2 0.0 0.1 -0.2 0.3 0.2 1.0 EC 0.6 0.1 0.5 0.8 0.7 0.4 0.6 0.7 0.6 0.2 1.0 TDS 0.5 0.1 0.5 0.8 0.7 0.3 0.5 0.7 0.6 0.1 1.0 1.0 Al -0.1 -0.2 -0.1 -0.1 0.01 -0.1 -0.1 -0.1 0.01 -0.1 -0.2 -0.2 1.0 Zn -0.2 0.01 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.2 -0.1 -0.1 0.01 1.0 Cu -0.1 -0.1 -0.1 -0.2 -0.1 -0.1 -0.2 -0.1 -0.1 0.01 -0.2 -0.2 0.3 0.01 1.0 Mn -0.1 0.5 0.2 0.2 -0.1 -0.1 -0.1 0.3 -0.1 0.01 0.01 0.01 -0.1 0.8 -0.1 1.0 Fe -0.1 -0.1 -0.2 0.4 0.4 0.01 0.4 0.1 0.01 -0.2 0.2 0.2 0.1 0.01 -0.1 0.1 1.0 Cr -0.1 -0.1 -0.1 -0.1 -0.1 -0.2 -0.1 -0.1 -0.1 -0.2 -0.1 -0.1 0.1 0.01 0.01 0.01 -0.1 1.0 Pb 0.01 -0.1 -0.1 0.5 0.5 0.01 0.4 0.2 0.2 0.01 0.4 0.4 0.01 -0.1 0.01 0.01 0.8 -0.1 1.0 Co -0.2 -0.1 -0.2 0.4 0.4 0.01 0.3 0.1 -0.1 -0.2 0.2 0.2 0.01 0.01 0.01 0.1 0.9 0.01 0.8 1.0 Cd 0.3 0.1 0.3 0.3 0.1 0.2 0.01 0.5 0.5 0.6 0.4 0.4 -0.1 -0.1 -0.1 0.01 -0.1 0.01 0.2 -0.1 1.0 Ni 0.01 -0.3 -0.1 -0.2 0.01 -0.1 -0.2 -0.1 0.01 0.01 -0.2 -0.1 0.7 -0.1 0.4 -0.2 -0.1 0.01 0.2 0.1 0.1 1.0 As 0.01 -0.1 -0.1 -0.1 -0.1 -0.1 0.1 0.01 -0.1 -0.2 0.1 0.1 -0.1 0.01 -0.1 -0.1 0.01 0.01 0.01 0.01 -0.1 -0.1 1.0 193 University of Ghana http://ugspace.ug.edu.gh Table 4. 40: Pearson correlation matrix of hydrochemical data and trace element data for the boreholes sampled in 2016 Ca2+ Mg2+ TH Na+ K+ HCO - 3 SO 2- - - 4 Cl NO3 pH EC TDS Al Zn Cu Mn Fe Cr Pb Co Cd Ni As Ca2~ 1 Mg2+ 0.01 1.0 TH 0.9 0.5 1.0 Na+ 0.1 -0.1 0.1 1.0 K+ 0.01 0.01 0.01 0.6 1.0 HCO - 3 0.5 -0.1 0.4 0.1 0.01 1.0 SO 2- 4 0.3 0.2 0.3 0.6 0.4 -0.3 1.0 Cl- 0.3 0.2 0.3 0.4 0.2 -0.1 0.1 1.0 NO 3 0.01 0.2 0.01 -0.1 -0.1 -0.1 -0.1 0.2 1.0 PH 0.2 0.01 0.1 0.01 0.01 0.4 -0.2 0.01 -0.1 1.0 EC 0.4 0.3 0.5 0.2 0.1 0.3 0.2 0.4 -0.2 0.3 1.0 TDS 0.4 0.3 0.5 0.3 0.2 0.3 0.2 0.5 -0.2 0.3 0.9 1.0 Al -0.1 -0.2 -0.2 0.4 0.3 -0.1 0.2 0.2 0.01 -0.2 0.1 0.01 1.0 Zn -0.1 -0.1 -0.1 -0.2 -0.1 -0.1 -0.1 -0.2 0.01 -0.1 -0.2 -0.2 -0.1 1.0 Cu -0.2 -0.2 -0.2 -0.1 -0.1 -0.1 -0.1 -0.2 0.01 -0.1 -0.2 -0.2 0.01 1.0 1.0 Mn -0.1 -0.1 -0.1 -0.2 -0.1 -0.1 0.01 -0.2 0.01 -0.1 -0.2 -0.2 -0.1 1.0 1.0 1.0 Fe 0.01 0.01 0.01 -0.3 -0.1 -0.1 -0.1 -0.2 0.2 -0.2 -0.2 -0.2 0.01 0.7 0.7 0.7 1.0 Cr 0.2 -0.2 0.1 -0.1 0.01 0.1 0.0 -0.1 -0.2 -0.3 -0.1 0.01 0.01 -0.1 -0.1 -0.1 -0.1 1.0 Pb 0.1 0.3 0.2 0.1 0.2 0.1 0.1 0.01 -0.3 -0.1 0.1 0.2 -0.1 -0.1 -0.1 -0.1 -0.1 0.4 1.0 Co -0.2 0.01 -0.2 0.01 -0.1 -0.1 0.01 0.01 -0.2 0.01 -0.2 -0.1 -0.1 0.01 -0.1 0.01 -0.1 -0.1 0.3 1.0 Cd 0.4 0.1 0.4 -0.1 -0.1 0.01 0.01 0.3 -0.3 0.1 0.2 0.2 -0.1 0.01 0.01 0.01 -0.1 0.3 0.2 0.01 1.0 Ni 0.6 0.01 0.5 0.1 0.01 0.2 0.01 0.4 -0.2 0.01 0.2 0.2 -0.1 0.01 0.01 0.01 0.01 0.1 0.01 0.01 0.7 1.0 As 0.1 0.5 0.3 0.01 -0.1 0.2 0.01 0.01 -0.2 0.2 0.2 0.2 -0.1 -0.1 -0.1 -0.1 -0.1 0.01 0.3 0.1 0.1 0.01 1.0 194 University of Ghana http://ugspace.ug.edu.gh Table 4. 41: Pearson correlation matrix of hydrochemical data and trace element data for the Hand dug wells sampled in 2017 Ca2+ Mg2+ TH Na+ K+ HCO - 3 SO 2- 4 Cl- NO - 3 PH EC TDS Al Zn Cu Mn Fe Cr Pb Co Cd NI As Ca2+ 1 Mg2+ 0.6 1.0 TH 1.0 0.8 1.0 Na+ 0.5 0.6 0.6 1.0 K+ 0.5 0.6 0.6 0.8 1.0 HCO - 3 0.7 0.6 0.7 0.5 0.5 1.0 SO 2- 4 0.4 0.5 0.5 0.6 0.5 0.4 1.0 Cl- 0.4 0.3 0.4 0.6 0.5 0.01 0.01 1.0 NO - 3 0.01 -0.1 0.01 0.3 0.2 -0.2 0.2 0.3 1.0 PH 0.6 0.4 0.6 0.1 0.3 0.6 0.3 -0.1 -0.2 1.0 EC 0.8 0.7 0.9 0.8 0.8 0.7 0.5 0.6 0.2 0.3 1.0 TDS 0.8 0.7 0.9 0.8 0.8 0.7 0.5 0.6 0.2 0.3 1.0 1.0 Al -0.2 0.01 -0.1 0.2 0.2 -0.2 -0.2 0.4 0.4 -0.5 0.2 0.1 1.0 Zn -0.2 -0.1 -0.1 0.01 0.01 -0.2 0.1 0.01 0.3 -0.2 -0.2 -0.2 0.2 1.0 Cu 0.3 0.4 0.4 0.4 0.4 0.2 0.5 0.2 0.2 0.4 0.3 0.3 0.1 0.6 1.0 Mn -0.2 -0.1 -0.2 0.01 0.1 -0.3 -0.2 0.2 0.3 -0.5 0.01 0.01 0.8 0.3 0.01 1.0 Fe 0.8 0.7 0.8 0.4 0.3 0.5 0.4 0.2 -0.1 0.6 0.6 0.6 -0.1 -0.1 0.3 -0.1 1.0 Cr 0.4 0.5 0.5 0.5 0.5 0.5 0.4 0.01 0.1 0.4 0.5 0.5 0.1 0.2 0.5 0.01 0.3 1.0 Pb 0.8 0.5 0.8 0.3 0.4 0.5 0.2 0.3 0.01 0.6 0.6 0.7 0.01 -0.1 0.4 -0.1 0.7 0.3 1.0 Co -0.2 0.01 -0.1 0.1 0.1 -0.2 -0.2 0.2 0.3 -0.4 0.01 0.01 0.7 0.2 0.01 1.0 -0.1 0.1 0.01 1.0 Cd -0.1 0.2 0.01 0.4 0.3 -0.1 0.01 0.4 0.4 -0.4 0.2 0.1 0.7 0.7 0.5 0.6 -0.2 0.3 -0.1 0.5 1.0 Ni 0.1 0.2 0.1 0.2 0.2 -0.1 0.3 0.1 0.3 -0.1 0.1 0.1 0.5 0.7 0.6 0.6 0.2 0.3 0.2 0.6 0.7 1.0 As 0.6 0.6 0.6 0.2 0.3 0.4 0.2 0.1 -0.1 0.5 0.4 0.4 -0.1 0.01 0.4 -0.2 0.6 0.5 0.5 -0.1 0.01 0.2 1.0 195 University of Ghana http://ugspace.ug.edu.gh Table 4. 42: Pearson correlation matrix of hydrochemical data and trace element data for the boreholes sampled in 2017 Ca2+ Mg2+ TH Na+ K+ HCO - 2- - - 3 SO4 Cl NO3 PH EC TDS Al Zn Cu Mn Fe Cr Pb Co Cd Ni As Ca2+ 1 Mg2+ 0.5 1.0 TH 0.8 0.6 1.0 Na+ 0.3 0.1 0.3 1.0 K+ 0.3 0.0 0.3 0.7 1.0 HCO - 3 0.8 0.6 0.7 0.2 0.0 1.0 SO 2- 4 0.3 0.4 0.3 0.6 0.5 0.01 1.0 Cl- 0.2 0.1 0.2 0.7 0.6 0.01 0.2 1.0 NO - 3 0.01 0.01 0.1 0.2 0.2 0.01 0.01 0.2 1.0 PH 0.2 0.1 0.3 0.01 0.2 0.2 -0.1 0.01 0.1 1.0 EC 0.4 0.4 0.4 0.2 0.1 0.6 0.01 0.1 0.3 0.1 1.0 TDS 0.5 0.4 0.5 0.2 0.1 0.6 0.01 0.2 0.3 0.2 0.9 1.0 Al 0.3 0.3 0.1 0.2 0.1 0.3 0.01 0.3 -0.1 -0.1 0.3 0.4 1.0 Zn -0.1 -0.2 -0.2 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 0.0 -0.1 -0.1 0.1 1.0 Cu -0.1 -0.1 -0.1 -0.1 0.01 -0.1 -0.1 -0.1 0.01 0.1 0.01 0.01 0.01 0.9 1.0 Mn 0.3 0.2 0.3 -0.1 -0.1 0.3 0.1 -0.2 0.01 0.1 0.1 0.1 0.01 -0.1 -0.1 1.0 Fe -0.2 -0.3 -0.2 0.4 0.2 -0.2 0.3 0.01 -0.1 -0.3 -0.2 -0.2 -0.2 0.1 0.1 -0.3 1.0 Cr 0.3 0.01 0.2 0.3 0.3 0.1 0.3 0.2 0.1 -0.1 0.1 0.1 0.2 0.01 0.01 0.01 0.3 1.0 Pb 0.01 -0.1 0.01 0.01 0.01 0.01 -0.2 0.1 0.01 0.01 0.1 0.2 0.6 0.1 0.1 -0.1 -0.3 -0.1 1.0 Co 0.3 0.2 0.2 -0.1 -0.1 0.2 0.01 0.1 0.01 0.01 0.1 0.1 0.3 0.01 0.01 0.7 -0.3 0.01 0.3 1.0 Cd -0.1 -0.1 -0.2 -0.1 0.0 -0.1 -0.1 -0.1 0.01 0.01 -0.1 -0.1 0.01 0.9 1.0 0.01 0.1 -0.1 0.01 0.01 1.0 Ni 0.1 0.01 0.01 -0.3 -0.1 0.01 -0.2 0.01 -0.1 0.01 -0.1 -0.1 0.01 0.3 0.4 0.3 -0.3 -0.1 0.1 0.6 0.4 1.0 As 0.01 0.01 0.1 -0.1 -0.1 0.1 -0.1 -0.2 -0.2 -0.1 0.1 0.2 -0.1 -0.1 -0.1 0.3 0.2 0.01 -0.1 0.01 -0.1 0.01 1.0 196 University of Ghana http://ugspace.ug.edu.gh From, the above tables (table 4.37 to 4.42), the cations, anions and trace elements that correlated are highlighted in red. Mg2+ correlated strongly with Ca2+ for the boreholes drilled in 2013, and hand dug wells and boreholes sampled in 2017. The study area records high amount of rainfall (Fig 1.3 to 1.6), as such, carbon dioxide (CO2) released from the atmosphere and decaying organic matter might likely dissolve in the rainwater to form a weak carbonic acid i.e., CO2 + H2O → H CO → H + 2 3 + (HCO - 3 ) (Apello & Postma, 1999). The acid possibly attacks the limestone which exist in the underlying geology, dissolving CaCO3 or MgCO3 to yield an aqueous solution of HCO - , Ca and Mg2+ 3 in the groundwater. TH corelated strongly with Ca2+ and Mg2+ for the boreholes drilled in 2013, boreholes drilled from 2014 to 2015, hand dug wells and boreholes sampled in 2016 and boreholes sampled in 2017. The good relationship is linked to the dissolution of limestones and weathering of silicate minerals (hornblende, plagioclase, biotite etc.) from the underlying geology of the study area. For the boreholes drilled from 2014 to 2015 (Table 4.35) Na+ correlated strongly with Mg2+. In 2016, Na+ correlated strongly with TH for the hand dug wells (Table 4.36) and Na+ correlated strongly with (Ca2+, Mg2+ and TH) for the hand dug wells sampled in 2017. The good relationship between Na+ and (Ca2+ and Mg2+) suggest the possibility of cation-exchange processes at the soil-water interface (Guo & Wang. 2004) which will be explained further in the 3rd specific objective. Also, the good relationship between Na+ and (Ca2+ and Mg2+) indicates the possible weathering of silicate minerals (hornblende, plagioclase, feldspar, etc.) from the underlying geology (Fig 3.3 and 3.4). Bowser and Jones (2002) argued that territories subjugated by silicate minerals is the primary source of Na+, Ca2+ and Mg2+.in groundwater. The good relationship between Na+ and TH indicates that the presence of sodium hardness in the groundwater The boreholes drilled from 2014 to 2015 had K+ correlating strongly with (Mg2+ and Na+). In addition, K+ correlated strongly with Na+ for the hand dug wells and boreholes sampled in 197 University of Ghana http://ugspace.ug.edu.gh 2016. For the hand dug wells sampled in 2017, K+ correlated strongly with (Ca2+, Mg2+, TH and Na+). Also, for the boreholes sampled in 2017, K+ correlated strongly with Na+. The good relationship between K+ and Na+ is linked to the chemical weathering of silicate minerals (biotite, feldspars) from the underlying geology of the study area (Fig 3.3 and 3.4). In addition, the good relationship between K+ and Mg2+ is linked to the weathering of granitic rocks which exist in the study area. Also, the relationship between K+ and Mg2+ suggest a possible cation - exchange processes (Drever, 1988). The good relationship between K+ and TH suggest potassium hardness in the groundwater. HCO - correlated strongly with (Ca2+, Mg2+3 , and TH) for the boreholes drilled from 2014 to 2015. Also, HCO -3 correlated strongly with Na + for the hand dug wells sampled in 2016. For the boreholes sampled in 2016, HCO -3 correlated strongly with Ca 2+. In 2017, HCO -3 in the sampled hand dug wells and boreholes correlated strongly with (Ca2+, Mg2+, TH, K+, Na+), and (Ca2+, Mg2+ and TH), respectively. Groundwater containing bicarbonate, calcium and magnesium could be altered to one containing bicarbonate, sodium, and potassium (Kister & Hardt, 1966). Hence, the good relationship between HCO - 3 and the above-mentioned elements is linked to Base- Exchange reactions. In addition, the good relationship between HCO -3 and (Ca2+ and Mg2+) represents the dissolution of carbonate minerals (limestones etc.) and chemical weathering of granitic rocks. The good relationship between HCO -3 and TH indicates the presence of carbonate hardness (Drever, 1988) in the sampled groundwater due to the groundwater interacting with carbonate minerals and silicate minerals from the underlying geology. Also, the good relationship between HCO -3 and (Na + and K+) suggests a possible cation exchange processes were Na+ and K+ from silicate mineral (feldspars, plagioclase etc) weathering from the underlying geology are specially desorbed into the groundwater. In addition, the relationship between HCO -3 and Ca 2+ probably indicate a recharging aquifer which will be explained in the 3rd and 4th specific objective and dissolution of carbonate 198 University of Ghana http://ugspace.ug.edu.gh minerals (Khashogji and El Maghraby, 2013) and weathering of silicate mineral (plagioclase, hornblende, etc) (Gastmans et al. 2010) from the underlying geology of the study area. SO 2-4 correlated strongly with K + for the boreholes drilled from 2014 to 2015. For the hand dug wells and boreholes sampled in 2016, SO 2-4 correlated strongly with (Ca 2+, Na+ , K+) and SO 2-4 correlated strongly with Na +, respectively. In 2017, SO 2-4 correlated strongly with (Mg 2+, TH, Na+ , K+) for the hand dug wells and SO 2- correlated strongly with (Na+ , K+4 ). The good relationship between SO 2- 4 and (Ca 2+, Mg2+) is ascribed to ion-exchange processes. The good relationship between SO 2- 4 and (Na + and K+) is accredited to anthropogenic sources (Sophocleous et al., 2002). Also, the good relationship between SO 2- 2+4 and Mg indicate that sulphide mineral dissolution from the underlying geology is the basis for sulphate loading in the groundwater (Liu et al., 2019). In 2013, Cl- correlated strongly with Mg2+ and TH for the drilled boreholes. For the boreholes drilled from 2014 to 2015, Cl- correlated strongly with Mg2+, Na+ and K+. For the hand dug wells sampled in 2016, Cl- correlated strongly with Ca2+, Mg2+, TH, Na+ and K+. In 2017, Cl- correlated strongly with Na+ and K+ for the hand dug wells and boreholes sampled in 2017. The relationship between Cl- and (Na+, K+) in the groundwater is linked to ion exchange processes and imitates the contribution of rainfall recharge, which will be explained further in the 4th specific objective. The good relationship between Cl- and (Ca2+, Mg2+) is linked to rock- water interactions. The good linkage between Cl- and TH indicates chloride hardness in the groundwater. Additionally, NO -3 correlated strongly with Na +, K+ and Cl- in the hand dug wells sampled in 2016. The good relationship between NO -3 and (Na + and K+) indicates a possible ion exchange process. That of NO - - 3 and Cl is due to anthropogenic sources such as prolonged minimal application of fertilizers by peasant farmers, cocoa farmers, and coconut farmers in the study 199 University of Ghana http://ugspace.ug.edu.gh area. Another source is attributed to effluents discharge from the surrounding industries such as coconut oil industries, but further investigations is required. pH correlated strongly with Ca2+, Mg2+, TH, Na+, K+, HCO - and Cl- 3 for the boreholes drilled from 2014 to 2015. For the hand dug wells sampled in 2017, pH correlated strongly with Ca2+, TH and HCO -. The good relationship between pH and (Ca2+3 , Mg 2+, -) indicate carbonate mineral dissolution and silicate mineral (plagioclase, biotite, feldspar etc.) weathering from the underlying geology. The good relationship between pH and TH suggests the dissolution of carbonate minerals from the rocks of the Apollonian and chemical weathering of silicate minerals from the rocks of the Birimian supergroup. Additionally, the good connection between pH and (Na+, K+) suggest weathering of silicate minerals (plagioclase, hornblende feldspars, etc.) from the underlying geology. The good relationship between pH and Cl- is attributed to a contaminated source which requires further investigations. The good relationship between pH and HCO -3 indicates same geochemical processes. EC correlated strongly with (Mg2+ and TH) for the boreholes drilled in 2013. For the boreholes drilled from 2014 to 2015, EC correlated strongly with Ca2+, Mg2+, TH, Na+, K+, HCO -3 , pH and Cl-. For the hand dug wells and boreholes sampled in 2016, EC correlated strongly with Ca2+, TH, Na+, K+, SO 2-4 , Cl - and NO - 3 , and TH, respectively. For the hand dug wells and boreholes sampled in 2017, EC correlated strongly with Ca2+, Mg2+, TH, Na+, K+, HCO -3 , SO 2-4 , and Cl -, and HCO -3 , respectively. The good relationship between EC and the above- mentioned elements indicates that the above analyzed ions possibly contributed to the groundwater mineralization of the study area. The good relationship between EC and (SO 2-4 , NO -3 ) indicates that anthropogenic sources or geogenic sources possibly aids in the mineralization of groundwater in the study area. Also, the good relationship between EC and (Ca2+, Mg2+, TH, Na+, K+, SO 2- -4 , Cl and HCO - 3 , NO - 3 ) indicates that most of the above- mentioned ions are probably involved in physiochemical reactions such as oxidation-reduction and ion-exchange (Subba Rao, 2002). 200 University of Ghana http://ugspace.ug.edu.gh There was a good relationship between TDS and EC for the boreholes drilled in 2013, the boreholes drilled from 2014 to 2015, the hand dug wells and boreholes sampled in 2016, and the hand dug wells and boreholes sampled in 2017. TDS reveals the behavior of EC in groundwater (Patil et al., 2010). Also, TDS correlated strongly with Mg2+, TH and Cl for the boreholes drilled in 2013. For the boreholes drilled from 2014 to 2015, TDS correlated strongly with (Ca2+, Mg2+, TH, Na+, K+, HCO - 3 , Cl - and pH). For the hand dug wells sampled in 2016 there was a strong correlation between TDS and (Ca2+, TH, Na+, K+, SO 2-4 , Cl -, and NO -3 ) and for the boreholes sampled in 2016, TDS correlated strongly with (TH and Cl-). For the hand dug wells sampled in 2017, TDS correlated strongly with Ca2+, Mg2+, TH, Na+, K+, HCO - 3 , SO 2-4 , and Cl -). For the boreholes sampled in 2017, TDS correlated strongly with Ca2+, TH and HCO3). The relationship between the TDS and the above mention ions in the groundwater shows that the above - mentioned elements is involved in a long-term physiochemical reaction such as ion exchange and oxidation – reduction (Subba Rao, 2002). Al negatively correlated with pH for the hand dug wells sampled in 2017. The pH of natural water generally varies from 4 to 10 (Apello & Postma, 1999). Comparatively small changes of pH can have a critical effect on the adsorption of ions onto, and from the surface of sediments. The relatively low mean pH (5.98) recorded during the dry season for the hand dug wells could possibly not influence the weathering of silicate mineral (Hornblende, granite, biotite etc.) from the underlying geology to release Al as a primary ion in the groundwater. Zn correlated negatively with SO 2-4 for the boreholes drilled in 2013. This shows that SO 2- 4 is not influenced during sulphide mineral (pyrites, arsenopyrites, cha;copyrites) oxidation to release Zn as a secondary mineral in the groundwater. (Luebe et al.,1990) discovered Zn as one of the trace elements hosted in the sulphide minerals of the study area. Cu correlated strongly with SO 2- 4 for the boreholes drilled in 2013. For the boreholes drilled from 2014 to 2015, Cu correlated strongly with Mg2+, Na+, K+, Cl-, pH, EC, and TDS. For the 201 University of Ghana http://ugspace.ug.edu.gh boreholes sampled in 2016, Cu correlated perfectly with Zn. Additionally, Cu correlated strongly with (SO 2-4 and Zn) and perfectly with Zn for the hand dug wells and boreholes sampled in 2016, respectively. The good relationship between Cu and (SO 2-4 , Zn) is possibly from the oxidation of sulphide bearing minerals {arsenopyrite (FeAsS), chalco- pyrite (CuFeS2) and pyrite (FeS2)} (Luebe et al., 1990; Adjimah et al., 1993) to liberate SO 2- 4 and Zn, as secondary mineral in the groundwater. In addition, the good relationship between Cu and (Mg2+, Na+, K+) suggests the likelihood of rock weathering. When rainfall containing Cl interacts with chalco-pyrite from the underlying geology, transportation of mobilized Cu in the groundwater occurs thus leading to the good relationship between Cu and Cl-. Additionally, the sulphide minerals are present in the underlying geology of the study area, hence drainage of sulfuric acid may significantly contribute to the acidity (Hunslow, 1995) of the groundwater thus leading to a good relationship exists between Cu and pH for the boreholes drilled from 2014 to 2015. The good relationship between Cu and (EC and TDS) indicates that the mobilization of sulphide minerals {chalcopyrite (CuFeS2)} from the underlying geology influences the mineralization of the groundwater. Mn correlated negatively with pH for the boreholes drilled in 2013. This indicates that the pH of the sampled groundwater does not influence the weathering of ferromagnesium (Biotite) minerals or banded manganese formation. In addition to the boreholes drilled in 2013, Mn correlated strongly with TDS. This suggests that the weathering of ferromagnesium (Biotite) minerals or banded manganese formation minerals adds to the mineralization of the groundwater. For the boreholes drilled from 2014 to 2015, Mn correlated strongly with (Ca2+, Mg2+). This indicates a possible weathering of silicate minerals (biotite, hornblende, feldspar, muscovite, quartz, staurolite, etc.) (fig 3.3 and 3.4) from the underlying geology. The good relationship between Mn and HCO -3 has explained the weathering of ferromagnesium (Biotite) minerals or banded manganese formation of the study area. The good connection between Mn and TH indicates manganese hardness in the groundwater. For the hand dug wells and 202 University of Ghana http://ugspace.ug.edu.gh boreholes sampled in 2016, Mn correlated strongly with (Mg2+ and Zn), and perfectly with Zn respectively. Geochemically, Mn behaves like Mg2+, Ni, Fe and Co and tends to partition into minerals that form in the early stages of magmatic crystallization (Post, 1999). Hence, the good relationship between Mn and Mg2+ is likely to be seen. Additionally, Mn and Zn are found as trace elements in groundwater that ensue as crystal structure of minerals seen in rocks and the occurrence of Mn and Zn in groundwater is dependent on the mobility and the weathering condition (Handa, 1986). Hence, the good relationship between Mn and Zn is likely to be observed. For the hand dug wells sampled in 2017, Mn correlated negatively with pH. This indicates the absence of same geochemical processes. In addition, Mn correlated strongly with Al and the possible reason might be from the weathering of silicate minerals (hornblende, biotite etc.) from the underlying geology. For the boreholes drilled in 2013, Fe negatively correlated with pH and Fe correlated strongly with pH for the hand dug wells sampled in 2017. In the study area, the underlying geology is rich in pyrites, and the pH of the boreholes sampled in 2013 were neutral to basic (6.7 – 7.7). Hence there is a non-occurrence of geochemical processes (Hunslow, 1995). For the boreholes sampled in 2017, the pH was acidic to basic, hence the is a possible geochemical process or or oxidation of sulphide minerals or weathering of silicate minerals or granitic rocks from the underlying geology. Fe correlated strongly with TDS for the boreholes drilled in 2013 and the hand dug wells sampled in 2017. The good relationship indicates that Fe controls the groundwater mineralization in the 2013 sampled boreholes and 2017 sampled hand dug wells. For the hand dug wells sampled in 2017, Fe correlated strongly with (Ca2+, Mg2+, TH, and HCO -3 ). This is attributed to the weathering of granitic rocks, and silicate minerals (hornblende, etc.) from the underlying geology. Additionally, for the hand dug wells sampled in 2017, Fe correlated strongly with EC and this indicates that Fe controls the mineralization of the hand dug wells sampled in 2017. The good relationship between Fe and (Cu and Zn) for the boreholes sampled in 2016 suggest sulphide minerals {chalco- pyrite (CuFeS2), pyrites } 203 University of Ghana http://ugspace.ug.edu.gh oxidation. Luebe et al., 1990; Adjimah et al., 1993 discovered trace elements like As, Pb, Cu, Zn, Ni etc. hosted in the sulphide minerals. These trace elements were used as pathfinder elements for the discovery of gold in the study area. Similarly for the boreholes drilled in 2013 and the boreholes sampled in 2016, Fe correlated strongly with Mn. Looking at the geological map of the study area (fig 3.3 and 3.4), it is seen that the rocks of the Apollonian is in a coastal alluvial plain. Alluvial plain is naturally not rich in trace elements but are porous, coarse, and permeable (Kesse, 1985) enough to facilitate the contamination of groundwater with trace elements such as Fe and Mn. Such plains usually have elevated organic- matter which might enhance microbial activities that in turn produce a reducing environment protruding the dissolution of Fe and Mn (Postawa et al., 2013; Weng et al., 2007). Studies have shown that coastal aquifers are vulnerable to salinization and previous investigations elsewhere have found that elevated salinity is responsible for the dissolution of Fe and Mn (Zang et al., 2020; Liu et al., 2019; Pezzetta et al., 2011) in groundwater. Also, the coastal zone of the study area is the hub for oil and gas industries and a target for urbanization and studies have proven and confirmed that urbanization correlates with high Fe and Mn content in groundwater (Onodera, 2008; Fadly et al., 2017). In the study area, even though the rock matrixes contain Fe and Mn bearing minerals like hornblende, biotite etc., the hydrogeological information with respect to natural conditions are limited. Hence, the good relationship between Fe and Mn suggests a possible-non-homogeneous geochemical processes such as different ion concentrations in the aquifer system and different mineral dissolution rate, but further investigations is required. Fe is normally present at elevated concentration than Mn (Postawa et al., 2013; Giblin, 2009). However, in this study, the analyzed Fe values is higher than Mn for all the sampled groundwater and this possibly confirm the heterogeneous geochemical nature of the aquifer of the Birimian supergroup and the Apollonian formation, where Fe and Mn were irregularly dispersed. 204 University of Ghana http://ugspace.ug.edu.gh For the boreholes drilled from 2014 to 2015, Cr correlated perfectly with Al. Cr also correlated strongly with (Mg2+, TH, Na+, K+, HCO -3 , EC, TDS, Cu) for the hand dug wells sampled in 2017. Chromite is an oxide mineral that contains Fe, Mg2+, Al, Ca2+ and Cr in variable proportions depending on their deposits (Murthy et al., 2011; Sanchez-Segado et al., 2015). Chromite transpires exclusively in mafic and ultramafic igneous rocks {Papp & Lipin. (2006)}. In the study area, ultramafic rocks and minor mafic igneous rocks which are undifferentiated are found in the underlying geology (Fig 3.3 and 3.4; Dampare et al. (2008)}and it can be inferred that the possible occurrence of mafic and ultramafic weathering from the underlying geology of the study area led to the good relationship between Fe and (Cr, Al, Mg2+) in the groundwater of the study area. The good relationship between Cr and (Cu, Na+and K+) indicates a possible rock weathering with rock-water interactions but further investigations are required. Also, the good relationship between Cr and HCO -3 indicates a possible rock-water interaction (McClain & Maher, 2016). The good relationship between Cr and (EC and TDS) is attributed to similar geochemical processes such as ion exchange processes and Cr possibly added to the groundwater mineralization of the study area. For the boreholes drilled from 2014 to 2015, Pb correlated negatively with Fe, suggesting that Pb might possibly not influence Fe in the aquifer system. For the hand dug wells sampled in 2016 and 2017, Pb correlated strongly with (Na+, K+ and Fe), and (Ca2+, Mg2+, TH, HCO -3 , pH EC, TDS, and Fe), respectively. For the boreholes sampled in 2017, Pb correlated strongly with Al. The good relationship between Pb and (Na+, K+ , Ca2+, Mg2+, Fe, Al) suggests a possible rock -water interaction. Pb released as a secondary mineral from the oxidation of pyrites {arsenopyrite (FeAsS), chalco- pyrite (CuFeS2) and pyrite (FeS2)} (Luebe et al., 1990) might possibly dissolve into surrounding surface waterbodies and through natural processes like rainfall or run off might be carried to the water table and leached into the aquifer to interact 205 University of Ghana http://ugspace.ug.edu.gh with Na+, K+, Ca2+, Mg2+,Fe , Al released from the weathering of silicate minerals (Biotite, Muscovite, hornblende,, sericite, feldspars, etc.),granitic rocks, monzonite rocks and carbonates mineral (limestones, clay minerals etc.) dissolution from the underlying geology. The strong positive correlation shown between Pb and TH suggest Pb hardness in the groundwater. Also, the good linkage between Pb and HCO -3 suggests a possible rock-water interactions. For the boreholes drilled from 2014 to 2015, Co correlated strongly with Mg2+, TH, Na+, K+, HCO - -3 , Cl , pH, EC, TDS, and Cu. For the hand dug wells sampled in 2016, Co strongly correlated with Fe and Pb and for the hand dug wells sampled in 2017, Co correlated perfectly with Mn and strongly with Al. For the boreholes sampled in 2017, Co correlated strongly with Mn. A relationship exists between Cobalt (Co) and Manganese (Mn) in rocks or soils due to their similar characteristics or properties and are frequently in ferromagnesian minerals where their respective divalent radii permit them to replace readily for Fe (II) and Mg (II) (Goldschmidt, 1958). In sedimentary rocks the concentrations of Mn and Co are highly variable, but as a rule they are uppermost in fine-grained sediments e.g., shales (Goldschmidt, 1958). The above, has explained the good relationship between Co and (Mn, Mg2+, Na+, K+, Al, Fe) that existed in the groundwater. The relationship between Co and (Fe, Pb and Cu) reveals the oxidation of sulphide minerals (pyrites, arsenopyrites, chalcopyrite etc.) from the underlying geology to release Co and Pb as secondary minerals in the groundwater of the study area. The relationship between Co and Cl- is probably related to rock-water interaction. That is when the sulphide minerals from the underlying geology of the study area oxidizes, Co is liberated as a secondary mineral in the groundwater and when rainfall containing Cl interacts with the host rocks Co will probably be transported into the aquifers. The good relationship between Co and (EC and TDS) indicates similar geochemical processes where Co controls the mineralization of groundwater. The good linkage between Co and pH suggests same geochemical source. 206 University of Ghana http://ugspace.ug.edu.gh Also, Cd correlated strongly with Cl-, NO -3 , and pH for the hand dug wells sampled in 2016. In addition, Cd correlated strongly with Al, Zn, Cu, Mn, and Co for the hand dug wells sampled in 2017. For the boreholes sampled in 2017, Cd correlated strongly with Zn and Cu. The good relationship between Cd and (Zn, Cu, Co) are attributed to rock-water interaction. The good relationship between Cd and (Al, Mn) is possibly from the dissolution of clay mineral and carbonate minerals from the underlying geology of the study area. This is possible because works carried out by Appel and Ma. (2002), Buerge-Weirich et al. (2002) and He et al. (2005) shows that high Cd concentration in sediments and soils are normally linked to the abundance of carbonates, clay minerals, organic matter, and hydrous oxides, as well as other physicochemical settings, such as high pH, and/or anoxic conditions. But further investigations are required. The good relationship between Cd and pH implies same geochemical processes. The good relationship between Cd and (Cl- and NO -3 ) indicates a probable anthropogenic source. For the boreholes drilled from 2014 to 2015, Ni correlated strongly with (Ca2+, Mg2+, TH, Na+, K+, HCO -3 , Cl -, pH, EC, TDS, Cu, Co). For the hand dug wells and boreholes sampled in 2016, Ni correlated strongly with Al and (Ca2+, TH and Cd), respectively. In 2017, Ni correlated strongly with (Al, Cu, Zn, Mn, Co, and Cd) for the hand dug wells and (Co) for the boreholes. In the underlying geology of the study area, the omnipresence of pyrites, chalcopyrite and arsenopyrites which host trace elements like Ni, Zn, Co etc. {Luebe et al. (1990)} possibly influences the groundwater mineralization leading to the good relationship between Ni and (EC, TDS) in the groundwater. The good relationship between Ni and (Zn, Co, Cu). suggests the oxidation of sulphide minerals (chalcopyrite’s etc.) from the underlying geology to release Cu as a primary mineral and Ni, Zn and Co as secondary minerals in the groundwater. The good connection between Ni and Cl suggests rock -water interaction. That is Ni released as a secondary mineral from the oxidation of sulphide minerals from the underlying geology probably interacts with Cl- in rainwater from the unsaturated zone to the saturated zone. 207 University of Ghana http://ugspace.ug.edu.gh The rocks of the Apollonian and the Birimian formation of the study area are rich in pyrites, hence drainage of sulfuric acid may significantly contribute to the acidity (Hunslow, 1995) of the aquifer thereby leading to the strong correlation between Ni and pH. Also, the good correlation between Ni and (Na+, K+) indicates rock weathering. The good relationship between Ni and pH specifies sulphide mineral oxidation to release Ni as a secondary mineral in the groundwater. The good connection between Ni and HCO - 3 suggests same geochemical sources in the groundwater. For the boreholes drilled from 2014 to 2015, As correlated strongly with K+, Cu and Co. For the borehole sampled in 2016, As correlated strongly with Mg2+ and for the hand dug wells sampled in 2017, As correlated strongly with (Ca2+, Mg2+, TH, pH, Fe, Cr, and Pb). The good relationship between As and (Fe, Pb, Cu, and Co) suggest sulphide mineral oxidation or mobilization to release Pb and Cu as secondary minerals and As, Fe and Cu as primary minerals in the groundwater. In addition, the good relationship existing between As and (Ca2+, Mg2+, and K+) suggest a possible geogenic sources and the good connection between As and pH indicates sulphide mineral oxidation to release As as a primary mineral in the groundwater. The good relationship between As and TH reveals arsenic hardness in the groundwater. As correlated strongly with Cr, and this suggest a possible rock-water interaction. 4.2.4 Calculation of Water Quality Index (WQI) WQI is a significant parameter aimed at categorizing groundwater suitability for drinking (Magesh et al., 2012) purposes. It also provides the composite influence of individual water quality parameters on the overall water quality (Mitrs and ASABE Member, 1998). To calculate the water quality index for the Lower Tano River Basin, each chemical and trace element parameters are assigned a weight. The weights in each parameter are grounded on its respective WHO (2011) standards. The assigned weight illustrates the importance of the parameters and its impact on the water quality index. A usual water quality index procedure follows three steps which involve Parameter selection, assessment of quality function for each 208 University of Ghana http://ugspace.ug.edu.gh selected parameter and accumulation through mathematical equation (Tyagi s et al., 2013). WQI offers a sole number that signifies the overall water quality at a certain site and time based on some water quality parameters. WQI allows comparison between different sampling locations. It also simplifies a complex dataset into easily reasonable and practical information. Additionally, water quality classification system used in the water quality index denotes the suitability of water for drinking. Table 4.43 and 4.44 shows the assigned weight and its relative weights for the cations, anions, and trace element parameters, respectively for this study. Table 4. 43: Relative weight of hydrochemical parameters. Chemical WHO Weight Relative Relative weight Relative weight Parameters standards (wi) weight (Wi, 2014 - 2015) (Wi, 2016 and (2011) (Wi, 2017) 2013) pH (on scale) 6.5 - 8.5 4 0.25 0.18 0.17 EC (µS/cm) 500 4 0.25 0.18 0.17 TDS (mg/L) 500 4 0.25 0.18 0.17 2+ Ca (mg/L) 75 2 0.13 0.09 0.09 2+ 50 2 0.06 0.05 0.04 Mg (mg/L) TH (mg/L) 500 2 0.13 0.09 0.09 - 500 3 0.14 0.13 HCO3 (mg/L) 2- 250 4 0.25 0.18 0.17 SO4 (mg/L) NO -3 (m/L) 50 5 0.31 0.22 - Cl (mg/L) 250 3 0.19 0.14 0.13 + Na (mg/L) 200 2 0.09 0.09 + K (mg/L) 12 2 0.09 0.09 Table 4. 44: Relative weight of trace element parameters Trace elements WHO (2011) Weight (wi) Relative weight Relative weight Relative weight Standards (Wi, 2013) (Wi, 2014 - 2015) (Wi, 2016 and 2017) Cr 0.05 5 0.31 0.23 0.22 Mn 0.4 4 0.25 0.18 0.17 Fe 0.3 4 0.25 0.18 0.17 Co 0.05 1 0.05 0.04 Ni 0.006 1 0.05 0.04 Cu 0.05 2 0.13 0.09 0.09 Zn 5 1 0.06 0.05 0.04 As 0.01 5 0.31 0.23 0.22 Cd 0.003 5 0.23 0.22 Pb 0.01 5 0.31 0.23 0.22 Al 0.2 2 0.09 0.09 ∑ wi= ∑Wi = ∑Wi = 3.02 ∑Wi = 3.08 72 3.44 The relative weight is computed from the equation: 209 University of Ghana http://ugspace.ug.edu.gh 𝑤𝑖 𝑊𝑖 = 𝑛 Eq 4.8 ∑𝑖=1 𝑤𝑖 The relative weight = Wi The weight of each parameter = wi The number of parameters = n The quality ranking scale for each parameter is calculated by dividing its content in each groundwater sample by its respective WHO (2011) drinking water standard. After, the result is multiplied by 100. The above is given by the equation: 𝑐𝑖 𝑞𝑖 = ( ) × 100 Eq 4.9 𝑠𝑖 Where qi is the quality rating Ci is the concentration of each parameter in each groundwater sample in mg/L. Si is the WHO standard for each chemical parameter in mg/L according to the WHO (2011) guidelines. In calculating the final stage of WQI, the Si is determined for each parameter. The sum of Si values gives the WQI for each groundwater sample. 𝑆𝑙𝑖 = 𝑊𝑖 × 𝑞𝑖 Eq 4.10 𝑊𝑄𝐼 = ∑ 𝑆𝑙𝑖 Eq 4.11 Where Sli is the sub –index of the ith parameter. Qi is the rating based on the concentration of the ith parameter. n is the number of parameters. The statistical summary of WQI results for groundwater sampled from 2013 to 2017 is presented in appendix 27 to 29. A spatial distribution map showing WQI values with the water quality classification for the various groundwater in the sampled years (2013 to 2017) is presented in Figure 4.28 a, b, c. The ground water quality classification with respect to WQI is tabulated below. 210 University of Ghana http://ugspace.ug.edu.gh Table 4. 45: Water quality classification and water types based on WQI Range Type of water <50 Excellent water 50-100 Good water 100-200 Poor water 200-300 Very poor water In this study, 212 samples were analyzed for WQI. Among these samples, groundwater sampled from 2013 to 2015 had 20.83% of the samples(n=48) showing excellent water, 47.92% falling under good water, 12.5% were poor in quality and the remaining 8.33% and 10.42% fall under very poor and unsuitable water, respectively. Comparing Figure 4.2 to Figure 4.28 a, it is seen that the Apollonian formation aquifer which yielded more water are excellent to unsuitable for drinking (31.39 to 389.45), while the aquifer of the Birimian supergroup which yielded less water are excellent to good for drinking (31.39 – 389.45). Figure 4. 28a Spatial distribution map of water quality index WQI) for groundwater sampled from 2013 to 2015. The groundwater sampled in 2016 had 8% of the samples (n=80) falling under excellent for drinking, 13.6% shows good water, 8.8% falls under poor water and the remaining 6.4% and 41.25% of the groundwater were very poor and unsuitable for drinking, respectively. The 211 University of Ghana http://ugspace.ug.edu.gh spatial distribution map for WQI in groundwater sampled in 2016 (Fig 4.28 b) shows that the aquifer of the Apollonian formation and the Birimian supergroup both yielded excellent to unsuitable water for drinking. Figure 4.28b: Spatial distribution map of water quality index (WQI) for groundwater sampled in 2016. In 2017, 50% of the sampled groundwater falls under excellent water quality, 8.33% are good water, 16.7% are poor water, and the remaining 2.38% and 13.10% are very poor and unsuitable for drinking respectively. A spatial distribution map of WQI for 2017 groundwater samples is shown in Figure 4.28 c. Figure 4.28 c indicates that the aquifer of the Apollonian formation mostly yielded excellent water (represented by shades of blue colour) for drinking. 212 University of Ghana http://ugspace.ug.edu.gh Figure 4.28c: Spatial distribution map of water quality index (WQI) for groundwater sampled in 2017. Comparing the quality of the newly boreholes (Fig 4.28 a) drilled in the aquifer of the Apollonian formation and the Birimian supergroup to that of the existing groundwater (Fig 4.28 b and 4.28 c) sampled from both aquifers in 2016 and 2017, it is seen that the existing groundwater is off better quality than the newly developed groundwater. This reveals that the topographic position of the sampling points, the mineral composition, the depth, the seasons in which the samples were taken, the lithology and human activities possibly affected the quality of groundwater in the study area. 4.2.5 Groundwater quality for irrigation Groundwater quality for irrigation depends on the quality of water, soil type, plus salt tolerance characteristics of the plants etc. On similar terms, the suitability of groundwater for 213 University of Ghana http://ugspace.ug.edu.gh irrigation is characterized based on the chemistry, which varies both temporally and spatially. The temporal variability in a particular area is often assigned to anthropogenic reasons (Adhikary et al., 2012) whiles spatial variations is due to its natural hydrogeological setting. In this section, the quality of groundwater for irrigation in the Lower Tano River Basin using chemical indices is assessed. A statistical summary of the calculated chemical indices is tabulated and shown in appendix 27, 28 and 29. 4.2.5.1 Sodium Hazard – Sodium Adsorption ratio The determination of Alkali hazard and sodium in groundwater (hand dug wells and boreholes) is determined by the relative absolute cation concentrations. This is expressed in terms of SAR (Shahid and Mahmoudi, 2014), i.e. 𝑵𝒂+ 𝑺𝑨𝑹 = ………….. Eq 4.12 𝟐+ 𝟐+ √𝑪𝒂 + 𝑴𝒈 𝟐 Where the concentrations of Ca2+, Mg2+ and Na+ is expressed as meq/L. In addition, there is a substantial relationship between the extent to which sodium is adsorbed by the soils and SAR values of irrigation water (Singh et. al., 2008). If irrigation water is low in calcium and high in sodium, cation-exchange reaction might become saturated with sodium. This can destroy the structure of the soil due to scattering of clay particles. In this study, the results obtained from the calculation of SAR are interpolated using inverse distance weighting (IDW) interpolation model in ArcGIS 10.5 software and the SAR classification for irrigation is shown in Table 4.46 and 4.47. Table 4. 46: Sodium Hazard (SAR) and Salinity Hazard for irrigation water (adapted from USSL 1954) Sodium Salinity Range Scale/Class Water Class Hazard Hazard S1 C1 <10 Low Excellent S2 C2 10-18 Medium Good S3 C3 18 - 26 High Doubtful S4 C4 >26 Very High Unsuitable Table 4. 47: Suitability of groundwater (hand dug well) for irrigation based on Sodium Hazard (USSL, 1954). Sodium Hazard/SAR Range Class 2016 (n=36) 2017 (n=30) S1 <10 Excellent 34 30 S2 10 - 18 Good 2 S3 18 -26 Doubtful S4 >26 Unsuitable 214 University of Ghana http://ugspace.ug.edu.gh SAR values in the hand dug wells sampled in 2016 and 2017 range from 0.51 to 15.12 and 0.65 to 5.12, respectively. The SAR values in the hand dug wells is classified into various classes. From Table 4.46 and 4.47, majority of the hand dug wells sampled in both 2016 and 2017 fell under excellent category for irrigation and 2 hand dug wells sampled in 2016 fell under good water for irrigation. Table 4.48: Suitability of groundwater (boreholes) for irrigation based on Sodium Hazard (USSL, 1954). Sodium Hazard/SAR Range Class 2014- 2016 (n=44) 2017 (n= 2015(n=18) S1 <10 Excellent 18 44 50 S2 10 - 18 Good S3 18 -26 Doubtful S4 >26 Unsuitable The calculated SAR values for the boreholes drilled from 2014 to 2015 range from 0.11 to 5.14, that for the boreholes sampled in 2016 and 2017 range from 0.28 to 6.01 and 0.29 to 5.02, respectively. Based on the calculated SAR values (Fig 4.28), it can be said that the groundwater in the aquifer of the Apollonian formation and the Birimian supergroup yields excellent water for irrigation. The USSL diagram (Fig 4.29) indicates that majority of the groundwater samples are within C1-S1 category representing very low salinity medium sodium water, which can be used, for irrigation. But one borehole in the aquifer of the Birimian supergroup falls within C3-S3 category. This shows that the borehole cannot be used for irrigation (Kumar et al., 2007). Figure 4.30 shows the spatial distribution map of SAR in groundwater in the aquifer of the Birimian super group and the Apollonian formation and from the map, it is seen that the groundwater in both aquifers is excellent for irrigation. 215 University of Ghana http://ugspace.ug.edu.gh Figure 4. 29: The quality of water for irrigation in relation to Salinity Hazard and Sodium Hazard based on USSL (1954). Figure 4. 30: Spatial distribution map of groundwater suitability for irrigation based on SAR. 216 University of Ghana http://ugspace.ug.edu.gh 4.2.5.2 Sodium Percentage (Na %) The Na% (Wilcox, 1995; Richards, 1954) is estimated using the formula: 𝑁𝑎+ + 𝐾+ 𝑁𝑎% = 𝐶𝑎2+ …………….. Eq 4.13 + 𝑀𝑔2+ + 𝑁𝑎++ 𝐾+ All concentrations are in meq/L. Na% is calculated for the groundwater in the study catchment (Table 4.46) and the obtained result is interpolated using IDW (Fig 4.31). Table 4.46 shows the classification of groundwater suitability for irrigation based on Na%. Table 4. 49: Sodium percent classification of groundwater within the lower Tano River Basin (After Wilcox, 1955). Na% Water class HDW (2016) HDW (2017) BH (2014-2015) BH (2016) BH (2017) n=36 n=30 n= 18 n=44 n=53 <20 Excellent 2 2 3 20 - 40 Good 3 5 5 7 9 40 - 60 permissible 11 13 9 17 20 60 - 80 doubtful 16 11 2 13 18 >80 unsuitable 6 1 0 5 3 The calculated Na% in the hand dug wells sampled in 2016 ranges from 29.82% to 96.38% and that of 2017 varies from 29.27% to 80.82%. For the boreholes sampled from 2014 to 2015, the Na% varies from 4.47% to 71.57% and in 2016 and 2017 groundwater samples, the Na% varies from 15.26% to 90.63% and 16.21% to 89.15%, respectively. The spatial distribution map of Na% (Fig 4.31) shows that groundwater located in some parts of the coastal aquifer (Apollonian formation), some parts of NE and southern aquifer (Birimian supergroup) represented by shades of red gave out doubtful to unsuitable water for irrigation. 217 University of Ghana http://ugspace.ug.edu.gh Figure 4. 31: Spatial distribution map of groundwater suitability for irrigation based on Na%. Wilcox (1955) used EC and Na% to estimate the quality of groundwater for irrigation purposes. The computed results from the Wilcox diagram (Fig 4.32) shows that majority of the sampled groundwater falls under very good to good water for irrigation. Also from the diagram, fewer groundwater samples fall within good to permissible water for irrigation while few groundwater samples fall under permissible to doubtful water for irrigation, and one sample fall under doubtful to unsuitable water for irrigation. The samples that fall under permissible to doubtful water for irrigation indicate the presence of excess sodium in the groundwater. This possibly restricts the movement of water and circulation of air through the soils (Collins & Jenkins, 1996; Saleh et al., 1999). 218 University of Ghana http://ugspace.ug.edu.gh Figure 4. 32: Wilcox diagram for classifying the suitability of groundwater for irrigation. 4.2.5.3. Residual sodium carbonate (RSC) The amount of carbonate and bicarbonate in excess of alkaline earths (Ca+ Mg) affects the suitability of groundwater for irrigation. When the sum of bicarbonate and carbonate is in excess of calcium and magnesium, there may be a likelihood of complete precipitation of Mg2+ and Ca2+ (Raghunath, 1987). To compute the effects of bicarbonate and carbonate, (Eaton, 1950) residual sodium carbonate (RSC) the equation below is used (HCO -3 + CO 2- 3 ) – (Mg 2+ + Ca2+) ………………. Eq 4.14 In accordance with Eaton (1950), an elevated RSC value (>5 meq/L) in water leads to an increase in the adsorption of sodium in the soil. This can be harmful to the soil when the water is used for irrigation. This is due to the increase in soil sodium adsorption, which finally leads to soil blockage. In this study, calculation of the above RSC equation reveals that RSC in the boreholes drilled from 2014 to 2015 ranges from -0.90 to -0.05 meq/L. In 2016, the RSC content in the sampled hand dug wells and boreholes varies from -3.51 to 1.33 meq/L and - 1.93 to 1.30 meq/L, respectively. In 2017, the RSC in the sampled hand dug wells and the 219 University of Ghana http://ugspace.ug.edu.gh boreholes range from 2.57 to 1.92 meq/L and 1.88 meq/L to 1.05 meq/L, respectively. The RSC concentration for the groundwater in the study area is classified and presented in Table 4.50. In this study, all the groundwater sampled from 2014 to 2017 in both the aquifer of the Apollonian formation and the Birimian supergroup is suitable and safe for irrigation. Table 4.50: Groundwater suitability for irrigation based on RSC (After Eaton, 1950) RSC Water Class HDW HDW (2017) BH (2014 to BH (2016) BH (2016) (n=36 (n=30) 2015) (n=18) (n=44 (2017) (n = 54) <2.5 Suitable 36 30 18 44 54 2.5 - 5 Unsuitable >5 Harmful 4.2.5.4. Magnesium Hazard (MH) Darab and Szaboles (1964) proposed magnesium hazard (MH) concentration for groundwater suitability for irrigation. Calculation of MH in groundwater is given by the equation: 𝑀𝑔2+ 𝑀𝐻 = ( 2+ 2+) × 100………….. Eq 4.15 𝐶𝑎 + 𝑀𝑔 Where all equations are expressed I meq/L. Table 4. 51: Suitability of groundwater for irrigation based on MH% MH % Water BH BH HDW BH (2016) HDW BH Classification (2013) (2014- (2016) (n= 44) (2017) (2017) (n=30) 2015) (n= 36) (n= 30) (n= 54) (n=18) <50 Suitable 30 18 32 32 25 12 >50 Unsuitable 4 12 5 38 Computation of the above equation reveals that the MH for the boreholes drilled in 2013 and from 2014 to 2015 range from 18.46% to 47.45%, and 5.77% to 49.51%, respectively. In 2016, the MH for the hand dug wells and the boreholes vary from 2.48% to 72.41% and 4.37% to 90.03%, respectively. For the hand dug wells and the boreholes sampled in 2017, the MH content range from 2.95% to 81.44% and 2.75% to 92.15%, respectively. Table 4.51 gives the classification of groundwater suitability for irrigation based on MH in the groundwater of the study area. From the Table, it is seen that majority of the groundwater in all the above- mention years are suitable for irrigation and few are unsuitable. 220 University of Ghana http://ugspace.ug.edu.gh Generally, the spatial distribution map of MH for the groundwater (Fig 4.33) reveals that groundwater mostly in parts of the aquifer of the Apollonian formation with few in the aquifer of the Birimian supergroup represented by shades of red colour are unbefitting for irrigation. Likewise, the most suitable groundwater (hand dug wells and boreholes) quality for irrigation represented by shades of green concentrates in the aquifer of the Birimian supergroup with fewer representations in the aquifer of the Apollonian formation of the study area. Figure 4. 33: Spatial distribution map of groundwater suitability for irrigation in the study area based on MH%. 4.2.5.5 Permeability Index (PI) Sodium, bicarbonate, calcium, and magnesium are factors that affect the permeability of soils when there is a long-term irrigational practice. Doneen (1962), classified the suitability of water for irrigation based on the equation: 𝑁𝑎++ √𝐻𝐶𝑂3− 𝑃𝐼 = ( 2+ 2+ +) × 100 Eq 4.16 𝐶𝑎 + 𝑀𝑔 +𝑁𝑎 All ions are expressed in meq/L. 221 University of Ghana http://ugspace.ug.edu.gh Table 4. 52: Groundwater suitability for irrigation based on the Permeability Index (PI) PI Class PI% Water BH HDW, BH, 2016 HDW,2017,(n=30) BH,2017 Class (2014 – 2016 (n=44) (n=54 2015) (n= 36) (n=18) Class I ≥ 75 Suitable 13 27 30 24 44 Class II 25-75 Suitable 5 9 14 6 10 Class III < 25 Unsuitable Assessment of the above equation indicates that the PI value for the boreholes drilled from 2014 to 2015, ranges from 49.26% to 105.53%. That of the hand dug wells and boreholes sampled in 2016 ranges from 47.55% to 137.56%, and 39.92% to 157.92%, respectively. In addition, the PI for the hand dug wells and the boreholes sampled in 2017 varies from 49.98% to 194.85%, and 47.68% to 223.74%, respectively. From table 4.52 and Fig 4.34, it is observed that the groundwater in the aquifer of the Apollonian formation and the Birimian supergroup of the Lower Tano River Basin is suitable for irrigation based on Doneen permeability index (PI). Figure 4. 34: Groundwater suitability for irrigation based on Doneen permeability Index (PI) (Doneen 1964) (HDW =hand dug wells, BH =Boreholes) 222 University of Ghana http://ugspace.ug.edu.gh 4.2.5.6 Chlorinity Index In this study, the concentration of chloride and its suitability for agriculture is described. The description or classification is done based on Ramesh et al. (2012) classification. The authors pointed out that “irrigation water, which is saline, is poisonous to plants”. Figure 4.35 reveals that the chlorinity index for groundwater sampled from 2013 to 2017 in the aquifer of the Birimian supergroup and the Apollonian formation is suitable for all crops. Figure 4. 35: Groundwater suitability for crop production in the study area based on Chlorinity index (Ramesh et al. (2012)) (HDW = hand dug wells, BH = Boreholes) In general, assessment of the above-described chemical indices for groundwater suitability for irrigation reveals that most groundwater in the aquifer of the Birimian super group and the Apollonian formation in the Lower Tano River Basin is suitable for irrigation and a few are unsuitable. The obtained results are like works carried out by Edjah et al. (2015). The variation in WQI results is linked to the lithology of the study area and human activities The 223 University of Ghana http://ugspace.ug.edu.gh statistical summary results for the above-mentioned chemical indices are shown in Appendix 27,28, and 29. 4.2.6. Sub -Conclusion From the results of the second specific objective, it is observed that the surface water and groundwater sampled from the rocks of the Apollonian and the Birimian supergroup are acidic to neutral. Also, most of the surface water had low TDS/EC concentrations whiles the groundwater had short residence time due to low TDS concentration with low salt enrichment due to the EC values being less than 1500 μS/cm. The weathering of minerals from the rocks of the Apollonian formation and the Birimian supergroup are the main processes controlling the surface water and groundwater chemistry of the study area. Greater percentage of groundwater per the calculated WQI results were chemically suitable for drinking. Salinity was not a major concern when considering groundwater for irrigation in the Lower Tano River Basin. 4.3 Determination of the Hydrogeochemical Processes that produces the Chemical Characteristics or Compositions of the Aquifers. Under this section, the results of the third specific objective are discussed. The outcome of the results will provide a detailed hydrogeochemical description of the Birimian super group aquifer and the Apollonian formation aquifer within the Lower Tano River Basin. The results of the groundwater sampled in 2013 were not included due to lack of adequate field and hydrochemical data. Results of groundwater sampled from 2014 to 2017 is analyzed using models such as Durov (1948) diagram, Ficklin diagram (Ficklin et al., 1992), Piper (1944) diagram, (Gibbs, 1970) diagram, compositional diagrams, and hydrogeochemical modelling. The above-mentioned models are done with the aid of software’s like AquaChem 2015, Grapher and Microsoft excel 2016. The analyzed results are combined with the lithological formation of the aquifer to 224 University of Ghana http://ugspace.ug.edu.gh provide an insight into the evolution and chemical compositions of groundwater. Hydrogeochemical molar ratio is employed to help direct the evolution of groundwater and ion exchange processes (Aastri, 1994). For this, Chloro – Alkaline indices and different molar ratios as indicated by Schoeller (Schoeller, 1977) is employed. The analysis of the results is backed by hydrogeochemical modelling, where calculation of Saturation Index (SI) of the minerals in the rocks of the Apollonian and the Birimian supergroup of the study area are calculated using PHREEQC hydrogeochemical modelling software (Parkhurst et al., 2013). 4.3.1 Geochemical processes controlling the chemistry of groundwater 4.3.1.1. Ficklin diagram The Ficklin plot (Ficklin et al., 1992) is a scatter diagram in which the pH is plotted against the sum of the trace metals. This is a very effective and easy way of classifying water samples based on the differences in the sum of the base metal concentrations (Manjo et al., 2012). Differences in the sum of trace element concentrations of different groundwater samples help in differentiating various geological controls and this is usually based on their resultant chemistry. From the study, the Ficklin plot (Fig 4.36) exhibits two water types. Out of these water types, 70% of the groundwater are near – neutral low-metal water, due to their pH values which lies within six to nine. This suggests that the pH of most groundwater is not influence by the geochemistry of the aquifers. Further to the diagram (Fig 3.6), the remaining 30% of the groundwater lie in the acid –low- metal water. This type of water gives an indication that minority of the groundwater samples from both aquifers have low pH and this influenced the aquifer geochemistry. The Ficklin diagram has explained why positive and negative strong correlation exist between the pH and fewer trace element in the groundwater as previously discussed. 225 University of Ghana http://ugspace.ug.edu.gh Figure 4. 36: Ficklin diagram (Ficklin et al., 1992) showing variations in trace element concentrations as a function of pH for the groundwater in the study area. 4.3.1.2. Durov diagram (Durov, 1948) is a composite plot consisting of two ternary diagrams where the anions of interest are plotted against the cations of interest. The main purpose of the Durov diagram is to cluster the hydrochemical and physicochemical data points in order to identify groundwater samples with similar chemical compositions as well as reveal useful properties and relationships for the groundwater samples. This method is used to evaluate the various water types and present the absolute or total concentrations of cation or anions, pH, and TDS. In this study, the Durov diagram for the sampled groundwater within the study area is presented in Figure 4.37 a to 4.37 e. 226 University of Ghana http://ugspace.ug.edu.gh The Durov diagram (Durov 1948) for the boreholes drilled from 2014 to 2015 (Fig 4.37 a) reveals six geochemical processes. From the six geochemical processes (Fig 4.37 a), three boreholes (n=18) drilled in the aquifer of the Apollonian formation laid in field two, that is water rich in Ca – HCO -3 or Mg -HCO - 3 thus representing recharge water or water from a limestone aquifer (Belkhiri et al., 2012) and this will be explained further using Gibbs diagram in subsequent chapters and stable isotopes in the 4th specific objective. In addition, two boreholes drilled in the aquifer of the Birimian supergroup plots in field 3 that is water rich in Na-HCO -3 . This represents water undergoing reverse ion exchange (Belkhiri et al., 2012). Additionally, one borehole (n=18) drilled in the aquifer of the Apollonian formation and two boreholes drilled in the aquifer of the Birimian supergroup laid in field 4, that is water 2- rich in Ca- SO4 . This signifies water that is in contact with a contaminated source (Belkhiri et al., 2012) or sulphide minerals from the underlying geology. Five boreholes and three boreholes drilled in the aquifer of the Apollonian formation and the aquifer of the Birimian supergroup, respectively are plotting in field 5. This characterize water with no dominant cation or anion that is groundwater undergoing a possible simple dissolution or mixing (Belkhiri et al., 2012). Also, one borehole drilled in the aquifer of the Apollonian formation are seen in field six that is water rich in Na+- SO 2- 4 thus groundwater possibly receiving influences from anthropogenic sources (Belkhiri etal., 2012). Additionally, one borehole in the aquifer of the Apollonian formation is seen in field seven that is water rich in Na-Cl, suggesting ion exchange (Belkhiri et al., 2012) which will be explained further in subsequent chapters. 227 University of Ghana http://ugspace.ug.edu.gh Figure 4. 37a: Durov diagram (1948) of boreholes drilled from 2014 to 2015 in the Lower Tano River Basin. For the hand dug wells and boreholes sampled in 2016 (Fig 4.37 b and Fig 4.37 c), six geochemical processes are seen. Out of the six, four hand dug wells sampled from the aquifer of the Apollonian formation are plotting in field one, that is water rich in Ca2+ - HCO -3 or Mg 2+-HCO -3 representing recharging water. Also, fourteen hand dug wells (8 sampled from the aquifer of the Apollonian formation and 6 sampled from the aquifer of the Birimian supergroup) and three boreholes (two sampled from the aquifer of the Apollonian formation and one sampled from the aquifer of the Birimian supergroup) are seen in field two, that is water rich in Ca2+ - Mg2+ and HCO - - CO 2-3 3 . This signifies recharging groundwater or groundwater from a limestone aquifer (Lloyd, 1965). One borehole sampled from the aquifer of the Birimian supergroup is seen in field three, that is water rich in Na+ - HCO -3 , representing water undergoing reverse ion exchange (Belkhiri et al., 2012). Additionally, four hand dug wells sampled from the aquifer of the Apollonian formation 228 University of Ghana http://ugspace.ug.edu.gh and seven boreholes (five in the aquifer of the Apollonian formation and two in the aquifer of the Birimian supergroup) are plotting in field four that is water rich in Ca2+ -SO 2-4 . This discloses groundwater in contact with a contaminated source or sulphide minerals from the underlying geology. Thirteen hand dug wells (8 sampled from the Aquifer of the Apollonian formation and 5 taken from the aquifer of the Birimian supergroup) and thirty borehole samples (16 taken from the aquifer of the Apollonian formation and 14 sampled from the aquifer of the Birimian supergroup) are seen in field five that is water undergoing simple dissolution or mixing. Also, one hand dug well and three borehole samples all taken from the aquifer of the Birimian supergroup are plotting in field 6 that is water rich in Na+ - SO 2- 4 indicating water affected by anthropogenic sources (Zaporozec, 1972; Lloyd & Heathcote, 1985). Figure 4.37b: Durov diagram (1948) of hand dug wells sampled in 2016 within the Lower Tano River Basin. 229 University of Ghana http://ugspace.ug.edu.gh Figure 4.37c: Durov diagram (1948) of boreholes sampled in 2016 within the Lower Tano River Basin. For the hand dug wells and boreholes sampled in 2017 six and seven geochemical processes are observed, respectively. Out of the six and seven, three hand dug wells (two sampled from the aquifer of the Apollonian formation and one taken from the aquifer of the Birimian supergroup) and six boreholes (four sampled from the aquifer of the Apollonian formation and two sampled from the aquifer of the Birimian supergroup) are seen in field two, that is water rich in Ca2+ - Mg2+ and HCO -3 - CO 2- 3 suggesting water from a limestone aquifer or recharge areas. One hand dug well sampled from the aquifer of the Birimian supergroup is seen in field three that is water rich in Na+ -HCO -3 , hence water undergoing reverse ion exchange (Belkhiri et al., 2012). Also, six hand dug wells (two taken from the aquifer of the Apollonian formation and four sampled from the aquifer of the Birimian supergroup) and three boreholes (one taken from the aquifer of the Apollonian formation and two sampled from the aquifer of the Birimian supergroup) are showing in field four, that is water rich in Ca2+ - SO 2-4 . Additionally, fifteen hand dug well (eight 230 University of Ghana http://ugspace.ug.edu.gh sampled from the aquifer of the Apollonian formation and six taken from the aquifer of the Birimian supergroup) and thirty-two boreholes (twenty sampled from the aquifer of the Apollonian formation and twelve sampled from the aquifer of the Birimian supergroup) are seen in field five indicating water undergoing mixing or simple dissolution. Also, five hand dug well (three taken from the aquifer of the Apollonian formation and two sampled from the aquifer of the Birimian supergroup) and eleven boreholes (eight sampled from the aquifer of the Apollonian formation and three taken from the aquifer of the Birimian supergroup) are seen in field six that is water rich in Na+- SO 2- 4 thus water influenced by anthropogenic sources (Zaporozec, 1972; Lloyd & Heathcote, 1985). In addition, three boreholes sampled from the aquifer of the Apollonian formation are seen in field eight that is water rich in chloride and have non – dominant cation which may imitate inverse ion exchange of sodium and chloride water (Zaporozec, 1972; Lloyd & Heathcote, 1985). Figure 4.37d: Durov diagram (1948) of hand dug wells sampled in 2017. 231 University of Ghana http://ugspace.ug.edu.gh Figure 4.37 e: Durov diagram (1948) of boreholes sampled in 2017. 4.3.2. Hydrogeochemical facies and Evolution With groundwater flowing from the aquifer of the Birimian super group to the Apollonian formation (Fig 4.4a,b), a series of water–rock interactions might occur, which probably will increase the ion concentrations in the groundwater. In regulating the factors affecting the groundwater chemistry within the basin, it is vital to investigate the hydrogeochemical transition of groundwater along a flow path or direction. This will give a better understanding of rock – water interactions in the aquifer. Chebotarev (1955), through many studies, have identified that the major anions in a regional groundwater system follow the sequence: HCO - → HCO - + SO 2- → SO 2- + HCO - → SO 2- + Cl → Cl- + SO 2- → Cl- 3 3 4 4 3 4 4 along a flow path (Li et al., 2011). Variation of cations and anions along groundwater flow direction and hydrogeochemical facies are explained using Stiff and Piper diagram (Stiff (1951; Piper, 1944, Fig 4.38 a, b, c). 232 University of Ghana http://ugspace.ug.edu.gh The Piper diagram is used to identify the relationship that exist between the cations and anions in the groundwater. Those with similar quality plots together as a group. Also, the stiff diagram is used to explain the factors that controls the groundwater evolution. From Fig 4.38 a and 4.38 c, it is seen that the Piper diagram and the Stiff diagram gave similar groundwater water types and the groundwater evolution for 2014 to 2015 and 2017 samples are also similar. In figure 4.38a and figure 4.38c, three groundwater types are observed. These groundwater types are mixed (Ca-Mg-Cl) water, Na-Cl water and Ca-Mg-HCO -3 water. The mixed groundwater type indicates that the ions are equally dominant in the groundwater sampled from the aquifer of the Apollonian formation and the Birimian supergroup. The Na- Cl water suggests ion exchange processes which proposes that the 2014-2015 and 2017 groundwater samples was flowing from a recharge zone to a discharge zone. but this will be explained further in subsequent chapters. The Ca-Mg-HCO -3 groundwater implies that the aquifer of the Birimian supergroup and the Apollonian formation were recharged extensively by rainwater, but it will be explained further using stable isotopes of δ18O and δ2H in the 4th specific objective. For the groundwater evolution for 2014 – 2015 and 2017 samples (figure 4.38 a and 4.38 c), it is observed that the groundwater is evolving from Ca-HCO -3 water type (recharging water or fresh water) to a Na-Cl water type (recharge - discharge). 233 University of Ghana http://ugspace.ug.edu.gh Figure 4. 36a: Piper (1944) and Stiff (1951) diagram showing the transition of groundwater chemistry along a flow direction (2014 – 2015) For the groundwater sampled in 2016, four groundwater types are seen (Fig 4.38 b) and these water types are Na-Cl water type, mixed water type (Ca-Mg-Cl and Na-Ca- HCO -3 ), Ca- Mg-Cl-SO 2-4 water type, and Ca-Mg-HCO -3 water type. The Na-Cl, Ca-Mg-HCO - 3 and mixed groundwater types have been discussed previously, but the Ca-Mg-Cl-SO 2- 4 groundwater type infers that the groundwater has been in contact with a contaminated source or sulphide minerals from the underlying geology. Also, the groundwater evolves from Ca- 234 University of Ghana http://ugspace.ug.edu.gh HCO -3 (recharge water or fresh water) to Na-Cl water type (recharge to discharge) per the Stiff diagram shown in figure 4.38c. Figure 4.38 b: Piper (1944) and Stiff (1951) diagram showing the transition of groundwater chemistry along a flow direction (2016). 235 University of Ghana http://ugspace.ug.edu.gh Figure 4.38 c: Piper (1944) and Stiff (1951) diagram showing the transition of groundwater chemistry along a flow direction (2017). Table 4. 53: Characterization of groundwater types based on Piper (1944) Trilinear diagram and Stiff (1951) diagram. Type of water 2014 – 2015 (n=18) 2016 (n=80) 2017 (n=84) Na - Cl 7 28 30 Ca- Cl 6 6 2 Ca – HCO - 3 5 1 3 Na – SO 2-4 24 19 Na -HCO3 8 15 Mg – SO 2- 4 2 6 Ca -SO 2- 4 11 3 Mg-Cl 3 Mg-HCO - 3 3 The variation in groundwater evolution is attributed to rock- water interactions and ion exchange processes which will be explained further in subsequent chapters. 236 University of Ghana http://ugspace.ug.edu.gh The Piper diagram, the Stiff diagram, and Table 4.53 revealed Na-Cl type of water as the dominant groundwater type in the aquifer of the Apollonian formation and the Birimian supergroup. To account for the possible reasons behind the dominate Na-Cl groundwater type, Na/Cl molar ratio (Meybeck, 1987) are calculated for the sampled groundwater in the study area and the calculated results is shown in Table 4.54 to 4.56. Table 4. 54: Relationship of dissolved Na+ and Cl- in groundwater sampled from 2014 to 2015 Sample Id Location Rock Na+ (meq/l) Cl- (meq/l) Na/CL Formation BH 1 Newtown Apollonian 6.79 6.32 1.1 formation BH 2 Effasu Apollonian 0.58 0.56 1.0 formation BH 3 Mangyea Apollonian 0.60 0.74 0.8 formation BH 4 Mpeasem Apollonian 0.49 0.99 0.5 formation BH 5 Alumatuape Apollonian 0.32 0.28 1.1 formation BH 6 Jawey Apollonian 0.24 0.24 1.0 formation BH 7 Annor Adjaye SHS Apollonian 0.52 0.50 1.1 formation BH 8 Allengenzule Apollonian 0.71 0.71 1.0 formation BH 9 Agyeza Apollonian 0.99 0.85 1.2 formation BH 10 Ehoaka Apollonian 0.13 0.16 0.8 formation BH 11 Ehoaka Apollonian 0.13 0.16 0.9 formation BH 12 Twenen Apollonian 0.75 1.02 0.7 formation BH 13 Kengen Apollonian 0.43 0.64 0.7 formation BH 14 Elloyin Apollonian 0.82 0.88 0.9 formation BH 15 Kangbunli Apollonian 0.94 0.72 1.3 formation BH 16 Azuleleounu Apollonian 0.63 0.65 1.0 formation BH 17 Asanda Apollonian 0.85 0.76 1.1 formation BH 18 Asanda Apollonian 0.33 0.30 1.1 formation BH = Boreholes 237 University of Ghana http://ugspace.ug.edu.gh Table 4. 55: Relationship of dissolved Na+ and Cl- in groundwater sampled in 2016. Sample Community Rock Na Cl(meq/l) Na/Cl Sample Community Rock Na Cl Na/Cl number Formation (meq/l) number Formation (meq/l) (meq/l) HDW1 Esiama Apollonian 1.43 0.90 1.6 BH1 Salman Birimian 1.68 0.17 9.9 formation Supergroup HDW2 Nkroful Birimian 5.44 2.20 2.5 BH2 Kamgbuli Apollonian 0.94 0.23 4.1 supergroup formation rocks HDW3 Kikam Apollonian 3.12 2.65 1.2 BH3 Kamgbuli Apollonian 0.30 1.18 0.2 formation formation HDW4 Kikam Apollonian 3.76 2.88 1.3 BH4 Asemko Apollonian 1.63 0.68 2.4 formation formation HDW5 Aniwa Birimian 1.02 0.56 1.8 BH5 Ampaim Apollonian 1.22 1.02 1.2 supergroup formation rocks HDW6 Kikam Apollonian 1.14 0.85 1.3 BH6 Aniwa Birimian 1.22 0.34 3.6 formation Supergroup HDW7 Ampain Apollonian 0.23 0.51 0.4 BH7 Nkroful Birimian 1.98 0.73 2.7 formation Supergroup HDW8 Asanta Apollonian 1.87 0.62 3.0 BH8 Sanwoma Apollonian 1.47 1.47 1.0 formation formation HDW9 Nkroful Birimian 0.78 0.45 1.7 BH9 Aluku Birimian 3.75 1.52 2.5 supergroup Supergroup HDW10 Kikam Apollonian 1.78 1.18 1.5 BH10 Awiebo Apollonian 0.59 0.17 3.5 formation formation HDW11 Bomuakpole Birimian 1.33 0.62 2.1 BH11 Esiama Apollonian 0.69 0.34 2.0 Supergroup formation HDW12 Kikam Apollonian 1.94 1.47 1.3 BH12 Ampain Apollonian 2.81 0.96 2.9 formation formation HDW13 Ankobra Apollonian 4.25 4.85 0.9 BH13 Salman Birimian 0.34 0.45 0.8 formation Supergroup HDW14 Asanta Apollonian 0.85 0.79 1.1 BH14 Nkroful Birimian 1.52 0.56 2.7 formation Superroup HDW15 Gyegyekrom Apollonian 0.31 0.17 1.8 BH15 Bobrama Apollonian 1.29 0.79 1.6 formation formation HDW16 Kikam Apollonian 1.38 2.09 0.7 BH16 Bomuakpole Apollonian 0.81 0.90 0.9 formation formation 238 University of Ghana http://ugspace.ug.edu.gh HDW17 Asanta Apollonian 0.92 1.13 0.8 BH17 Sanwoma Apollonian 0.62 1.52 0.4 formation formation HDW18 Esiama Apollonian 2.96 1.86 1.6 BH18 Alabokazo Apollonian 0.23 0.39 0.6 formation formation HDW19 Aniwa Birimian 1.26 0.23 5.6 BH19 Aluku Birimian 1.01 0.34 3.0 supergroup supergroup HDW20 Esiama Apollonian 0.85 0.45 1.9 BH20 Alabokazo Apollonian 0.86 1.02 0.8 formation formation HDW21 Elubo Birimian 3.57 2.37 1.5 BH21 Asanta Apollonian 1.31 0.73 1.8 supergroup formation HDW22 Asanta Apollonian 2.98 1.64 1.8 BH22 Salaman Birimian 0.31 0.11 2.8 formation Supergroup HDW23 Ankobra Apollonian 2.78 1.75 1.6 BH23 Telekobokaso Birimian 1.27 1.02 1.3 formation supergroup HDW24 Esiama Apollonian 4.88 3.27 1.5 BH24 Aluku Birimian 1.79 1.41 1.3 formation supergroup HDW25 Esiama Apollonian 0.93 0.62 1.5 BH25 Esiama Apollonian 0.65 0.45 1.4 formation formation HDW26 Nkroful Birimian 1.47 0.51 2.9 BH26 Ankobra newsite 1.49 1.97 0.8 Supergroup Apollonian formation HDW27 Esiama Apollonian 2.32 1.64 1.4 BH27 Sanwoma Apollonian 1.24 0.51 2.4 formation formation HDW28 Gyegyekrom Apollonian 0.66 0.39 1.7 BH28 Old Kablasuazo Apollonian 1.49 0.68 2.2 formation formation HDW29 Elubo Birimian 0.99 0.62 1.6 BH29 Azulenloa Apollonian 0.81 0.62 1.3 Supergroup formation HDW30 Azulenloanu Apollonian 0.99 0.56 1.7 BH30 Azuleno Apollonian 1.29 1.13 1.1 formation formation HDW31 Half Assini Apollonian 1.25 0.68 1.8 BH31 Fante new site Apollonian 0.37 0.23 1.6 formation formation HDW32 Bobrama Apollonian 0.95 0.56 1.7 BH32 Elubo Birimian 2.11 1.18 1.8 formation supergroup HDW33 Asanta Apollonian 2.09 1.07 1.9 BH33 Bomuakpole Apollonian 1.17 0.39 3.0 formation formation HDW34 Sanwoma Apollonian 0.98 0.56 1.7 BH34 NyanZinli Apollonian 1.10 0.68 1.6 formation formation 239 University of Ghana http://ugspace.ug.edu.gh HDW35 Bobrama Apollonian 2.78 1.13 2.5 BH35 Atwibanso Apollonian 0.52 0.28 1.8 formation formation HDW36 Ankobra Apollonian 4.20 4.68 0.9 BH36 New Nzulezu Apollonian 0.16 0.17 1.0 formation formation BH37 NEW Ankasa Apollonian 0.40 0.28 1.4 formation BH38 Bonyere Apollonian 2.49 1.41 1.8 formation BH39 Atwibaso Apollonian 1.25 0.56 2.2 formation BH40 Awiafoto Apollonian 0.35 0.56 0.6 formation BH41 Aniwafuto(chips) Apollonian 0.70 0.17 4.1 formation BH42 New Nzulezu(2) Apollonian 0.63 2.37 0.3 formation BH43 Tiekobo 1 Apollonian 0.80 0.11 7.1 formation BH44 Bobrama Apollonian 1.05 1.13 0.9 formation HDW = Hand dug wells and BH = Boreholes 240 University of Ghana http://ugspace.ug.edu.gh Table 4. 56: Relationship of dissolved Na+ and Cl- in groundwater sampled in 2017 Sample Community Rock Na+ Cl- Na/Cl Sample Community Rock Na+ Cl+ Na/Cl Number Formation (meq/l) (meq/l) Number Formation (meq/l) (meq/l) HDW 1 Nkroful Birimian 0.80 0.68 1.2 BH1 Sanzule Apollonian 0.82 0.23 3.6 Supergroup formation HDW 2 Aluku Birimian 1.96 1.64 1.2 BH2 Nyaniba Apollonian 2.01 1.07 1.9 supergroup formation HDW 3 Kikam Apollonian 1.61 0.56 2.9 BH3 Ampaim Apollonian 0.92 0.85 1.1 formation formation HDW 4 Nkroful Birimian 0.53 0.51 1.0 BH4 Atwinbanso Apollonian 0.64 0.56 1.1 Supergroup formation HDW 5 Esiama Apollonian 1.76 3.38 0.5 BH5 Elubo Apollonian 1.96 1.58 1.2 formation formation HDW 6 Elubo Birimian 3.69 3.78 1.0 BH6 Awiefoto Apollonian 0.42 0.17 2.5 Supergroup formation HDW 7 Kikam Apollonian 1.61 1.30 1.2 BH7 Esiama Apollonian 3.73 2.54 1.5 formation formation HDW 8 Half Assini Birimian 0.47 0.73 0.6 BH8 Old Apollonian 0.48 0.56 0.9 Supergroup Kablazuaso formation HDW 9 Bomuakpole Apollonian 1.16 1.52 0.8 BH9 Fante New Apollonian 0.85 0.23 3.8 formation Town formation HDW Nkroful Birimian 1.15 0.45 2.6 BH10 Half Assini Apollonian 1.60 0.90 1.8 10 supergroup SHS formation HDW Kikam Apollonian 3.14 2.14 1.5 BH11 Salman Birimian 0.33 0.17 1.9 11 formation supergroup HDW Kikam Apollonian 1.03 2.26 0.5 BH12 Salman Birimian 0.73 0.17 4.3 12 formation supergroup HDW Elubo Birimian 3.18 3.78 0.8 BH13 Esiama Apollonian 2.39 1.30 1.8 13 Supergroup formation HDW Nkroful Birimian 4.79 1.58 3.0 BH14 Azuleno Apollonian 1.50 0.39 3.8 14 Supergroup formation 241 University of Ghana http://ugspace.ug.edu.gh HDW Aniwa Birimian 1.16 0.73 1.6 BH15 Bomuakpoley Birimian 0.58 0.34 1.7 15 Supergroup supergroup HDW Asemda Apollonian 0.80 0.11 7.1 BH16 Salman Apollonian 0.35 0.11 3.1 16 formation formation HDW Gyegyekrom Apollonian 0.37 0.17 2.2 BH17 Nkroful Birimian 0.63 0.56 1.1 17 formation Supergroup HDW Esiama Apollonian 1.48 0.90 1.6 BH19 Esiama Apollonian 0.60 0.45 1.3 18 formation formation HDW Ampaim Apollonian 0.36 0.56 0.6 BH20 Ankobra Apollonian 0.78 0.34 2.3 19 formation newsite formation HDW Eikwe Apollonian 3.78 1.52 2.5 BH21 Ampiam Apollonian 0.52 0.11 4.6 20 formation formation HDW Atuabo Apollonian 2.12 0.11 18.8 BH22 Nkroful Birimian 1.22 0.68 1.8 21 formation supergroup HDW Benyin Apollonian 3.50 2.99 1.2 BH23 New Nzulazu Apollonian 0.28 0.17 1.7 22 formation formation HDW Esiama Apollonian 4.47 0.73 6.1 BH24 Tiekobo 1 Apollonian 0.16 0.11 1.4 23 formation formation HDW Gyegyekrom Apollonian 0.26 0.11 2.3 BH25 Bobrama Apollonian 1.34 1.18 1.1 24 formation formation HDW Bobrama Apollonian 1.58 1.30 1.2 BH26 New Nzulazu Apollonian 0.70 0.06 12.5 25 formation formation HDW Elubo Birimian 0.83 0.68 1.2 BH27 Bonyere Apollonian 1.15 0.51 2.3 26 Supergroup formation HDW Kikam Apollonian 1.25 0.79 1.6 BH28 Kamgbunli Apollonian 1.13 0.90 1.3 27 formation formation HDW Kikam Apollonian 1.77 1.41 1.3 BH29 Aluku Birimian 1.97 1.64 1.2 28 formation Supergroup HDW Azulenuano Apollonian 1.07 0.56 1.9 BH30 Atwinbanso Apollonian 0.75 0.62 1.2 29 formation formation HDW Aniwa Apollonian 1.03 0.39 2.6 BH31 Asemko Apollonian 0.72 0.23 3.2 30 formation formation 242 University of Ghana http://ugspace.ug.edu.gh BH32 Salman Birimian 0.74 0.11 6.6 Supergroup BH33 Azeneluno Apollonian 1.50 0.39 3.8 formation BH34 Aluku Birimian 0.52 0.34 1.5 Supergroup BH35 Alabokazo Apollonian 0.23 0.96 0.2 formation BH36 Kamgbunli Apollonian 0.36 0.34 1.1 formation BH37 Ankasa Apollonian 0.51 0.96 0.5 formation BH38 Telekobokaso Birimian 1.42 0.56 2.5 Supergroup BH39 Alabokazo Apollonian 0.96 0.62 1.5 formation HDW =Hand dug wells and BH = Boreholes 243 University of Ghana http://ugspace.ug.edu.gh The computation of the Na/Cl molar ratio (Table 4.54 – 4.56) for 2014 to 2015 borehole samples reveals that, 40% of the boreholes (n=18) is greater than one, 38% is less than one and 22% o is equal to one. In 2016, the calculated Na/Cl molar ratio results for the sampled groundwater indicates that 78.8% of the groundwater (n= 80) is greater than one, 19.25% is less than one and 2% is equal to one. In 2017, the calculated Na/Cl molar ratio results show that 67.9% of the groundwater (n=84) is greater than one, 30.14% is less than one and 2% is equal to one. Assessment of the above Na/Cl molar ratio reveals that most groundwater in the Lower Tano River Basin have Na+ /Cl- molar ratio to be greater than one. This implies that ion exchange processes (Garrels & Mackenzie, 1967) are the dominant factor controlling sodium and chloride ion content in the aquifer of the Apollonian formation and the Birimian supergroup rocks. Additionally, few groundwater samples had Na/Cl molar ratio greater than one and this represents Na+ released from silicate mineral (feldspar, hornblende, plagioclase, granite etc.) weathering (Garrels & Mackenzie, 1967). Lesser groundwater samples had Na+ /Cl- molar ratio to be equal to one. indicating the presence of halite dissolution (Meybeck, 1987) in the aquifer of the Apollonian formation and the Birimian supergroup rocks. In the study area, halite is absent in the general geology (Fig 3.3 and 3.4) but if halite is present then it might be through evaporation, which concentrates in the soil zone, before moving into the aquifer by direct rainfall infiltration. Little groundwater samples had Na+ / Cl- lesser than one. This suggests minimal seawater intrusion (Meybeck, 1987). 4.3.4 Groundwater mineralization Processes A clear understanding of the main factors affecting the chemical quality of groundwater mineralization is important for groundwater resource development and protection. To do this, Gibbs (1970) diagram is employed. Gibbs (1970) proposed a diagram, which includes two sub- 244 University of Ghana http://ugspace.ug.edu.gh diagrams. One of the sub-diagrams represent the relationship between TDS and the weight ratio of Cl- versus (Cl- + HCO - 3 ) and the other denotes the relationship between TDS and the weight ratio of Na+ versus (Na+ + Ca2+). The geochemistry behind the basis of the Gibbs (1970) diagram is the geological formations and the composition of groundwater. In the diagram, three distinct fields are established. These fields are rock dominance, evaporation dominance, and precipitation dominance (Li et al., 2013 a; Gibbs, 1970). The Gibbs (1970) diagram (Fig 4.39 a, b) plotted for 2014 to 2015, 2016 and 2017 hydrochemical data suggests that rock weathering and rainfall is the chemical quality controlling the groundwater mineralization of the aquifer of the Birimian supergroup and the Apollonian formation. The groundwater lying in the rock dominance zone (Fig 4.39 a, b) has explained the results obtained for the Person correlation matrix, the dominance of sodium, and calcium in the groundwater of the study area as well as the results of the Fickling diagram discussed in subsequent chapters. Also, the groundwater lying in the rainfall dominance zone has explained the Ca-HCO -3 groundwater type obtained from the Durov and Piper diagram as well as the low recorded TDS content for the groundwater. But it will be explained further using stable isotopes of oxygen-18 and deuterium in the 4th specific objective. 245 University of Ghana http://ugspace.ug.edu.gh Figure 4. 37a: Gibbs (1970) diagram indicating the general mechanisms of groundwater evolution Figure 4.39 b: Gibbs (1970) diagram indicating the general mechanisms of groundwater evolution 246 University of Ghana http://ugspace.ug.edu.gh 4.3.4.1 Rock weathering Since rock weathering is one of the major sources of chemical quality controlling the groundwater mineralization of the Apollonian formation aquifer and the aquifer of the Birimian supergroup, compositional diagrams are used to interpretate and confirm the accession. This is done by plotting Na+ against Cl- (Fig 4.40) and Na+ against HCO -3 (Fig 4.41) For Na+ vs Cl- - plot (Fig 4.40) and Na+ vs HCO3 plot (Fig 4.41), a strong positive correlation 3 is observed. Also, most of the groundwater samples are plotting above the 1:1 equiline. This suggests ion exchange (Hounslow, 1995) process. Fig 4.40 and 4.41 has explained the Piper diagram and the Stiff diagram where most samples were Na-Cl groundwater type and evolving from Ca-HCO - to Na-Cl and Ca-SO 2-3 4 to Na-Cl. The effects of ion-exchange processes in the groundwater implies a change in aquifer chemistry along a flow direction. Also, looking at the diagrams (Fig 4.40 and 4.41), it is seen that few groundwater samples are plotting on or near the 1:1 equiline. This shows that the hydrochemical evolution of groundwater sampled from the aquifer of the Birimian super group and the Apollonian formation might be controlled by the effect of limited dissolve carbonate equilibria and limited mixing with rainfall (Hounslow, 1995). This explains the Gibbs diagram where 50% of the groundwater was lying in the rock dominance zone and 50% was lying in the rainfall dominance zone. 247 University of Ghana http://ugspace.ug.edu.gh Figure 4. 38: Relationship between Cl- and Na+ drawn for the sampled groundwater in the study area. Figure 4. 39: Relationship between Na+ and HCO - 3 drawn for the sampled groundwater in the study area. The hydrochemical data of groundwater sampled from the aquifer of the Apollonian formation 4 and the Birimian supergroup is plotted on Ca2+ + Mg2+ vs. SO 2- 4 + HCO - 3 diagram (Fisher & Mulican, 1997). From the diagram (Fig 4.42), 5% of the sampled groundwater is clustered around the 1:1 equiline. This reveals dissolution of carbonate minerals from the underlying geology. Also, 55% of the sampled groundwater are lying below the 1:1 equiline representing excess SO 2-4 + HCO - 3 . This suggests weathering of silicate minerals from the underlying geology. Figure 4.42 has confirmed the Gibbs diagram where 50% of the groundwater were lying in the rock dominance zone. Additionally, the remaining 40% of the groundwater samples are plotting above the 1:1 equiline revealing excess magnesium and calcium (reverse ion - exchange) ion concentration (Fisher & Mulican, 1997). The strong positive correlation 248 University of Ghana http://ugspace.ug.edu.gh between Ca2+ + Mg2+ and SO 2- + HCO - 4 3 reveals the occurrence of rock weathering (Hounslow, 1995) as a major factor controlling the groundwater chemistry of the study area. Figure 4. 40: Relationship between (Ca + Mg) vs (SO 2-4 + HCO -3 ) in the sampled groundwater within the study area. Groundwater undergoing ion exchange would typically plot along a line whose slope is -1, whiles groundwater plotting close to the zero value on the x-axis is not influenced by ion exchange (Jankowski et al., 1998). In this study, the most likely additional sources of Mg2+ and Ca2+ contribution to the groundwater chemistry apart from cation- exchange is the dissolution of carbonate minerals and the weathering of silicate minerals as explained previously. To explain further, Ca2+ + Mg2+ - HCO - - SO 2- vs Na+ - Cl-3 4 (McClean & Jankowski, 2000) plot in meq/L is used (Fig 4.43). The diagram (Fig 4.43) shows that groundwater sampled from 2014 to 2015 plots along a line with slope (-0.04) (close to the zero value of the x-axis). This indicates that cation exchange processes (McClean & Jankowski, 2000) are not influencing the chemistry of the aquifers. Also, groundwater sampled in 2016 and 2017 plots along a line with slope -0.9 and -0.8 (away from the zero value of the x-axis), respectively (Fig 4.43). This suggests that in the rainy season, the chemistry of the aquifers is influenced by cation-exchange processes (McClean & Jankowski, 2000). 249 University of Ghana http://ugspace.ug.edu.gh Figure 4. 41: Relationship between Ca2+ + Mg2+ – HCO -3 - SO 2-4 and Na-Cl for the sampled groundwater within the study area (2014 – 2017). \A plot of Na+ + K+ vs TC (Total cations) for groundwater sampled from 2014 to 2017 is also drawn. From the plot (Fig 4.44), it is seen that all the groundwater sampled from the aquifer of the Apollonian formation and the Birimian supergroup are clustering along the equiline in a linear spread. This reveals an increasing contribution of alkalis with increasing dissolved solids (Singh et al., 2013) in both aquifers. 250 University of Ghana http://ugspace.ug.edu.gh Figure 4. 42: Relationship between Na+ +K+ and Total cations in the sampled groundwater in the study area. 4.3.4.1.1 Cation Exchange Cation exchange is an important natural process that can have significant impact on the evolution of the aquifer chemistry (Li et al., 2013 a). In further studying the occurrence of cation exchange reactions in the groundwater taken from the aquifer of the Apollonian formation and the Birimian supergroup, two Chloro Alkaline Indices (CAI - 1 and CAI -2) proposed by Schoeller (1965) are used. These indices are expressed as: (𝑁𝑎+𝐾) 𝐶𝐴𝐼 − 1 = 𝐶𝑙 − Eq 4.17 𝐶𝑙 (𝑁𝑎+𝐾) 𝐶𝐴𝐼 − 2 = 𝐶𝑙 − + 𝐻𝐶𝑂3 + 𝐶𝑂3 + 𝑁𝑂3 Eq 4.18 𝑆𝑂4 Where all values are expressed in meq/L. Results from the computation of the above equations is shown from Appendix 30 to 34. I f negative values for the two indices are achieved from the results, reverse reaction expressed as Ca 2+ + 2NaX = 2Na+ + CaX2 is probably taking place. Likewise, if positive values for the 251 University of Ghana http://ugspace.ug.edu.gh two indices are obtained, cation exchange expressed as 2Na + + CAX 2+ 2 = Ca + 2NaX is occurring. Results obtained from the calculation of the two-chloro alkaline indices are plotted and shown in Fig 4.45 a and 4.45 b. Figure 4. 43a: Bivariate plot for studying cation exchange in the sampled groundwater (2014 – 2015) within the Lower Tano River Basin Fig 4.45b: Bivariate plot for studying cation exchange in groundwater (2016 and 2017) within the Lower Tano River Basin From the above diagrams (Fig 4.45 a and Fig 4.45 b), it is observed that most of the groundwater are plotting in the negative zone. This indicate that majority of the groundwater sampled in the aquifer of the Apollonian formation and the Birimian super group have undergone reverse cation- exchange processes. However, few of the groundwater samples taken from the aquifer of the Apollonian formation and the Birimian supergroup have also undergone cation- exchange and are seen in the positive zone. The cation- exchange processes 252 University of Ghana http://ugspace.ug.edu.gh decrease the calcium content whiles increasing the sodium concentration in the groundwater. Likewise, the reverse cation - exchange processes increase the calcium content whiles decreasing the sodium content in the groundwater (Marghade et al., 2011). To further investigate the effects cation- exchange (including reverse cation exchange) has on the salinity of groundwater in the aquifer of the Apollonian formation and the Birimian supergroup, a bivariate plot of (Ca 2+ + Mg2+) – ( HCO - + SO 2- + + -3 4 ) and (Na + K - Cl ) is drawn 2+ and (Ca + Mg 2+) – ( HCO -3 + SO 2- 4 ) 2+ 2+ suggests the increment or decrement of (Ca + Mg ) caused by processes excluding precipitation/dissolution of limestones (dolomite, calcite). Na+ + K+ - Cl - represents the increment of Na+ induced by processes excluding halite dissolution, (Li et al., 2014 b). If cation- exchange is the main process affecting groundwater salinity, the relationship between the above- mentioned ions will be linear and the slopes will that the relationship between (Ca2+ 2+ - 2-be close to -1. Figure 4.46, indicates + Mg ) – ( HCO3 + SO4 ) and (Na+ + K+ - Cl -) for the groundwater sampled from 2014 to 2017 conforms to the following linear equations, thus: y= -0.023x +0.2506, R = 0.04, in 2014 to 2015 y=-0.3587x - 0.1371, R =0.39 in 2016 and y=-0.6648x + 0.143, R = 0.75 in 2017. From the above equations, it is mathematically observed that the fitted slopes are not closer to the theoretical value of -1 for groundwater sampled from 2014-2015 and 2016. This shows that cation - exchange between calcium, magnesium and sodium is not the main possible hydrochemical process affecting the salinity of fewer boreholes developed in 2014 to 2015 and groundwater sampled during the rainy season. Similarly, the groundwater sampled in 2017 had a fitted slope approximately equal to -1. This suggests that cation - exchange between calcium, magnesium and sodium is the main hydrochemical processing controlling the salinity of groundwater during the dry season. The differences between the slopes and the theoretical value of -1 for the groundwater sampled from the aquifer of the Apollonian formation and the Birimian supergroup indicates that groundwater salinity is not affected by cation- exchange 253 University of Ghana http://ugspace.ug.edu.gh processes, but other factors such rainfall as observed in the Piper and Gibbs diagrams and this will be further explained using stable isotopes of δ18O and δ2H. Figure 4. 44: Bivariate diagram for cation exchange reaction in groundwater sampled from the aquifer of the Apollonian formation and the Birimian supergroup. 4.3.4.2 Precipitation (Rainfall) Further to the Gibbs diagram, another dominant factor controlling groundwater mineralization in the aquifer of the Birimian supergroup and the Apollonian formation is rainfall. The high rainfall amount (Fig 1.3 to 1.6) recorded and observations made by Edjah et al. 2015 indicates that rainfall influence the groundwater mineralization and that can increase Na+ and Cl- levels in the groundwater of the two aquifers (Hounslow, 1995). Generally, evaporation causes an increase in the concentrations of chemical ions in groundwater and if it is dominant and no ions are precipitated, the Na+ /Cl- ratio is unchanged 254 University of Ghana http://ugspace.ug.edu.gh (Jankowski & Acworth, 1997). A plot of Na/Cl vs EC would also give a horizontal line, which suggests concentration by transpiration and evaporation. In this study, the plot (Fig 4.47) illustrates a drop in Na/Cl ratio and decrease in EC in the - groundwater sampled from 2014 – 2017. This is potentially from the loss of TDS and HCO3 due to rainfall recharge with short residence time. This explains why low TDS content was measured in all the groundwater samples taken from the aquifer of the Apollonian formation and the Birimian supergroup rocks. Figure 4. 45: Relationship between Na/Cl and EC in the sampled groundwater within the Lower Tano River Basin. 255 University of Ghana http://ugspace.ug.edu.gh 4.3.5. Hydrogeochemical modelling In this study, the controls on natural chemistry of groundwater in the aquifer of the Apollonian formation and the aquifer of the Birimian supergroup is discussed using hydrochemical model (PHREEQC). Also, the chemical reactions in the various aquifer systems (Garrels & Mackenzie, 1971) are defined. One speciation in PHREEQC used in this study is the saturation indices (SI). The saturation indices (SI) are quantitative deviation of groundwater from equilibrium with respect to its dissolved minerals and its defined (Garrels & Mackenzie, 1971; Stumm & Morgan, 1981) as: 𝐼𝐴𝑃 𝑆𝐼 − 𝐿𝑜𝑔 𝐸𝑞 4.19 𝐾𝑠𝑝 Where Ksp is the thermodynamic equilibrium constant for the mineral at the measured temperature and IAP is the Ion Activity Product of the mineral-water reaction. A positive SI indicates that the solution is supersaturated with the occurrence of precipitation. A negative SI indicates that the solution is under- saturated with dissolution occurrences. An SI of ± 0.5 indicates equilibrium conditions. Considering the general geology (Fig 3.3 and 3.4) of the Lower Tano River Basin, Aragonite, Albite, Quartz, Amorphous Silica, Ca-Montmorillonite, Gibbsite, K-feldspar, K-mica, Kaolinite, Calcite, Dolomite, and Chalcedony are considered as possible mineral phases existing in the aquifer of the Apollonian formation and the Birimian supergroup. To perform the hydrogeochemical modelling on the groundwater in both aquifers, cation- exchange between calcium and sodium are taken into consideration due to the essential processes of calcium and magnesium. From the groundwater geochemical modelling, it is observed that the saturation index (SI) for carbonate minerals in almost all the groundwater samples are under-saturated with aragonite, dolomite, and calcite (Fig 4.48) except for three groundwater samples. The under saturation with respect to the above-mentioned minerals suggests that carbonates and silicate 256 University of Ghana http://ugspace.ug.edu.gh minerals from the underlying geology have dissolved and weathered respectively without reaching equilibrium. This is due to short residence time, and a fast-flowing velocity (Halim et al., 2010). Also, the remaining three groundwater samples all taken from the aquifer of the Birimian supergroup rocks are saturated with aragonite. This indicates that calcium ion from silicate minerals (Hornblende, etc.) in the underlying geology have reached equilibrium. This is due to long residence time and a slow flowing velocity (Halim et al., 2010) due to highly fractured rocks of the Birimian. Figure 4. 46: Saturation index of carbonate minerals in the groundwater within the Lower Tano River Basin. In fig 4.49, the saturation index of silicate minerals for most groundwater sampled in the aquifer of the Apollonian and the Birimian supergroup are undersaturated with chalcedony, quartz, and amorphous silica. This means that silica in the underlying geology exist in other forms and have not reached equilibrium due to short residence time and rainwater recharge (Halim et al., 2010). Additionally, four groundwater samples are supersaturated with chalcedony (Fig 4.49). The super saturation could be linked to input from excess silica from the underlying geology. 257 University of Ghana http://ugspace.ug.edu.gh Figure 4. 47: Saturation index of silicate minerals in groundwater within the Lower Tano River Basin. The saturation index (SI) for alumino- silicate minerals (Fig 4.50) in the groundwater is in the order of K– mica > kaolinite> gibbsite > Ca-montmorillonite > K feldspar. More variation is also noted in SI for all the alumino-silicate minerals in groundwater taken from the aquifer of the Apollonian formation and the Birimian supergroup. This suggests a possible differential intensities of rock weathering. 258 University of Ghana http://ugspace.ug.edu.gh Figure 4. 48: Saturation index of alumino silicates in groundwater within the Lower Tano River Basin. The activity ratio of the major ions in the groundwater sampled from both aquifer of the Apollonian formation and the Birimian supergroup are also plotted on mineral stability diagrams of + 2+ CaAl Si O + 2H + 3H O ↔ Al Si O (OH) + Ca + H SiO 2 2 8 2 2 2 5 4 4 2 + + 2NaAlSi O + 2H + 9H O ↔ Al Si O (OH) + 2Na + 4H SiO (aq) (Belkhiri et al., 2010). 3 8 2 2 2 5 4 4 2 The stability diagrams (Fig 4.51a to 4.51d) will help understand the controls of natural chemistry of groundwater. From Figure 4.5a, calcium in 42 groundwater samples (n=58) with 22 taken from the aquifer of the Birimian supergroup and 20 taken from the aquifer of the 259 University of Ghana http://ugspace.ug.edu.gh Apollonian formation lie in the kaolinite stability field. This suggests dilution of calcium ion. The calcium content in the remaining 16 groundwater samples all taken from the aquifer of the Apollonian formation plots in the gibbsite stability fields. This suggests that as Kaolinite is being formed, the pH of the groundwater is decreased (Belkhiri et al., 2010). This is another reason why some of the groundwater sampled from the aquifer of the Apollonian formation were acidic. Also, the flow of groundwater is unrestricted due to unconsolidated rocks of the Apollonian. Figure 4.49a Calcium stability diagram for groundwater samples within the Lower Tano River Basin Figure 4.51 b shows that magnesium in 20 groundwater samples taken from the aquifer of the Apollonian formation plots in the gibbsite stability field. This indicates that as Kaolinite is being formed the pH of the groundwater is reduced and the flow of groundwater is unrestricted due to unconsolidated rocks of the Apollonian. Also, the magnesium ion in 6 groundwater sampled from the aquifer of the Birimian supergroup plots in the Mg- montmorillonite stability 260 University of Ghana http://ugspace.ug.edu.gh fields. This is due to the weathering of granites, hornblende etc. from the underlying geology. Also, the flow of groundwater is restricted due to highly fractured rocks of the Birimian. Additionally, magnesium in 32 groundwater samples from the aquifer of the Apollonian formation and the Birimian supergroup plots in the Kaolinite stability fields. This suggests dilution of Mg2+ ion. Figure 4.51b: Magnesium stability diagram for groundwater samples within the Lower Tano River Basin. Fig 4.51c shows that potassium in 13 groundwater samples all taken from the aquifer of the Birimian supergroup rocks plots in the K-feldspar stability field. This suggests a possible dissolution of amorphous silica producing kaolinite. In addition, potassium in 40 groundwater samples both taken from the aquifer of the Apollonian formation and the Birimian supergroup plots in the muscovite stability field. This suggests dissolution of kaolinite and the formation of muscovite and K – feldspar. Potassium in 5 groundwater samples all taken from the aquifer of the Apollonian formation plots in the gibbsite stability fields indicating that the flow of water in the aquifer are unrestricted (thus initial stage of weathering) and have a short residence time resulting in very low mineralization thus possibly producing fresh groundwater. 261 University of Ghana http://ugspace.ug.edu.gh Fig 4.51c: Potassium stability diagram for groundwater samples within the study area. Fig 4.51d also reveals that sodium in 13 groundwater samples all taken from the aquifer of the Apollonian formation plots in the gibbsite stability field suggesting the formation of Kaolinite with decreasing pH of the groundwater (Belkhiri et al., 2010) and the flow of groundwater is unrestricted. Also, sodium in 10 groundwater samples all taken in the aquifer of the Birimian supergroup rocks plots in the Na-Montmorillonite stability field. This suggests silicate minerals (hornblende, plagioclase, feldspar etc.) weathering. Also, the groundwater in the Na- montmorillonite fields indicate that the flow of groundwater is restricted due to highly fractured rocks of the Birimian and decreased interconnection between the fractures that control the movement of groundwater in the aquifer of the Birimian super group. Both Mg – montmorillonite and Na- montmorillonite in the aquifer of the Apollonian formation and the Birimian super group reveals longer residence time with high degree of rock-water interactions. In addition, sodium in 35 groundwater samples plots in the Kaolinite stability fields. This indicates a probable dilution of sodium ion concentration and a decrease in pH in the groundwater. 262 University of Ghana http://ugspace.ug.edu.gh Fig 4.51d: Sodium stability diagram for groundwater samples in the study area. The diagram (Fig 4.51a to Fig 4.51d) reveals kaolinite stability field as the most dominant followed by gibbsite and montmorillonite. The dominance of Kaolinite in the sampled groundwater indicates that infiltrating water enhanced by soil CO2 might possibly reacts with limestone and clay minerals from the aquifer of the Apollonian formation and silicate minerals particularly plagioclase feldspar, biotite etc. from the aquifer of the Birimian super group. The infiltrating water releases Ca2+, Mg2+, Na+ and HCO -3 , resulting in a more silica-rich clay mineral imitative of the clay minerals and silicate minerals contained in the aquifer of the Apollonian formation and the Birimian super group, respectively. This infers that incongruent dissolution controls the natural chemistry of groundwater in the aquifer of the Apollonian formation and the Birimian supergroup of the Lower Tano River Basin. This is explained further using HCO -3 and SiO2 ratio (Hounslow, 1995). In this ratio, silicate weathering releases a considerable amount of silica into groundwater, since carbonate dissolution will not release silica into t h e groundwater. Hence, groundwater with HCO -3 / SiO2 > 10 suggests carbonate mineral weathering as the dominant factor controlling the natural chemistry of the groundwater, whiles groundwater with HCO -3 / SiO2 < 10 shows silicate weathering as the dominant factor controlling the natural groundwater chemistry. The computed values are shown in table 4.57. 263 University of Ghana http://ugspace.ug.edu.gh Table 4. 57: Values and HCO -3 / SiO2 values showing the dominant weathering activity of groundwater within the Lower Tano River Basin. Sample HCO - SiO Na+ K+ Cl- HCO - /SIO + + -3 2 3 2 SIO2/Na +K - Cl SIy = SIg-SI k number 1 48.77 -3.08 32.94 18.66 45.99 -15.83 -0.55 2.66 2 12.19 -1.36 11.94 0.56 12.00 -53.79 -2.71 -0.75 3 60.96 -2.39 17.32 13.19 23.99 -25.51 -0.37 0.18 4 58.52 -2.49 13.73 1.58 4.00 -23.50 -0.22 0.18 5 21.95 -1.29 33.63 17.35 45.99 -17.02 -0.26 -1.61 6 121.92 BDL 32.70 1.14 19.99 0.00 0.00 0.13 7 60.96 -1.46 21.46 8.34 14.00 -41.75 -0.09 -0.66 8 85.34 -3.10 77.82 36.59 89.97 -27.53 -0.13 0 9 60.00 BDL 16.55 0.82 8.00 0.00 0.00 0.69 10 19.51 -0.84 7.67 0.74 6.00 -23.22 -0.35 -2.59 11 75.00 BDL 10.80 3.57 25.99 0.00 0.00 0.44 12 39.01 -0.50 37.10 0.70 41.99 -78.02 0.12 -4.71 13 24.38 -1.06 11.73 1.14 33.99 -23.00 0.05 -2.04 14 14.63 BDL 7.55 1.53 4.00 0.00 0.00 0.83 15 219.45 -3.09 17.03 0.82 4.00 -71.02 -0.22 1.2 16 14.63 -2.50 11.13 0.33 19.99 -5.85 0.29 1.97 17 26.82 -3.10 13.79 2.12 16.00 -8.65 36.45 -0.14 18 24.38 BDL 14.69 1.43 19.99 0.00 0.00 -1.24 19 20.00 -3.08 5.94 0.74 4.00 -6.49 -1.15 1.61 20 36.58 -1.71 24.57 2.99 14.00 -21.39 -0.13 -0.2 21 353.56 -1.16 34.05 8.06 31.99 -304.79 -0.11 -2.8 22 121.92 BDL 32.70 1.14 19.99 0.00 0.00 0.13 23 12.19 -1.89 11.08 0.66 17.99 -6.45 0.30 1.05 24 231.64 BDL 100.10 37.45 55.98 0.00 0.00 0.94 25 48.77 BDL 44.98 7.45 55.98 0.00 0.00 -0.12 26 17.07 -2.32 45.02 7.61 57.98 -7.36 0.43 1.99 27 110.00 -1.11 22.06 3.56 21.99 -99.10 -0.31 -2.01 28 14.63 BDL 32.18 6.94 53.98 0.00 0.00 0.54 29 34.14 -0.58 10.04 0.78 17.99 -58.86 0.08 -2.01 30 75.00 -1.29 10.80 3.57 25.99 -58.14 0.11 -1.2 31 70.00 -1.12 13.34 0.76 12.00 -62.50 -0.53 0 32 9.75 -2.61 6.47 0.75 6.00 -3.74 -2.13 2.45 33 2.44 -1.16 73.00 8.30 133.96 -2.10 0.02 -1.05 34 24.38 -1.05 24.15 6.53 25.99 -23.22 -0.22 -2.05 264 University of Ghana http://ugspace.ug.edu.gh 35 17.07 -1.32 45.02 7.61 57.98 -12.93 0.25 0 36 34.14 -1.83 8.33 0.80 12.00 -18.66 0.64 0 37 14.63 -2.61 32.18 6.94 53.98 -5.61 0.18 1.48 38 2.44 -2.50 17.24 1.79 21.99 -0.98 0.84 3.85 39 24.38 -0.54 11.73 1.14 33.99 -45.15 0.03 -3.09 40 50.00 -2.78 7.56 0.19 6.00 -17.99 -1.59 2.52 41 197.64 -1.19 156.00 13.70 224.00 -166.08 0.02 -2.39 42 46.36 -1.52 13.30 2.60 19.80 -30.50 0.39 -3.5 43 37.82 -1.52 13.90 1.00 26.20 -24.88 0.13 -2.99 44 91.50 -1.30 11.30 1.50 35.10 -70.38 0.06 -2.99 45 17.08 -1.42 7.30 0.80 10.00 -12.03 0.75 -3.47 46 47.58 -1.67 5.60 2.60 8.40 -28.49 8.35 -2.82 47 28.06 -1.59 12.00 1.70 17.60 -17.65 0.41 -2.57 48 10.98 -1.56 16.40 0.20 25.30 -7.04 0.18 -2.01 49 31.72 -1.46 22.80 6.00 30.00 -21.73 1.22 -3.15 50 197.64 -1.65 3.00 0.90 5.50 -119.78 1.03 -2.04 51 192.76 -1.65 3.10 0.90 5.50 -116.82 1.10 -2.04 52 23.18 -1.28 17.30 1.70 36.00 -18.11 0.08 -4.1 53 7.32 -1.54 9.90 0.50 22.70 -4.75 0.13 -2.29 54 6.10 -1.86 18.80 1.30 31.30 -3.28 0.17 -1.3 55 208.62 -0.70 21.60 2.80 25.50 -298.03 0.64 -4.2 56 21.96 -1.16 14.50 2.00 22.90 -18.93 0.18 -3.16 57 28.06 -1.55 19.60 8.90 27.10 -18.10 -1.11 -2.52 58 31.72 -1.39 7.70 0.20 10.70 -22.82 0.50 -3.28 265 University of Ghana http://ugspace.ug.edu.gh From table 4.57, it is seen that silica in the sampled groundwater ranges from BDL (below detection limit) to 38.83 mg/L. All the groundwater samples had HCO -3 / SiO2 less than 10. The computed HCO -3 / SiO2 reveals rock weathering as the main geochemical process contributing to the formation of kaolinite in the aquifer of the Apollonian formation and the Birimian supergroup and it’s in line with the Gibbs (1970) diagram illustrated in previous chapters. Also computed SiO2 / (Na + + K+ - Cl-) ratio indicates that 98% of the sampled groundwater (n=58) are less than 1, suggesting cation-exchange reaction as the significant processes through which Na+ enters the groundwater in both aquifers. To identify the intensity of weathering, the difference in saturation index of gibbsite to that of the saturation index of K-feldspar (SIy = SIg – SIk) is calculated (Table 4.57). This was done to identify the zones of recharge (initial stage of weathering) and the zones of discharge (intensive weathering) (Chidambaram et al., 2012). Based on the SIy values, the groundwater is classified into initial, transitional, and final stages of weathering. Positive SIy values suggest initial stage of weathering, negative SIy values suggests final stage of weathering and SIy values near zero suggest transitional stage of weathering. In Figure 4.52, it is seen that groundwater mostly located in the aquifer of the Birimian supergroup with few in the aquifer of the Apollonian formation represented by shades of red and orange colour are regions of possible recharge or initial stages of weathering. Discharge zones or final stages of weathering are seen in groundwater situated mostly in the aquifer of the Apollonian formation with few in the aquifer of the Birimian super group. This groundwater is represented by different shade of colours except red and orange. The differences between the rock – water interactions in the groundwater are attributed to different lithological conditions of the aquifer of the Apollonian and the Birimian supergroup rocks and rainfall. 266 University of Ghana http://ugspace.ug.edu.gh Figure 4. 50: Spatial distribution map of SI (Gibbsite – K-feldspar) in the sampled groundwater within the Lower Tano River Basin. 4.3.5 Sub -Conclusions From the above results, it is observed that Na-Cl type of groundwater was predominant in the aquifer of the Apollonian formation and the Birimian supergroup. In addition, rock-water interactions, rainfall, ion exchange processes, and incongruent dissolution are the predominant processes that took place in both aquifers. The mineral stability diagrams indicates that Kaolinite was the most stable mineral in the aquifer of the Apollonian formation and the Birimian supergroup. This therefore enhanced ion exchange processes in the groundwater of the study area due to kaolinite having a low cation-exchange capacity of 1-15 meq/100 g (Appelo & Postma, 2005). 4.4. Sources of Recharge to the aquifer system The role of δ18O and δ2H as an effective tracer can efficiently define the interrelationships between surface water and groundwater (Yurtsever & Gat, 1981). It can also assist in identifying the sources of groundwater recharge. Hence in these studies, the sources of recharge and recharge mechanism is identified using δ18O and δ2H compositions in rainwater, 267 University of Ghana http://ugspace.ug.edu.gh rivers, streams, hand dug wells and boreholes sampled in 2016 and 2017. The isotopic composition data for groundwater sampled in 2013 and from 2014 to 2015 was not measured due to technical issues beyond control. 4.4.1 Isotopic composition (δ18O and δ2H) in Rainwater The statistical summary of the isotopic compositions (δ18O and δ2H) and deuterium excess (d-excess) in rain water sampled in January, February, March, August, and December 2016(rainy season) and 2017 (dry seasons) is shown in Table 4.58. That of April, May, June, July, September, October, and November 2016 and 2017 is shown in Table 4.59. Table 4. 58: Statistical summary of stable isotope composition in rainfall sampled in January, February, March, August,and December (2016 and 2017) within the Lower Tano River Basin. Parameters δ18O δ2H d -excess Number of samples 24 24 24 Mean -0.51 7.74 11.84 Standard Error 0.19 1.65 0.70 Median -0.39 8.40 12.10 Mode -0.33 11.72 14.32 Standard Deviation 0.95 8.07 3.44 Sample Variance 0.90 65.17 11.81 Kurtosis -0.18 -0.21 -0.07 Skewness -0.69 -0.32 0.08 Minimum -2.64 -9.53 6.35 Maximum 0.80 22.00 20.00 Sum -12.29 185.84 284.16 Confidence Level (95.0%) 0.40 3.41 1.45 Table 4. 59: Statistical summary of stable isotope composition in rainfall sampled in April, May, June, July, September, October, and November (2016 and 2017) within the Lower Tano River Basin. Parameters δ18O δ2H d- excess Number of samples 38 38 38 Mean -1.75 -2.67 11.30 Standard Error 0.16 1.34 0.39 Median -1.85 -4.22 11.17 Mode -1.02 -0.62 8.73 Standard Deviation 0.99 8.25 2.39 Sample Variance 0.97 67.98 5.73 Kurtosis 0.81 1.51 -0.40 Skewness 0.46 0.63 0.19 Minimum -3.91 -23.11 6.33 Maximum 0.51 18.00 16.00 Sum -66.35 -101.30 429.52 Confidence Level 0.32 2.71 0.79 (95.0%) 268 University of Ghana http://ugspace.ug.edu.gh From Table 4.58, the isotopic composition in rain water sampled in January, February, March, August, and December 2016 and 2017 during the dry seasons ranges from -2.64 to 0.80 for δ18O‰ V-SMOW with a mean of -0.51 V-SMOW. That of δ2H ‰ V-SMOW values range between -9.53 and 22.0 with a mean of 7.74. From table 4.59, the isotopic compositions in rainwater sampled in April, May, June, July, September, October, and November 2016 and 2017 during the wet season ranges from -3.91 to 0.59 ‰ V- SMOW for δ18 O with a mean of -1.75 ‰ V-SMOW. That of δ2 H varies from -23.11 to 18‰ V-SMOW with a mean of -2.67 ‰. The linear relationship between δ2 H and δ18 O with a correlation coefficient of 0.9 for the rains sampled in January, February, March, August, and December is given by δ2 H = 7.69 δ18 O + 11.68 (Fig 4.53a) And that of April, May, June, July, September, October, and November is given by δ2 H = 8δ18O + 11.31. (Fig 4.53b) The slopes for January, February, March, August, and December, and April, May, June, July, September, October, and November are virtually identical to the global meteoric water line (GMWL of Craig, 1961) of 8 and the local meteoric water line (LMWL of Akiti, 1986) of 7.86. Nevertheless, the intercepts are above the GMWL of 10 and below the LMWL of 13.61. The intercepts for January, February, March, August, and December, and April, May, June, July, September, October, and November (2016 and 2017) are different from the GMWL and the LMWL (Akiti, 1986). This is due to the differences in climatic conditions. The deuterium excess in rainwater sampled in April, May, June, July, September, October, and November ranges from 6.33‰ to 16‰ V-SMOW with a mean of 11.30‰ and that of January, February, March, August, and December varied from 6.35‰ to 20.0‰ V-SMOW with a mean of 11.84‰. More depleted isotopic composition (δ18O and δ2H) in rainwater sampled in April, May, June, July, September, October, November was greater than rainwater sampled in January, February, 269 University of Ghana http://ugspace.ug.edu.gh March, August, and December. The effects of low rainfall amount over January, February, March, August, and December might have caused the enrichment of oxygen and hydrogen isotope signatures in the sampled rainwater. Similarly, the effects of high rainfall amount over April, May, June, July, September, October and, November might cause the significant depletion of oxygen and hydrogen isotopes in the sampled rainwater. Since the study area is known for high rainfall amount, it is likely that the sources of surface water and groundwater might be derived from the local rains with depleted isotopic compositions (Yurtsever & Gat, 1981). To prove this the rainfall regression lines obtained in this study together with the local meteoric water line (LMWL) of Ghana (Akiti, 1986) and the global meteoric water line (GMWL) (Craig, 1961) is used as reference lines in investigating the sources of surface water and groundwater recharge within the Lower Tano River Basin. Figure 4. 51a Schematic plot of δ2H versus δ18 O for rainfall sampled in January, February, March, Aug, September, and December, 2016 and 2017. 270 University of Ghana http://ugspace.ug.edu.gh Figure 4.53b: Schematic plot of δ2H versus δ18 O for rainfall sampled in April, May, June, July, October, November 2016 and 2017 Figure 4. 52: Average monthly humidity in the study area from 2006 to 2017 (Data from Ghana Meteorological Authority) 271 University of Ghana http://ugspace.ug.edu.gh 4.4.2. Isotopic Composition (δ18O and δ2H) in Rivers Table 4. 60: Statistical summary of stable isotope composition in Rivers sampled in 2016 and 2017 within the Lower Tano River Basin. 2016 2017 Parameters δ18O δ2H d- excess δ18O δ2H d- excess Number of samples 9 9 9 14 14 14 Mean -2.11 -5.93 10.96 -0.67 1.35 6.74 Standard Error 0.17 0.97 0.76 0.42 1.47 2.08 Median -2.19 -6.20 11.27 -1.29 0.43 9.10 Mode N/A N/A N/A N/A N/A N/A Standard Deviation 0.50 2.92 2.27 1.57 5.48 7.79 Sample Variance 0.25 8.54 5.13 2.46 30.08 60.67 Kurtosis 4.12 -0.71 1.53 3.08 0.21 3.55 Skewness 1.70 0.33 -1.16 1.73 0.80 -1.97 Minimum -2.72 -10.01 6.17 -2.17 -5.20 -14.32 Maximum -0.94 -1.35 13.36 3.51 13.76 12.57 Sum -19.00 -53.35 98.66 -9.43 18.93 94.37 Confidence 0.39 2.25 1.74 0.91 3.17 4.50 Level (95.0%) The δ18O of the sampled rivers in 2016 and 2017 ranges from -2.72 ‰ to −0. 94 ‰ with a mean of -2.11‰ and from -2.17 ‰ to 3.51 ‰ V-SMOW w i t h a mean of -0.67 ‰, respectively (Table 4.60). The δ2H of the rivers sampled in both 2016 and 2017 varies between -10.01 ‰ and - 1.35 ‰V-SMOW with a mean of -2.11 and from -5.20 ‰ to 13.76 ‰ V-SMOW with a mean of 1.35 respectively. Also, the deuterium excess for the rivers in both 2016 and 2017 ranges from 6.17‰ to 13.36‰ with a mean of 10.96‰ and from -14.32‰ to 12.57‰ with a mean of 6.74, respectively. The equation of the local evaporation line of the rivers (Fig 4.55) is δ2H = 3.75δ18O + 3.14. In addition, the regression line for the rivers sampled in both 2016 and 2017 is δ2H = 4.8 δ18O + 4.3 (2016). δ2H = 3.2 δ18O + 3.5 (2017). The slopes of the regression lines in both 2016 and 2017 are below the slopes of the GMWL and the LMWL and the regression line for January, February, March, August, and December (dry 272 University of Ghana http://ugspace.ug.edu.gh seasons) and April, May, June, July, September, October, and November (wet season). Since the slope of the regression line for the rivers sampled in 2016 and 2017 are below the slopes of the GMWL and the LMWL’s, it can be said that the isotopic composition of the rivers is affected by evaporation. Figure 4. 53: Isotopic compositions in the rivers sampled in 2016 and 2017 within the Lower Tano River Basin. 4.4.3. Isotopic Composition (δ18O and δ2H) in Streams Table 4. 61: A statistical summary of the isotopic compositions of the streams sampled in 2016 and 2017. 2016 2017 Parameters δ18O δ2H d-excess δ18O δ2H d-excess Number of samples 15 15 15 15 15 15 Mean -2.36 -6.70 12.24 -1.23 -0.24 9.57 Standard Error 0.32 1.28 1.40 0.18 0.98 0.81 Median -2.03 -5.67 10.39 -1.53 0.06 10.77 Mode N/A N/A N/A N/A N/A N/A Standard Deviation 1.25 4.96 5.43 0.71 3.81 3.12 Sample Variance 1.57 24.56 29.51 0.50 14.51 9.75 Kurtosis 2.64 0.86 3.09 2.91 3.73 0.41 Skewness -1.82 -1.32 1.96 1.68 1.44 -0.94 Minimum -5.31 -17.20 7.37 -1.88 -5.74 2.95 Maximum -1.07 -1.22 25.68 0.70 10.43 14.54 Sum -35.37 -100.50 183.62 -18.40 -3.60 143.59 Confidence Level (95.0%) 0.69 2.74 3.01 0.39 2.11 1.73 273 University of Ghana http://ugspace.ug.edu.gh For the isotopic compositions, δ18O‰ V-SMOW in the streams sampled in 2016 vary from - 5.31 to -1.07 with a mean of -2.3 and that of 2017 ranges from -1.88 to 0.70 with a mean of - 1.23 (Table 4.61). Likewise, δ2H ‰ V-SMOW in the streams sampled in both 2016 and 2017, ranges from - 17.20 to -1.22 with a mean of -6.70 and -5.74 to 10.43 with a mean of -0.24 respectively. The deuterium excess in the streams varies from 7.37‰ to 25.68‰ V-SMOW with a mean of 12.24 V-SMOW in 2016 and from 2.95‰ to 14.54‰ V-SMOW with a mean of 9.57 V- SMOW in 2017. The equation of the local evaporation line for the streams as shown in Fig (4.56) is δ2H = 4.42δ18O + 4.46. In addition, the regression line for the streams sampled in both 2016 and 2017 is δ2H = 3.81 δ18O + 2.28 (2016) and δ2H = 4.59 δ18O + 5.39 (2017), respectively. The slope for the regression lines in both 2016 and 2017 was less than the slope for the GMWL, the LMWL (Akiti, 1986) and the rainfall regression lines for both dry and wet season of the study area. Significant differences are seen in the oxygen and hydrogen isotope signatures in the stream, rivers, and rainwater. The forested canopies around the streams prevented a possible evaporation and this caused the isotopic compositions of the streams to be more depleted than the rivers. The mean and median of oxygen and hydrogen isotope compositions in the streams and rivers are also slightly similar. This has explained why a hydraulic relationship existed between the streams and the rivers sampled in 2017. 274 University of Ghana http://ugspace.ug.edu.gh Figure 4. 54: Isotopic compositions in the streams sampled in 2016 and 2017. 4.4.4. Isotopic Composition (δ18O and δ2H) in Lagoons. Table 4. 62: A statistical summary of the isotopic compositions of the Lagoons sampled in 2016 and 2017. 2016 2017 Parameters δ18O δ2H d - excess δ18O δ2H d - excess Number of samples 3 3 3 3 3 3 Mean -1.17 -2.27 7.12 -1.00 0.98 8.95 Standard Error 0.37 1.46 1.52 0.15 0.99 0.36 Median -1.43 -2.77 8.61 -1.06 0.06 8.64 Mode N/A N/A N/A N/A N/A N/A Standard Deviation 0.63 2.53 2.63 0.26 1.72 0.63 Sample Variance 0.40 6.39 6.90 0.07 2.95 0.40 Kurtosis 0.00 0.00 0.00 0.00 0.00 0.00 Skewness 1.52 0.86 -1.73 1.03 1.72 1.68 Minimum -1.64 -4.51 4.09 -1.22 -0.08 8.54 Maximum -0.45 0.47 8.66 -0.71 2.96 9.68 Sum -3.52 -6.81 21.36 -2.99 2.94 26.86 Confidence Level 1.57 6.28 6.52 0.65 4.26 1.57 (95.0%) The δ18O‰ V-SMOW compositions in the Lagoon sampled in both 2016 and 2017 varies from -1.64 to -0.45 with a mean of 1.17 and from -1.22 to -0.71 with a mean of -1 respectively. That of δ2H ‰ V-SMOW in the Lagoon ranges from -4.51 to 0.47 with a mean of -2.27 in 2016 and from -0.08 to 2.96 with a mean of 0.98 in 2017. Figure 4.57 shows the relationship between δ2H and δ18O for the sampled Lagoons. Similarly, the deuterium excess for the lagoon sampled in both 2016 and 2017 varies from 4.09‰ to 8.66‰ with a mean of 7.12 and from 8.54 ‰ to 9.68 ‰ with a mean of 8.95 275 University of Ghana http://ugspace.ug.edu.gh respectively. The equation of the local evaporation line for the lagoons as shown in Figure 4.57 is δ2H = 4.94 δ18O + 4.72. The slope of the local evaporation line for the lagoons was lower than the slopes of the LMWL, the rainfall regression lines of the study area and the GMWL. This suggests that the sampled Lagoons are affected by evaporation. Figure 4. 55: Isotopic compositions in the Lagoon sampled in 2016 and 2017. 4.4.5. Isotopic Composition (δ18O and δ2H) in Seawater Table 4. 63: A statistical summary of the isotopic compositions of the Lagoons sampled in 2016 and 2017. 2016 2017 Parameters δ18O δ2H d- excess δ18O δ2H d-excess Number of samples 3 3 3 9 9 9 Mean -0.97 -2.62 5.13 0.85 5.90 -0.88 Standard Error 0.63 3.64 1.95 0.45 1.92 1.73 Median -1.39 -2.87 5.52 1.01 6.67 -1.63 Mode N/A N/A N/A N/A 6.34 N/A Standard Deviation 1.10 6.30 3.37 1.36 5.76 5.20 Sample Variance 1.20 39.72 11.36 1.84 33.23 27.09 Kurtosis 0.00 0.00 0.00 5.38 6.43 4.05 Skewness 1.48 0.17 -0.51 -1.86 -2.28 1.23 Minimum -1.79 -8.80 1.58 -2.43 -8.55 -9.01 Maximum 0.28 3.80 8.29 2.66 12.27 10.89 Sum -2.91 -7.87 15.39 7.63 53.08 -7.96 Confidence Level (95.0%) 2.73 15.66 8.37 1.04 4.43 4.00 276 University of Ghana http://ugspace.ug.edu.gh The δ 18O‰ V-SMOW compositions in seawater sampled in both 2016 and 2017 ranges from -1.79 to 0.28 with a mean of 0.97 and from -2.43 to – 2.66 with a mean of 0.85, respectively. δ2H ‰ V-SMOW in the seawater ranges from -8.80 to 3.80 with a mean of -2.62 in 2016 and from -8.55 to 12.27 with a mean of 5.90 in 2017. The relationship between δ2H and δ18O for the seawater is shown in Figure 4.58. In 2016, the deuterium excess for the seawater samples varies from 1.58‰ to 8.29 ‰ with a mean of 5.13 ‰ and in 2017, the deuterium excess ranges from -9.01‰ to 10.89‰ with a mean of -0.88‰. The equation of the local evaporation line for the seawater as shown in Fig 4.58 is given as δ2H = 4.48 δ18O + 2.01. The slope of the regression line is lower than the GMWL, LMWL (Akiti, 1986) and the rainfall regression lines of the study area. Figure 4. 56: Isotopic compositions in seawater sampled in 2016 and 2017. The global meteoric water line, the local meteoric water line and the rainfall regression lines determined for this study is inserted in Figure 4.55 to Figure 4.58. The lines are inserted to serve as reference lines in discussing the sources of recharge for the surface water. Further to 277 University of Ghana http://ugspace.ug.edu.gh the plots (Fig 4.55 to 4.58), the following observations were made for the isotopic ratios (δ2 H and δ18 O) in the surface water (River, Stream, Lagoon and Seawater) and that is: • No surface water (River, Stream, Lagoon and Seawater) plots on the local meteoric water line proposed by Akiti (1986). • 10 sampled Rivers and 7 sampled Streams plots on the local rainfall regression lines determine for the study area. • 2 sampled Rivers, 8 sampled streams and 1 sampled Seawater plots on the GMWL • 3 sampled Streams plots above and beneath the meteoric water lines. • 10 sampled rivers, 12 sampled streams, 6 sampled lagoons, and 11 seawater samples plots below the meteoric water lines. From figure 4.55 to 4.58, it is seen that the surface water is mainly of meteoric origin with few from other sources and the recharge mechanism is direct infiltration. Also, the surface water plotting above and beneath the meteoric water lines are highly depleted and the depletion might be as a result of the forested canopy in which the samples were taken. These forested canopies serve as a shade, which induces high humidity, thus reducing the rate of evaporation but further investigations are required using carbon-14 isotope. The surface water plotting below the meteoric water lines indicates that the surface water is evaporated and the source of recharge is from other sources apart from rainwater. Also, the recharge mechanism is not direct infiltration. These surface water (10 Rivers, 12 Streams and 6 Lagoons) were not shaded along their banks and the absence of shade induces low humidity thus increasing the rate of evaporation. 278 University of Ghana http://ugspace.ug.edu.gh 4.4.6 Isotopic Composition (δ18O and δ2H) in Groundwater Table 4. 64: A statistical summary of the isotopic compositions of the hand dug wells sampled in 2016 and 2017. 2016 2017 Parameters δ18O δ2H d - excess δ18O δ18H d - excess Number of samples 36 36 36 30 30 30 Mean -2.77 -8.61 13.85 -1.49 -2.44 9.47 Standard Error 0.22 0.81 0.99 0.12 0.70 0.71 Median -2.24 -6.81 11.04 -1.66 -3.31 9.86 Mode N/A N/A N/A -1.74 -4.53 N/A Standard Deviation 1.32 4.88 5.92 0.66 3.81 3.89 Sample Variance 1.74 23.77 35.09 0.44 14.53 15.15 Kurtosis 0.02 0.37 -0.24 0.96 4.18 4.76 Skewness -1.21 -1.16 1.12 1.23 1.96 -1.98 Range 4.65 17.995 19.77 2.67 17.03 17.36 Minimum -5.97 -20.83 7.26 -2.5 -6.94 -2.65 Maximum -1.32 -2.84 27.03 0.17 10.09 14.71 Sum -99.59 -310.14 498.57 -44.66 -73.15 284.13 Confidence 0.45 1.65 2.00 0.25 1.42 1.45 Level(95.0%) Table 4. 65: A statistical summary of the isotopic compositions of the boreholes sampled in 2016 and 2017. 2016 2017 Parameters δ18O δ2H d -excess δ18O δ2H d - excess Number of samples 45 45 45 55 55 55 Mean -2.61 -8.51 12.43 -2.01 -7.22 9.60 Standard Error 0.14 0.59 0.59 0.10 0.30 0.63 Median -2.36 -7.91 12.04 -2.20 -7.24 9.60 Mode N/A N/A N/A -2.29 N/A N/A Standard Deviation 0.94 3.95 3.97 0.75 2.26 4.64 Sample Variance 0.88 15.58 15.75 0.56 5.10 21.52 Kurtosis 6.35 5.16 6.75 20.35 -0.72 5.98 Skewness -2.58 -2.24 2.41 3.67 0.16 0.34 Range 4.50 18.66 20.75 5.62 9.08 34.34 Minimum -5.96 -22.55 7.19 -3.29 -11.72 -6.92 Maximum -1.46 -3.89 27.94 2.33 -2.64 27.42 Sum -117.51 -382.80 559.26 -110.59 -397.29 527.91 Confidence 0.28 1.19 1.19 0.20 0.61 1.25 Level (95.0%) In the study area, the stable isotopic composition in the hand dug wells sampled in 2016 and 2017 range between – 5.97, and -1.32 ‰ V-SMOW with a mean of -2.77 ‰ V- SMOW and - 2.5 to 0.17 ‰ V-SMOW with a mean of -1.49‰ V-SMOW, respectively (Table 4.64). The mean value of -2.77‰ for δ18O in the hand dug wells sampled in 2016 is like the mean value of -2.8‰ obtained by Akiti (1980) for groundwater sampled from the Accra plains of Ghana. 279 University of Ghana http://ugspace.ug.edu.gh The δ2H values in the hand dug well sampled in 2016 and 2017 range between -20.83 and - 2.84 ‰ V-SMOW with a mean of -8.61 ‰ V-SMOW and -6.94 to 10.09‰ V-SMOW with a mean of -2.44‰ V-SMOW, respectively. The evaporation line for the hand dug wells is given as δ2H = 4.22δ18O + 3.59, (R2= 0.87) and the regression line for the hand dug wells for both years is given as δ2H = 3.57 δ18O + 1.27, (2016) and δ2H = 6.34 δ18O + 7.67, (2017). The regression lines suggest that the composition of oxygen and hydrogen isotopes in the hand dug wells sampled in 2016 are more affected by evaporation than those sampled in 2017. This means that either the hand dug wells are recharged by rainfall enriched in heavy isotopes or that the enrichment took place in the unsaturated zone. The relationship between δ2H and δ18O for the hand dug wells in both 2016 and 2017 is shown in figure 4.59. Figure 4. 57: Isotopic compositions in the hand dug wells sampled in 2016 and 2017. 280 University of Ghana http://ugspace.ug.edu.gh The δ18O‰ V-SMOW in the boreholes sampled in 2016 and 2017 vary from -5.96 to -1.46 with a mean of -2.61 and -3.29 to 2.33 with a mean of -2.01 (Table 4.65), respectively. Similarly, the δ2H‰ V-SMOW for the boreholes sampled in 2016 and 2017, ranges from - 22.55 to -3.89 with a mean of -8.51 and -11.72 to -2.64 with a mean of -7.22 respectively. The mean δ18O value for the boreholes sampled in 2016 and 2017 is slightly like the mean value of -2.8‰ obtained by Akiti (1980). The evaporation line for the boreholes is given as δ2H = 3.71 δ18O + 0.9 (r2 = 1) and the regression lines for the boreholes sampled in both 2016 and 2017 are given as δ2H = 3.98δ18O + 1.88 (2016) and δ2H = 3.63 δ18O + 0.5(2017), respectively (Fig 4.60). Both regression lines show that the boreholes a re subjected to evaporation but the boreholes sampled in 2017 are more evaporated than those sampled in 2016. Figure 4. 58: Isotopic compositions in the boreholes sampled in 2016 and 2017. 281 University of Ghana http://ugspace.ug.edu.gh The global meteoric water line, the local meteoric water line and the rainfall regression lines determined for this study is inserted in Figure 4.59 and Fig 4.60. These lines serve as reference lines in discussing the sources of groundwater recharge. From figure 4.59 and 4.60, the following observations are made for the isotopic composition of oxygen and hydrogen isotope in the hand dug wells sampled in 2016 (n= 37) and 2017 (n= 30). The observations are • 11 hand dug wells sampled in 2016 and 13 hand dug wells sampled in 2017 plots on the rainfall regression lines of the study area. • 2 hand dug wells sampled in 2017 plots on the LMWL proposed by Akiti ,1986. • 8 hand dug wells sampled in 2016 and 5 hand dug wells sampled in 2017 cluster around the GMWL. • 9 hand dug wells sampled in 2016 and 10 hand dug wells sampled in 2017 plots below the meteoric water lines. • 9 hand dug wells sampled in 2016 plots above and beneath the meteoric water lines. For the boreholes sampled in 2016 (n= 45) and 2017(n= 56), the following observations are made, that is • 27 samples taken in 2016 and 26 samples taken in 2017 cluster around the rainfall regression lines of the study area. • 5 boreholes sampled in 2016 cluster around the local meteoric water line (Akiti, 1986). • 4 boreholes sampled in both 2016 and 2017 plots above and beneath the meteoric water lines • 4 boreholes sampled in 2016 and 8 boreholes sampled in 2017 cluster around the GMWL. • The remaining 5 boreholes sampled in 2016 and 22 boreholes sampled in 2017 plots below the meteoric water lines. 282 University of Ghana http://ugspace.ug.edu.gh From figure 4.59 to 4.60, it is observed that the source of groundwater recharge in the Lower Tano River basin is mainly meteoric with no significant evaporation. Also, recharge mechanism is rapid without any significant evaporation and gaseous exchange. This agrees favorably to the results obtained by Edjah et al., 2015 and 2019. This explains why rainwater was one of the chemical qualities controlling the mineralization of 50% of the groundwater in the study area (Fig 4.39a). Additionally, it is seen that fewer groundwater (9 hand dug wells and 5 boreholes) samples were evaporated. This reveals that the groundwater might be undergoing evaporation due to limited degree of kinetic evaporation before or during infiltration process. In addition, most of the hand dug wells were opened without covers and there might be an occurrence of direct evaporation. Also, the recharge mechanism is not rapid and the source of recharge might be from the surface water, which will be explained further in subsequent chapters. The groundwater lying above and beneath the meteoric water lines (GMWL and LMWL’s) are highly depleted and the depletion might be as a result of the forested canopy where samples were taken. These forested canopies serve as a shade, which induces high humidity, thus reducing the rate of evaporation but further investigations are required using carbon-14 isotope. Comparing the isotopic regression lines of the sampled groundwater and the sampled surface water, it is observed that the regression line for the hand dug wells sampled in 2017 is like that of the lagoon sampled in 2017. This indicates that the sampled lagoon might possibly be influencing the hand dug well recharge of the study area. The oxygen and hydrogen compositions in the boreholes sampled in 2016 are slightly like the hand dug wells sampled in 2016. These indicate that the source of the borehole water sampled in 2016 might probably be related to the 2016 hand dug wells instead of rainwater recharge. This explains why a hydraulic relationship existed between the hand dug wells and the boreholes sampled in 2016 as discussed in the 2nd specific objective. Also, from fig 4.59 to 4.60 and fig 4.61, it is observed that most of the groundwater samples were clustering around the rainfall regression lines (wet and dry seasons) of the study area. 283 University of Ghana http://ugspace.ug.edu.gh This indicates that, local modern rainwater is a significant source of groundwater recharge in the aquifer of the Apollonian formation and the Birimian supergroup. The intercept and slopes for the groundwater (hand dug wells and boreholes) regression lines for both 2016 and 2017 are less than the LMWL’s (Akiti, 1986) and less than the rainfall regression lines of the study area. This explains the important effect of evaporative enrichment on the groundwater within the basin (Wassenaar et al., 2011). Also from Figure 4.61, the groundwater appears to be grouped in a narrow range signifying a well-mixed system with relatively constant isotopic compositions. This suggest that rainwater recharging the aquifer of the Apollonian formation and the Birimian supergroup is relatively homogeneous with evaporation playing an insignificant role on the infiltration processes. Figure 4. 59: Spatial distribution map of δ18O‰ values in the sampled groundwater of the study area. 4.4.7 Deuterium excess in groundwater of the study area The deuterium excess for the hand dug wells sampled in 2016 and 2017 ranges between 7.26 and 27.03 ‰ V-SMOW with a mean of 13.85 ‰ V-SMOW and -2.65 to 14.71‰ V-SMOW 284 University of Ghana http://ugspace.ug.edu.gh with a mean of 9.47 ‰ V-SMOW, respectively (Table 4.66). For the boreholes sampled in 2016, the deuterium excess varies from 7.19‰ to 27.94‰ with a mean of 12.43‰ and in 2017 the deuterium excess ranges from -6.92‰ to 27.42‰ with a mean of 9.60‰ (Table 4.67). The deuterium excess depends on conditions prevalent during primary evaporation, consisting of sea surface temperature, variation in humidity and wind speed, which gives information on the sources of water vapour {Gat, 1983; Clark & Fritz. (1997)}. Non-equilibrium evaporation causes a reduction in the deuterium excess, which suggests an increment in vapor phases. However, equilibrium processes will not change the deuterium excess for any of the phases. In this study, majority of the groundwater (hand dug wells and boreholes) have deuterium excess values close to that of rainfall and a few are close to evaporation. The plot (Fig 4.62) specifies a strong and a positive correlation (Hand dug wells (2016), r = 0.94, hand dug wells (2017), r = 0.7, boreholes (2016), r = 0.95, boreholes (2017), r = 0.76) existing between oxygen -18 and deuterium excess for the groundwater sampled from the aquifer of the Apollonian formation and the aquifer of the Birimian supergroup. The positive d-excess values (>10‰) for most of the groundwater samples is consistent with the origin, which is derived from rainfall. The positive d-excess values provided additional evidence to groundwater recharge from surface water, which will be explained further in subsequent chapters. Also, few of the groundwater has lower d-excess values, which suggest an evaporative enrichment of groundwater during the recharge process. This is due to slow recharge rates which requires further investigations in future works. 285 University of Ghana http://ugspace.ug.edu.gh Figure 4. 60: A cross plot of d-excess‰ against δ18O‰ in surface water and groundwater of the study area. 4.4.8 Quantification of River water contribution to Groundwater recharge of the study area. A two-component mixing equation is used in this study to estimate the proportion of the sampled rivers (Pr) and the sampled streams (Pstream) in the groundwater sampled from the aquifer of the Apollonian formation and the Birimian supergroup. The equation used is defined as: 𝛿18𝑂𝑔𝑤− 𝛿 18 𝑂 𝑃 𝑝𝑟𝑒𝑐𝑖𝑝𝑖𝑡𝑎𝑡𝑖𝑜𝑛𝑟 = 18 18 × 100 eq 4.20 𝛿 𝑂𝑟𝑖𝑣𝑒𝑟𝑠 − 𝛿 𝑂𝑝𝑟𝑒𝑐𝑖𝑝𝑖𝑡𝑎𝑡𝑖𝑜𝑛 Where δ18Ogw is the value of groundwater, δ 18Oprecipitation is the average value of precipitation (rainfall), δ18Oriver is the average value of the rivers, and Pr is the contribution of the river to the recharge of the groundwater (Rai et al., 2009; Clark & Fritz, 1997; Table 4.66). 286 University of Ghana http://ugspace.ug.edu.gh Table 4. 66: Proportion of Rivers and Streams to recharge of groundwater samples taken in 2016 Sample ID Sample location δ18 Ogw mean δ18Orainwater mean mean δ18O δ18 O - mean mean δ18Rivers gw ORiver - Pr mean δ18 Ostream - Pstream Pr % Pstream % δ18O 18 18 18streams δ Orainwater mean δ Orainwater mean δ Orainwater HDW 1 Esiama -2.11 -0.1 -2.36 -2.11 -2.0 -2.04 1.0 -2.29 0.89 100.05 89.27 HDW 2 Nkroful -1.89 -0.1 -2.36 -2.11 -1.8 -2.04 0.9 -2.29 0.79 88.96 79.37 HDW 3 Kikam -1.96 -0.1 -2.36 -2.11 -1.9 -2.04 0.9 -2.29 0.83 92.51 82.55 HDW 4 Kikam -1.84 -0.1 -2.36 -2.11 -1.8 -2.04 0.9 -2.29 0.77 86.85 77.49 HDW 5 Aniwa -1.74 -0.1 -2.36 -2.11 -1.7 -2.04 0.8 -2.29 0.73 81.84 73.03 HDW 6 Kikam -2.21 -0.1 -2.36 -2.11 -2.1 -2.04 1.0 -2.29 0.94 104.83 93.53 HDW 7 Ampain -2.20 -0.1 -2.36 -2.11 -2.1 -2.04 1.0 -2.29 0.93 104.16 92.94 HDW 8 Asanta -1.86 -0.1 -2.36 -2.11 -1.8 -2.04 0.9 -2.29 0.78 87.71 78.26 HDW 9 Nkroful -1.95 -0.1 -2.36 -2.11 -1.9 -2.04 0.9 -2.29 0.82 92.11 82.19 HDW 10 Kikam -1.94 -0.1 -2.36 -2.11 -1.9 -2.04 0.9 -2.29 0.82 91.62 81.75 HDW 11 Bomuakpole -2.14 -0.1 -2.36 -2.11 -2.1 -2.04 1.0 -2.29 0.90 101.40 90.48 HDW 12 Kikam -1.53 -0.1 -2.36 -2.11 -1.5 -2.04 0.7 -2.29 0.64 71.57 63.86 HDW 13 Ankobra -1.86 -0.1 -2.36 -2.11 -1.8 -2.04 0.9 -2.29 0.78 87.71 78.26 HDW 14 Asanta -2.40 -0.1 -2.36 -2.11 -2.3 -2.04 1.1 -2.29 1.02 114.12 101.83 HDW 15 gyegyEKROM -2.39 -0.1 -2.36 -2.11 -2.3 -2.04 1.1 -2.29 1.01 113.63 101.39 HDW 16 Kikam -2.12 -0.1 -2.36 -2.11 -2.1 -2.04 1.0 -2.29 0.90 100.43 89.61 HDW 17 Asanta -1.75 -0.1 -2.36 -2.11 -1.7 -2.04 0.8 -2.29 0.73 82.33 73.46 HDW 18 Esiama -1.98 -0.1 -2.36 -2.11 -1.9 -2.04 0.9 -2.29 0.84 93.65 83.56 HDW 19 Aniwa -1.99 -0.1 -2.36 -2.11 -1.9 -2.04 0.9 -2.29 0.84 94.27 84.12 HDW 20 Esiama -2.24 -0.1 -2.36 -2.11 -2.2 -2.04 1.1 -2.29 0.95 106.29 94.84 HDW 21 Elubo -1.53 -0.1 -2.36 -2.11 -1.5 -2.04 0.7 -2.29 0.64 71.68 63.96 HDW 22 Asanta -1.86 -0.1 -2.36 -2.11 -1.8 -2.04 0.9 -2.29 0.78 87.71 78.26 HDW 23 Ankobra -1.51 -0.1 -2.36 -2.11 -1.4 -2.04 0.7 -2.29 0.63 70.59 62.99 HDW 24 Esiama -1.90 -0.1 -2.36 -2.11 -1.8 -2.04 0.9 -2.29 0.80 89.87 80.19 HDW 25 Esiama -1.69 -0.1 -2.36 -2.11 -1.6 -2.04 0.8 -2.29 0.71 79.40 70.85 HDW 26 Nkroful -1.63 -0.1 -2.36 -2.11 -1.6 -2.04 0.8 -2.29 0.68 76.70 68.44 HDW 27 Esiama -1.78 -0.1 -2.36 -2.11 -1.7 -2.04 0.8 -2.29 0.75 83.98 74.93 HDW 28 Esiama -1.83 -0.1 -2.36 -2.11 -1.8 -2.04 0.9 -2.29 0.77 86.24 76.95 HDW 29 Gyegyekrom -2.08 -0.1 -2.36 -2.11 -2.0 -2.04 1.0 -2.29 0.88 98.47 87.86 HDW 30 Elubo -1.63 -0.1 -2.36 -2.11 -1.6 -2.04 0.8 -2.29 0.68 76.46 68.23 HDW 31 Azulenloanu -1.32 -0.1 -2.36 -2.11 -1.3 -2.04 0.6 -2.29 0.55 61.30 54.70 HDW 32 Half Assin(1) -2.29 -0.1 -2.36 -2.11 -2.2 -2.04 1.1 -2.29 0.97 108.49 96.81 HDW 33 Bobrama -2.08 -0.1 -2.36 -2.11 -2.0 -2.04 1.0 -2.29 0.88 98.47 87.86 HDW 34 Asanta -1.75 -0.1 -2.36 -2.11 -1.7 -2.04 0.8 -2.29 0.73 82.33 73.46 HDW 35 Sanwoma -1.92 -0.1 -2.36 -2.11 -1.9 -2.04 0.9 -2.29 0.81 90.67 80.90 HDW 36 Bobrama -2.08 -0.1 -2.36 -2.11 -2.0 -2.04 1.0 -2.29 0.88 98.47 87.86 BH 1 Salman(3) -2.06 -0.1 -2.36 -2.11 -2.0 -2.04 1.0 -2.29 0.87 97.49 86.99 BH 2 Kamgbuli -1.81 -0.1 -2.36 -2.11 -1.7 -2.04 0.9 -2.29 0.76 85.27 76.08 BH 3 Kamgbuli -2.26 -0.1 -2.36 -2.11 -2.2 -2.04 1.1 -2.29 0.96 107.31 95.75 BH 4 Asemko -2.25 -0.1 -2.36 -2.11 -2.2 -2.04 1.1 -2.29 0.95 106.72 95.22 287 University of Ghana http://ugspace.ug.edu.gh BH 5 Ampaim -1.46 -0.1 -2.36 -2.11 -1.4 -2.04 0.7 -2.29 0.61 68.15 60.81 BH 6 Aniwa -2.52 -0.1 -2.36 -2.11 -2.5 -2.04 1.2 -2.29 1.07 119.99 107.06 BH 7 Nkroful -2.06 -0.1 -2.36 -2.11 -2.0 -2.04 1.0 -2.29 0.87 97.49 86.99 BH 8 Sanwoma -2.02 -0.1 -2.36 -2.11 -2.0 -2.04 1.0 -2.29 0.85 95.54 85.24 BH 9 Aluku -1.93 -0.1 -2.36 -2.11 -1.9 -2.04 0.9 -2.29 0.81 91.24 81.41 BH 10 Awiebo -2.32 -0.1 -2.36 -2.11 -2.3 -2.04 1.1 -2.29 0.98 110.19 98.32 BH 11 Esiama -2.41 -0.1 -2.36 -2.11 -2.3 -2.04 1.1 -2.29 1.02 114.57 102.23 BH 12 Ampain -1.46 -0.1 -2.36 -2.11 -1.4 -2.04 0.7 -2.29 0.61 68.15 60.81 BH 13 Salman -2.33 -0.1 -2.36 -2.11 -2.3 -2.04 1.1 -2.29 0.99 110.94 98.99 BH 14 Nkroful -2.53 -0.1 -2.36 -2.11 -2.5 -2.04 1.2 -2.29 1.07 120.23 107.28 BH 15 Bobrama -2.66 -0.1 -2.36 -2.11 -2.6 -2.04 1.3 -2.29 1.13 126.85 113.19 BH 16 Bomuakpole -2.35 -0.1 -2.36 -2.11 -2.3 -2.04 1.1 -2.29 1.00 111.62 99.60 BH 17 Sanwoma -2.36 -0.1 -2.36 -2.11 -2.3 -2.04 1.1 -2.29 1.00 112.32 100.22 BH 18 Alabokazo -2.78 -0.1 -2.36 -2.11 -2.7 -2.04 1.3 -2.29 1.19 132.90 118.58 BH 19 Aluku (1) -1.99 -0.1 -2.36 -2.11 -1.9 -2.04 0.9 -2.29 0.84 94.04 83.91 BH 20 Alabokazo(2) -2.58 -0.1 -2.36 -2.11 -2.5 -2.04 1.2 -2.29 1.10 122.77 109.55 BH 21 Asanta(6) -2.46 -0.1 -2.36 -2.11 -2.4 -2.04 1.2 -2.29 1.04 116.99 104.38 BH 22 Salaman(1) -2.49 -0.1 -2.36 -2.11 -2.4 -2.04 1.2 -2.29 1.06 118.63 105.85 BH 23 Telekobokaso -2.12 -0.1 -2.36 -2.11 -2.1 -2.04 1.0 -2.29 0.90 100.56 89.73 BH 24 Aluku -1.81 -0.1 -2.36 -2.11 -1.7 -2.04 0.9 -2.29 0.76 85.49 76.28 BH 25 Esiama -2.54 -0.1 -2.36 -2.11 -2.5 -2.04 1.2 -2.29 1.08 120.97 107.93 BH 26 Ankobra newsite -2.37 -0.1 -2.36 -2.11 -2.3 -2.04 1.1 -2.29 1.01 112.77 100.62 BH 27 Sanwoma -2.06 -0.1 -2.36 -2.11 -2.0 -2.04 1.0 -2.29 0.87 97.64 87.12 BH 28 Old Kablasuazo -2.56 -0.1 -2.36 -2.11 -2.5 -2.04 1.2 -2.29 1.09 122.18 109.02 BH 29 Azulenloa -2.69 -0.1 -2.36 -2.11 -2.6 -2.04 1.3 -2.29 1.14 128.20 114.39 BH 30 Azuleno -2.18 -0.1 -2.36 -2.11 -2.1 -2.04 1.0 -2.29 0.92 103.54 92.38 BH 31 Fante new site -2.58 -0.1 -2.36 -2.11 -2.5 -2.04 1.2 -2.29 1.10 123.10 109.84 BH 32 Elubo -2.00 -0.1 -2.36 -2.11 -1.9 -2.04 0.9 -2.29 0.84 94.51 84.33 BH 33 Bomuakpole(1) -2.18 -0.1 -2.36 -2.11 -2.1 -2.04 1.0 -2.29 0.92 103.36 92.23 BH 34 NyanZinli(1) -2.22 -0.1 -2.36 -2.11 -2.1 -2.04 1.1 -2.29 0.94 105.14 93.81 BH 35 Atwibanso(1) -2.34 -0.1 -2.36 -2.11 -2.3 -2.04 1.1 -2.29 0.99 111.18 99.21 BH 36 New Nzulezu(1) -2.51 -0.1 -2.36 -2.11 -2.4 -2.04 1.2 -2.29 1.06 119.29 106.44 BH 37 NEW Ankasa -1.84 -0.1 -2.36 -2.11 -1.8 -2.04 0.9 -2.29 0.77 86.73 77.39 BH 38 Bonyere -2.35 -0.1 -2.36 -2.11 -2.3 -2.04 1.1 -2.29 1.00 111.67 99.64 BH 39 Atwibaso(2) -2.73 -0.1 -2.36 -2.11 -2.7 -2.04 1.3 -2.29 1.16 130.26 116.23 BH 40 Awiafoto -2.65 -0.1 -2.36 -2.11 -2.6 -2.04 1.3 -2.29 1.13 126.50 112.87 BH 41 Aniwafuto(chips) -2.13 -0.1 -2.36 -2.11 -2.1 -2.04 1.0 -2.29 0.90 100.83 89.97 BH 42 New Nzulezu(2) -2.27 -0.1 -2.36 -2.11 -2.2 -2.04 1.1 -2.29 0.96 107.63 96.03 BH 43 Tiekobo 1 -2.45 -0.1 -2.36 -2.11 -2.4 -2.04 1.2 -2.29 1.04 116.70 104.13 BH 44 Bobrama -1.83 -0.1 -2.36 -2.11 -1.8 -2.04 0.9 -2.29 0.77 86.24 76.95 BH 45 Ankobra (3) -1.41 -0.1 -2.36 -2.11 -1.3 -2.04 0.7 -2.29 0.59 65.70 58.63 288 University of Ghana http://ugspace.ug.edu.gh Table 4. 67: Proportion of Rivers and Streams to recharge of groundwater samples taken in 2017 Sample ID Sample Location δ18 Ogw mean mean mean δ 18 Ogw - mean mean δ 18 Pr mean δ18 Ostream - Pstream Pr % Pstream % δ18Orainwater δ 18O 18streams δ ORivers δ 18O O - mean mean δ18rainwater River Orainwater δ18Orainwater HDW1 Nkroful -1.74 -1.8 -1.23 -0.67 0.036 1.10 0.033 0.55 0.066 3.3 6.6 HDW2 Aluku -1.78 -1.8 -1.23 -0.67 -0.004 1.10 -0.003 0.55 -0.007 -0.3 -0.7 HDW3 Kikam -1.74 -1.8 -1.23 -0.67 0.036 1.10 0.033 0.55 0.066 3.3 6.6 HDW4 Nkroful -1.95 -1.8 -1.23 -0.67 -0.174 1.10 -0.158 0.55 -0.316 -15.8 -31.6 HDW5 Esiama -1.65 -1.8 -1.23 -0.67 0.126 1.10 0.114 0.55 0.230 11.4 23.0 HDW6 Elubo -1.31 -1.8 -1.23 -0.67 0.466 1.10 0.423 0.55 0.848 42.3 84.8 HDW7 Kikam -1.63 -1.8 -1.23 -0.67 0.146 1.10 0.133 0.55 0.266 13.3 26.6 HDW8 Half Assini -1.66 -1.8 -1.23 -0.67 0.116 1.10 0.105 0.55 0.211 10.5 21.1 HDW9 Bomuakpole -1.96 -1.8 -1.23 -0.67 -0.184 1.10 -0.167 0.55 -0.334 -16.7 -33.4 HDW10 Nkroful -1.91 -1.8 -1.23 -0.67 -0.134 1.10 -0.121 0.55 -0.243 -12.1 -24.3 HDW11 Kikam -1.68 -1.8 -1.23 -0.67 0.096 1.10 0.087 0.55 0.175 8.7 17.5 HDW12 Kikam -2.11 -1.8 -1.23 -0.67 -0.334 1.10 -0.303 0.55 -0.607 -30.3 -60.7 HDW13 Elubo -1.65 -1.8 -1.23 -0.67 0.126 1.10 0.114 0.55 0.230 11.4 23.0 HDW14 Nkroful -1.48 -1.8 -1.23 -0.67 0.296 1.10 0.269 0.55 0.539 26.9 53.9 HDW15 Aniwa -1.38 -1.8 -1.23 -0.67 0.396 1.10 0.359 0.55 0.721 35.9 72.1 HDW16 Asemda -1.6 -1.8 -1.23 -0.67 0.176 1.10 0.160 0.55 0.321 16.0 32.1 HDW17 Gyegyekrom -2.33 -1.8 -1.23 -0.67 -0.554 1.10 -0.502 0.55 -1.008 -50.2 -100.8 HDW18 esiama -1.63 -1.8 -1.23 -0.67 0.146 1.10 0.133 0.55 0.266 13.3 26.6 HDW19 Ampaim -1.76 -1.8 -1.23 -0.67 0.016 1.10 0.015 0.55 0.030 1.5 3.0 HDW20 Eikwe -2.5 -1.8 -1.23 -0.67 -0.724 1.10 -0.656 0.55 -1.317 -65.6 -131.7 HDW21 Atuabo -1.8 -1.8 -1.23 -0.67 -0.024 1.10 -0.022 0.55 -0.043 -2.2 -4.3 HDW22 Benyin -1.6 -1.8 -1.23 -0.67 0.176 1.10 0.160 0.55 0.321 16.0 32.1 HDW23 Esiama -1.24 -1.8 -1.23 -0.67 0.536 1.10 0.486 0.55 0.976 48.6 97.6 HDW24 Gyegyekrom -1.23 -1.8 -1.23 -0.67 0.546 1.10 0.495 0.55 0.994 49.5 99.4 HDW25 bobrama -2.02 -1.8 -1.23 -0.67 -0.244 1.10 -0.221 0.55 -0.444 -22.1 -44.4 HDW26 Elubo -1.9 -1.8 -1.23 -0.67 -0.124 1.10 -0.112 0.55 -0.225 -11.2 -22.5 HDW27 Kikam -1.72 -1.8 -1.23 -0.67 0.056 1.10 0.051 0.55 0.102 5.1 10.2 HDW28 Kikam -2.04 -1.8 -1.23 -0.67 -0.264 1.10 -0.239 0.55 -0.480 -23.9 -48.0 HDW29 Azuleno -1.63 -1.8 -1.23 -0.67 0.146 1.10 0.133 0.55 0.266 13.3 26.6 HDW30 Aniwa -1.62 -1.8 -1.23 -0.67 0.156 1.1 0.142 0.5 0.284 14.2 28.4 BH1 Sanzule -2.25 -1.8 -1.23 -0.67 -0.474 1.1 -0.430 0.5 -0.862 -43.0 -86.2 BH2 Nyaniba -2.29 -1.8 -1.23 -0.67 -0.514 1.1 -0.466 0.5 -0.935 -46.6 -93.5 BH3 Ampaim -2.37 -1.8 -1.23 -0.67 -0.594 1.1 -0.539 0.5 -1.080 -53.9 -108.0 BH4 Atwinbanso -2.27 -1.8 -1.23 -0.67 -0.494 1.1 -0.448 0.5 -0.898 -44.8 -89.8 BH5 Elubo -1.61 -1.8 -1.23 -0.67 0.166 1.1 0.151 0.5 0.302 15.1 30.2 BH6 Awiefoto -1.69 -1.8 -1.23 -0.67 0.086 1.1 0.078 0.5 0.157 7.8 15.7 BH7 Esiama -1.32 -1.8 -1.23 -0.67 0.456 1.1 0.414 0.5 0.830 41.4 83.0 BH8 Old Kablazuaso -2.17 -1.8 -1.23 -0.67 -0.394 1.1 -0.357 0.5 -0.716 -35.7 -71.6 BH9 Fante New Town -1.79 -1.8 -1.23 -0.67 -0.014 1.1 -0.013 0.5 -0.025 -1.3 -2.5 BH10 half Assin SHS -2.16 -1.8 -1.23 -0.67 -0.384 1.1 -0.348 0.5 -0.698 -34.8 -69.8 BH11 Salman -2.34 -1.8 -1.23 -0.67 -0.564 1.1 -0.511 0.5 -1.026 -51.1 -102.6 BH12 Salman -2.49 -1.8 -1.23 -0.67 -0.714 1.1 -0.647 0.5 -1.299 -64.7 -129.9 289 University of Ghana http://ugspace.ug.edu.gh BH13 Esiama -1.9 -1.8 -1.23 -0.67 -0.124 1.1 -0.112 0.5 -0.225 -11.2 -22.5 BH14 Azuleno -1.63 -1.8 -1.23 -0.67 0.146 1.1 0.133 0.5 0.266 13.3 26.6 BH15 Bomuakpolley -2.48 -1.8 -1.23 -0.67 -0.704 1.1 -0.638 0.5 -1.281 -63.8 -128.1 BH16 Salman -2.36 -1.8 -1.23 -0.67 -0.584 1.1 -0.529 0.5 -1.062 -52.9 -106.2 BH17 Nkroful -2.05 -1.8 -1.23 -0.67 -0.274 1.1 -0.248 0.5 -0.498 -24.8 -49.8 BH18 Esiama -2.68 -1.8 -1.23 -0.67 -0.904 1.1 -0.820 0.5 -1.644 -82.0 -164.4 BH19 Ankobra newsite -2.2 -1.8 -1.23 -0.67 -0.424 1.1 -0.384 0.5 -0.771 -38.4 -77.1 BH20 Ampin -2.11 -1.8 -1.23 -0.67 -0.334 1.1 -0.303 0.5 -0.607 -30.3 -60.7 BH21 Nkroful -2.58 -1.8 -1.23 -0.67 -0.804 1.1 -0.729 0.5 -1.462 -72.9 -146.2 BH22 New Nzulazu -2.14 -1.8 -1.23 -0.67 -0.364 1.1 -0.330 0.5 -0.662 -33.0 -66.2 BH23 Tiekobo -2.45 -1.8 -1.23 -0.67 -0.674 1.1 -0.611 0.5 -1.226 -61.1 -122.6 BH24 Bobrama -2.51 -1.8 -1.23 -0.67 -0.734 1.1 -0.665 0.5 -1.335 -66.5 -133.5 BH25 New Nzulazu -2.68 -1.8 -1.23 -0.67 -0.904 1.1 -0.820 0.5 -1.644 -82.0 -164.4 BH26 Bonyere -2.31 -1.8 -1.23 -0.67 -0.534 1.1 -0.484 0.5 -0.971 -48.4 -97.1 BH27 Kamgbunli -2.28 -1.8 -1.23 -0.67 -0.504 1.1 -0.457 0.5 -0.917 -45.7 -91.7 BH28 Aluku -1.68 -1.8 -1.23 -0.67 0.096 1.1 0.087 0.5 0.175 8.7 17.5 BH29 Atwinbanso -2.37 -1.8 -1.23 -0.67 -0.594 1.1 -0.539 0.5 -1.080 -53.9 -108.0 BH30 Asemko -2.19 -1.8 -1.23 -0.67 -0.414 1.1 -0.375 0.5 -0.753 -37.5 -75.3 BH31 Salman -2.54 -1.8 -1.23 -0.67 -0.764 1.1 -0.693 0.5 -1.390 -69.3 -139.0 BH32 Azeneluno -2.03 -1.8 -1.23 -0.67 -0.254 1.1 -0.230 0.5 -0.462 -23.0 -46.2 BH33 Aluku -2.57 -1.8 -1.23 -0.67 -0.794 1.1 -0.720 0.5 -1.444 -72.0 -144.4 BH34 Alabokazo -2.38 -1.8 -1.23 -0.67 -0.604 1.1 -0.548 0.5 -1.099 -54.8 -109.9 BH35 Kamgbunli -2.53 -1.8 -1.23 -0.67 -0.754 1.1 -0.684 0.5 -1.372 -68.4 -137.2 BH36 Ankasa -2.31 -1.8 -1.23 -0.67 -0.534 1.1 -0.484 0.5 -0.971 -48.4 -97.1 BH37 Telekobokaso -1.82 -1.8 -1.23 -0.67 -0.044 1.1 -0.040 0.5 -0.080 -4.0 -8.0 BH38 Alabokazo -1.52 -1.8 -1.23 -0.67 0.256 1.1 0.232 0.5 0.466 23.2 46.6 BH39 Awiafotu junction -1.63 -1.8 -1.23 -0.67 0.146 1.1 0.133 0.5 0.266 13.3 26.6 BH40 Azulenenuo -2.22 -1.8 -1.23 -0.67 -0.444 1.1 -0.402 0.5 -0.807 -40.2 -80.7 BH41 Salman -2.33 -1.8 -1.23 -0.67 -0.554 1.1 -0.502 0.5 -1.008 -50.2 -100.8 BH42 Sanzule -1.59 -1.8 -1.23 -0.67 0.186 1.1 0.169 0.5 0.339 16.9 33.9 BH43 Ngelekazo(kerrela hotel) -2.33 -1.8 -1.23 -0.67 -0.554 1.1 -0.502 0.5 -1.008 -50.2 -100.8 BH44 Eikwe -1.8 -1.8 -1.23 -0.67 -0.024 1.1 -0.022 0.5 -0.043 -2.2 -4.3 BH45 Ngelekazo -1.43 -1.8 -1.23 -0.67 0.346 1.1 0.314 0.5 0.630 31.4 63.0 BH46 sanzule -3.29 -1.8 -1.23 -0.67 -1.509 1.1 -1.368 0.5 -2.745 -136.8 -274.5 BH47 Krisan -1.6 -1.8 -1.23 -0.67 0.176 1.1 0.160 0.5 0.321 16.0 32.1 BH48 ngelekpolley -1.83 -1.8 -1.23 -0.67 -0.054 1.1 -0.049 0.5 -0.098 -4.9 -9.8 BH49 Baku -1.28 -1.8 -1.23 -0.67 0.496 1.1 0.450 0.5 0.903 45.0 90.3 BH50 Keegan -2.29 -1.8 -1.23 -0.67 -0.514 1.1 -0.466 0.5 -0.935 -46.6 -93.5 BH51 Asemda -2.69 -1.8 -1.23 -0.67 -0.914 1.1 -0.829 0.5 -1.663 -82.9 -166.3 BH52 Ngelekyi -1.46 -1.8 -1.23 -0.67 0.316 1.1 0.287 0.5 0.575 28.7 57.5 BH53 Twenen -1.5 -1.8 -1.23 -0.67 0.276 1.1 0.251 0.5 0.503 25.1 50.3 BH54 Half Assin(shs) -2.26 -1.8 -1.23 -0.67 -0.484 1.1 -0.439 0.5 -0.880 -43.9 -88.0 BH55 Atwinbanso -1.96 -1.8 -1.23 -0.67 -0.184 1.1 -0.167 0.5 -0.334 -16.7 -33.4 290 University of Ghana http://ugspace.ug.edu.gh The average value of δ18 O in rainwater sampled in both 2016 and 2017 is -0.1‰ and -1.8‰, respectively (Table 4.66 and 4.67). The average value of δ18 O in the rivers sampled in 2016 and 2017 is -2.11‰ and -0.67‰, respectively. Substituting δ18 O values in each sampled groundwater, the average value of δ18 O in rain water and rivers into Eq 4.20, gives a result, which shows that the proportion of river water to groundwater recharge for 2016 and 2017 samples varies from 61.30% to 132.90% and -136.83% to 49.54% respectively (Table 4.66 and 4.67). Comparing the spatial distribution map of Figure 4.63 a and Figure 4.63 b, it is observed that groundwater sampled in 2016 are recharged more by the rivers than the groundwater sampled in 2017. This is due to seasonal effects. Figure 4. 61a: Spatial variation of River contribution to 2016 groundwater recharge in the study area. 291 University of Ghana http://ugspace.ug.edu.gh Fig 4.63 b: Spatial variation of River water contribution to 2017 Groundwater recharge in the study area. 4.4.9 Quantification of sampled stream water contribution to sampled groundwater recharge in the study area In order to measure the contribution of the stream flow to the recharge of the groundwater, the binary mixing equation or the two-component separation method is applied: ( 𝛿18 𝑂𝑔𝑤− 𝛿 18 𝑂 𝑃 = 𝑝𝑟𝑒𝑐𝑖𝑝𝑖𝑡𝑎𝑡𝑖𝑜𝑛 ) 𝑠 × 100 Eq 4.21 (𝛿18 𝑂𝑠𝑡𝑟𝑒𝑎𝑚𝑠 − 𝛿18 𝑂𝑃𝑟𝑒𝑐𝑖𝑝𝑖𝑡𝑎𝑡𝑖𝑜𝑛 ) Where δ18O , δ18O , and δ18gw p Ostreams are the respective isotopic composition of the sampled groundwater, the sampled rainwater, and the sampled streams. Ps is the contribution of the sampled streams to the recharge of the sampled groundwater. The δ18 O value of the stream water in 2016 and 2017 is -2.36‰ and -1.23‰ respectively (Table 4.66 and 4.67). These two are the average value of δ18O in the streams sampled in 2016 and 2017. The average δ18 O values of the rainwater sampled in 2016 and 2017 is also stated in Table 4.66 and 4.67. δ18O value for each sampled groundwater, the average δ18O value in the 292 University of Ghana http://ugspace.ug.edu.gh sampled rainwater and the sampled streams is substituted into equation 4.21. The obtained results (Table 4.66 and 4.67) shows that the proportion of the sampled stream to that of the 2016 and 2017 sampled ground recharge varies from 54.70% to 118.58% and -274.52% to 99.38 %, respectively. Comparing Figure 4.64a and Figure 4.64b, it is seen that the groundwater sampled in 2016 are recharged more by the streams than the groundwater sampled in 2017. This explains why a hydraulic connection existed between the streams and the boreholes sampled in 2016 as discussed previously in the 2nd specific objective. Figure 4. 62a: A Spatial variation map of stream water contribution to 2016 groundwater recharge in the study area. 293 University of Ghana http://ugspace.ug.edu.gh Figure 4.64b: A Spatial variation map of stream water contribution to 2017 groundwater recharge in the study area. 4.4.10. Sub-Conclusion The results of the 4th specific objective shows that the source of surface water and groundwater recharge is mainly meteoric with few from other sources such as the rivers and streams. The recharge mechanism was rapid for majority of the groundwater while few of the groundwater lost some water through evaporation. 4.5. Groundwater age determination (Residence time) Tritium is regularly used as an indicator for sources of groundwater and as an age tracer in aquifer systems (Bouchaou et al., 2008). In Accordance with Lu et al. (2008), “aquifers having tritium concentrations greater than 1.0 TU are deduced as aquifers mixed with modern water or recharged after 1952 when tritium was released into the air because of atmospheric nuclear weapon testing. In this study, the tritium content in surface water (rain and rivers) and groundwater (hand dug wells and boreholes) are measured. The results obtained for the rain samples are compared with other results in Ghana and beyond. In addition, the results obtained 294 University of Ghana http://ugspace.ug.edu.gh for tritium in groundwater are used to determine the ages in which the the groundwater was recharged. 4.5.1. Tritium concentration results in the sampled Surface water In this study, tritium was measured in 35 rainfall samples and 3 rivers. The average tritium concentration of rainwater and rivers is 3.32 TU and 2.64 TU, respectively and the tritium results is presented in table 4.68. Table 4. 68: Results of tritium content in rainfall and Rivers sampled within the Lower Tano River Basin. All units are in tritium units (TU). Sample Number Type of Sample TU 1 Rainfall 10.11 2 Rainfall 6.77 3 Rainfall 5.5 4 Rainfall 3.47 5 Rainfall 2.84 6 Rainfall 5.97 7 Rainfall 4.2 8 Rainfall 3.36 9 Rainfall 3.09 10 Rainfall 2.91 11 Rainfall 1.94 12 Rainfall 6.09 13 Rainfall 2.15 14 Rainfall 3.73 15 Rainfall 2.03 16 Rainfall 1.27 17 Rainfall 2.1 18 Rainfall 2.42 19 Rainfall 2.72 20 Rainfall 3.52 21 Rainfall 2.72 22 Rainfall 2.96 23 Rainfall 1.34 24 Rainfall 1.8 25 Rainfall 1.67 26 Rainfall 1.11 27 Rainfall 2.84 28 Rainfall 3.09 29 Rainfall 2.63 30 Rainfall 2.25 31 Rainfall 4.73 32 Rainfall 3.05 33 Rainfall 4.27 34 Rainfall 3.07 35 Rainfall 2.32 36 River 2.8 37 River 2.04 38 River 3.08 295 University of Ghana http://ugspace.ug.edu.gh The obtained tritium results in the rainwater (Table 4.68) shows a decline in tritium concentration as compared to IAEA, (1980). This is deduced by the fact that during the dry and the wet seasons in the northern hemisphere where Ghana lies, the border layer between the troposphere and the stratosphere is possibly lowered. This decline might probably be accompanied by the release of tritium produced in the upper levels of the atmosphere into the troposphere, thereby increasing the flux of tritiated water to the ground by rainfall. The levels of tritium content in the rainwater of the study area were lower than the tritium values obtained by Akiti (1980) for rainwater in some regions of southern Ghana. Acheampong and Hess (2000) measured tritium content in precipitation in 1994, and their values fall within the range of values obtained for the tritium concentration in the rainwater for the study area. The only difference is that the mean tritium content in their rainfall data was less than the average tritium concentration obtained for the rainwater in this study. In addition, the obtained tritium results for the rainwater in this study is in accordance with other published literature such as Lopez et.al. (1994), Blagojevich, (2003), Eriksson (1983), and Villa and Manjon (2004). The obtained tritium values in the rainwater of the study area can be explained by the fact that the study area is close to the Gulf of Guinea and the effect of the ocean water with very low tritium content is to decrease the tritium concentrations in rainwater. Similar works conducted by Hayashi et al. (1999) in Japan, which is also affected by the Pacific Ocean, reported slightly similar results. It can therefore be reasoned that the tritium values for the sampled rain are in full accord with the recorded tritium contents of other investigators in similar oceanic terrain. Importantly, information obtained from this study combined with tritium measurements in the three sampled rivers may prove valuable for future hydrological investigations in the study catchment. 296 University of Ghana http://ugspace.ug.edu.gh Figure 4. 63: Tritium concentration in the sampled rainwater of the Lower Tano River Basin 4.5.2. Results of Tritium concentration in the sampled Groundwater Due to limited funds, tritium was measured in eighteen borehole samples located around the three sampled rivers. The results obtained is tabulated below: 297 University of Ghana http://ugspace.ug.edu.gh Table 4.69: Tritium results for the sampled groundwater in te aquifer of the Apollonian formation and the Birimian supergroup. All units are in tritium units (TU). Type of water Town Latitude Longitude Tritium HDW Esiama 4.93708 -2.34753 6.76 HDW Half Assin 5.05041 -2.88695 4.03 HDW Bobrama 4.91499 -2.29979 1.68 HDW Elubo 5.29211 -2.77604 4.31 HDW Esiama 4.94086 -2.34531 3.89 HDW Kikam 4.92601 -2.32429 2.16 HDW Aniwa 4.9233 -2.32594 2.65 BH Kamgbunli 4.98212 -2.41549 5.91 BH Elubo 5.29322 -2.77609 4.16 BH Azeleno 4.94827 -2.38005 1.74 BH Bomuakpolley 4.99989 -2.33273 1.94 Bh Aluku 4.99479 -2.2645 2.3 BH New Nzulezu 5.09191 -2.57354 3.03 BH Telekobokazo 4.98707 -2.32713 0.99 BH Tiekobo 1 5.05328 -2.32713 3.29 BH Bobrama 4.91497 -2.29765 1.26 BH Awiefoto 5.16214 -2.68664 4.36 BH Salman 5.00452 -2.22655 1.8 BH Ankobra New Site 4.90565 -2.27132 1.77 HDW – Hand dug well and BH – Borehole. The tritium values in the groundwater ranges from 0.99 TU to 6.76 TU with a mean of 3.05 TU. The mean tritium value of the sampled groundwater was slightly like the mean tritium value of the rainwater. Tritium values in groundwater less than one are an indicative of old water and it implies that the groundwater was recharged before the thermonuclear bomb testing in 1952 (IAEA,1981). In this study, 17 (n=18) of the analyzed groundwater samples recorded tritium values greater than one, suggesting a probable recent or modern recharge (i.e., direct infiltration of recent rainfall in the study area). This means that 17 of the sampled groundwater were possibly recharged after the thermonuclear bomb test in 1952, making them newer in age and indicates that most of the groundwater in the aquifer of the Apollonian formation and the Birimian supergroup are of modern recharge. The tritium values in the sampled groundwater were also less than the tritium values (6.5 TU to 20 TU) obtained by Akiti (1980). This indicate that tritium values in groundwater located at the southeastern portion of Ghana would have decayed simultaneously by 2020 due to the half-life of tritium, which is 298 University of Ghana http://ugspace.ug.edu.gh 12.32 years. Similarly, the tritium values in the groundwater were in the range obtained by Adomako et al. (2010) and Ganyaglo (2015). The tritium values obtained for most of the groundwater samples were also like modern day meteoric water values except one borehole located at Telekobokaso, in the aquifer of the Birimian Supergroup. That borehole had low tritium value (0.99 TU) which might possibly be due to tritium gradually decaying to its natural background levels after the cessation of a thermonuclear bomb tests in 1963 (www.iaea.com). Since δ18O and δ2H isotopic compositions in the borehole at Telekobokaso are not highly depleted than the rest of the groundwater samples, the low Tritium value recorded must be investigated further. The spatial distribution map of tritium in groundwater in the aquifer of the Apollonian formation and the Birimian supergroup (Fig 4.66) did not show a definite flow pattern indicating intermittent aquifers in the study area. Figure 4.64: Spatial distribution map of tritium concentrations (TU) in ground water of the study area. 299 University of Ghana http://ugspace.ug.edu.gh In the absence of long-term monitoring of tritium in rainfall in Ghana, approximation of the input signal since the bomb pulse in the early 1960s is done using the most proximate station (Aranyossy and Gaye 1992), which for Ghana is Bamako (Mali). This long-term tritium activity records in rainwater compiled by the I.A.E.A GNIP, from April 1963 to October 1998 are plotted in figure 4.67 together with the tritium values of rainwater, rivers, and groundwater sampled from the study area. From figure 4.67, two types of groundwater are observed that is groundwater recharged between 1960 - 1965, and 1965 – 1970. From the period in which the groundwater was recharged, it can be said that the aquifer of the Apollonian formation and the Birimian supergroup is of modern recharge with short residence time. This provides a general reason for low TDS content recorded for groundwater sampled from the aquifer of the Apollonian formation and the Birimian supergroup of the study area. Figure 4.67: Tritium activity in monthly precipitation at the IAEA monitoring station in Bamako, Mali, from 1963 to 1999 (IAEA GNIP); with surface water and groundwater samples. 300 University of Ghana http://ugspace.ug.edu.gh CHAPTER FIVE CONCLUSIONS AND RECOMMENDATION 5.1 General Conclusions Under this section the conclusion remarks under each specific objective is discussed. This will help understand the hydrogeology of the Lower Tano River Basin and that will help assist in the optimal decision-making regarding groundwater resources management to ensure sustainability. 5.1.1 Estimation of aquifer hydraulic parameters The present study reports on the estimation of aquifer hydraulic parameters in the Lower Tano River Basin of Ghana. Based on the computed results, the depths of the boreholes range from 18 to 62 m, the yield of the boreholes range from 10 to 800 l/min, the groundwater levels range from -0.8 to 20.70 a.m.s.l, the transmissivity values range from 1.73 to 1219.70 m3/day, the hydraulic conductivity values vary from 0.04 to 44.35 m/day, and the specific capacity values range from 0.72 to 122.24 L/min/m. With respect to the obtained aquifer hydraulic parameter results, the subsurface formation at the drilling sites was seen to be composed mainly of limestones, claystones along with conglomerates, sandstones, granites etc. Also, with respect to the computed aquifer hydraulic parameters, two types of aquifers were observed. That is the unconfined aquifer of the Apollonian formation and semi-confined aquifer of the Birimian supergroup. The computed water levels implies that groundwater in the Lower Tano River basin flows from the aquifer of the Birimian supergroup to the aquifer of the Apollonian formation and that was related to the deposition environment of the basin. Also, the estimated aquifer hydraulic parameters of the aquifer of the Apollonian formation and the Birimian supergroup had the potential to yield adequate amount of water for the growing population. 301 University of Ghana http://ugspace.ug.edu.gh 5.1.2 Assessing the overall quality of groundwater including the level of trace elements contamination and its suitability for domestic and agricultural purposes This study provides an improved understanding of the hydrochemical factors that determines the suitability of groundwater for domestic and agricultural purposes. Combined use of cations, anions and trace elements was successfully employed to help assess the overall quality of groundwater and trace the sources of contamination. The pH for the surface water and groundwater was acidic to neutral. The pH values of groundwater sampled from the aquifer of the Apollonian formation ranged from 4.1 to 6.8 with most samples below WHO (2011) permissible limit of 6.5 to 8.5. The pH of groundwater sampled from the aquifer of the Birimian supergroup ranged from 4.1 to 8.5 with most samples below WHO (2011) permissible limit of 6.5 to 8.5. The TDS content for the surface water and groundwater revealed the occurrence of low mineralization with fresh groundwater (TDS < 1000 mg/L). The electrical conductivity values for most of the surface water and all the groundwater were below WHO (2011) permissible limit of 1500 μS/cm for drinking water. In addition, the EC content in the groundwater sampled from the aquifer of the Apollonian formation and the Birimian supergroup had low enrichment of salts (EC<1500 μS/cm) making the groundwater drinkable. The ions Ca2+, Mg2+, Na+, K+, Cl-, SO 2-4 , NO - 3 , and HCO - 3 concentrations in the sampled surface water and the groundwater were minimal with Na+, HCO -3 and SO 2- 4 dominating. Na +, HCO -3 and SO 2- 4 ions were more than 93% of the total TDS concentrations in the surface water and the groundwater. Based on a comparison with the WHO (2011) standards, problems with 40% of the surface water and groundwater quality for drinking were mostly related to high amount of Cu, Cd, Zn, Cr, Fe, Ni, Mn, Co, Pb, As, whereas the anions and cations did not influence the quality. 302 University of Ghana http://ugspace.ug.edu.gh Results of the water quality index (WQI) indicated that groundwater quality status for majority of the groundwater were good for drinking with few unsuitable groundwater due to high concentration of Cu, Cd, Zn, Cr, Fe, Ni, Mn, Co, Pb, As. The increasing concentration of the trace elements in the groundwater sampled from the aquifer of the Apollonian formation and the Birimian supergroup was mainly geogenic with few anthropogenic sources. Groundwater suitability for drinking was low in the aquifer of the Apollonian formation. Even though the quality of groundwater was deteriorating for drinking purposes, most were suitable for irrigation based on SAR, PI, and chlorinity index. However, Na%, RSC, and MH % indices gave different results. The calculated groundwater indices within the basin suggest that 40% of the groundwater in the aquifer of the Apollonian formation and the aquifer of the Birimian supergroup were unsuitable for irrigation, whiles the remaining 60% was suitable for irrigation. 5.1.3 Determination of the Hydrogeochemical processes that produces the chemical characteristics or compositions of the aquifer system The Ficklin diagram used in this study demonstrated that most groundwater with high pH values and low trace elements were near – neutral low-metal water (pH = 6-9). Few groundwater with low pH content and high trace metals were acid-low metal water (pH = 4-6). The groundwater classification using the Ficklin diagram provided a useful information, which could be used to develop an appropriate water pollution and remediation strategies in the Lower Tano river basin. The Durov diagram illustrated that all the groundwater in the aquifer of the Apollonian formation and the Birimian supergroup were young with TDS content being less than 1000 mg/L. In accordance to the Durov diagram, the groundwater sampled from the aquifer of the Apollonian formation and the Birimian supergroup was mainly classified as Na-Cl water type. 303 University of Ghana http://ugspace.ug.edu.gh There were also representations of Ca-HCO3, Na-HCO 2- 3 and Na-SO4 in groundwater sampled from the aquifer of the Apollonian formation and the Birimain supergroup. Piper (1944) and Stiff (1951) diagrams used in the hydrochemical classification of the water types from 2014 to 2015 and 2017 groundwater samples showed a transition from Ca-Mg- HCO -3 water type to Na-Cl water type along the flow direction. For the groundwater sampled in 2016, the Piper diagram and Stiff diagram evolve from Ca-Mg-Cl-SO4 to NaCl water type. The above water types were under the influence of natural processes and climatic conditions. Gibbs (1970) diagram illustrated rock weathering and rainfall as the two major cause of variation in the groundwater hydrochemistry. Different ionic ratios (Na+/Cl-, Na+/HCO - 2+3 , Ca + Mg 2+ Vs SO 2-4 + HCO - 3 , Ca 2+ + Mg2+ - HCO -3 - SO 2- 4 Vs Na + - Cl-, Na+ + K+ Vs TC etc) were used to decipher different geochemical processes influencing the chemistry of groundwater in the aquifer of the Birimian supergroup and the Apollonian formation. All the results under ionic ratio suggested rock weathering, precipitation and ion exchange processes as the main processes governing the hyrochemical evolution of groundwater in the aquifer of the Apollonian formation and the Birimian supergroup. The results of saturation index calculation indicated that carbonate minerals in most groundwater samples were undersaturated with respect to dolomite, aragonite, and calcite. Also, silicate minerals in most of the groundwater samples were under saturated with chalcedony, quartz, and amorphous silica. The saturation index (SI) for alumino silicate minerals in the groundwater samples was in the order of K– mica > kaolinite> gibbsite > Ca- montmorillonite > K feldspar. Stability diagram for calcium, magnesium sodium and potassium identified kaolinite and montmorillonite as the stable weathered products from weathering of primary minerals namely limestones, clay minerals, feldspars, plagioclase, hornblende etc. 304 University of Ghana http://ugspace.ug.edu.gh The above result has not only helped in the understanding of the hydrogeochemical characteristics of the aquifer of the Apollonian formation and the Birimian supergroup but it has aided in providing a comprehensive understanding of the mineralization processes that supports the hydrochemical evolution and the hydrodynamic functioning of the aquifer of the Apollonian formation and the Birimian supergroup of the Lower Tano River Basin. This has therefore provided an important aquifer information for researchers and decision makers to formulate scientifically reasonable groundwater resource management strategies for the Lower Tano river basin of Ghana. 5.1.4 Investigating the sources of recharge to the aquifer system and age determination to understand the recharge sources This study is the first systematic attempt to identify the sources of recharge in the Lower Tano river basin using isotopes (δ18O, δ2H ). The Lower Tano river basin was characterized by properties such as geology and elevation that influence groundwater recharge. The isotopic results reveal that the sources of recharge for the groundwater within the basin was meteoric especially from the local rains. The isotopic binary mixing equation revealed that, rain fed rivers and streams also contributed to the groundwater recharge in the study area. These sources of recharge varied spatially according to their importance. Significantly, the influence of the rivers and the streams to the groundwater recharge was active in almost all the samples taken across the study area except for fewer samples. The spatial variability in the concentration of the isotopes (δ18O, δ2H) in the groundwater reflects the limited lateral connectivity of the aquifers due to the heterogeneity of their minerals. The tritium(3H) results indicates that the groundwater was of modern recharge with short residence time. This is due to the groundwater being recharged between 1960 to 1965 and 1965 to 1970. The isotopic composition results in the surface water and the groundwater will help in designing sustainable groundwater management strategies which will aid in the identification of active recharge zones in the Lower Tano River Basin. 305 University of Ghana http://ugspace.ug.edu.gh 5.2 Recommendations Based on the present study, the following recommendations are made for better protection and management of groundwater resources within the Lower Tano River Basin. • Groundwater quality monitoring must be conducted annually. • Due to high concentrations of Cu, Cd, Zn, Cr, Fe, Ni, Mn, Co, Pb, and As in few hand dug wells and boreholes, the health impacts, especially on children have to be assessed across the Lower Tano River Basin. • Environmentally friendly, cost effective and easy to adopt iron removal technology must be developed or contaminated groundwater must be restored using a cost- effective method such as managed aquifer recharge, thus using rainwater to dilute the concentration of trace element in the groundwater and this must be done when considering groundwater development in the study area. • Special indication mark in the form of colour painting must be carried out to identify the hand dug wells and the borehole water contaminated with Cu, Cd, Zn, Cr, Fe, Ni, Mn, Co, Pb and As. • Areas showing groundwater unsuitability for irrigation must be investigated further and appropriate soil amendments should be applied when considering large-scale farming in the Lower Tano River Basin. • For an effective management of groundwater systems in the study area, a yearly estimation of the amount of water per domestic or industrial usage using the safe yield approach introduced by Todd, 1959, Theis, 1940, Lee, 1915, Alley et al. 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Technol. 341 University of Ghana http://ugspace.ug.edu.gh APPENDICES Appendix 1: Available data for the Rivers sampled in 2016 Sample Name of river Location Date Sample ID RIV 1 Ankobra Ankobra 09/05/2016 RIV 2 Fia Awiebo 09/06/2016 RIV 3 Anuyayo Ayinasi – Half Assini Road 09/06/2016 RIV 4 Ellonyi Ellonyi 09/06/2016 RIV 5 Bile Nkroful 09/06/2016 RIV 6 Amanzura Esiama to Elubo road 09/06/2016 RIV 7 EBI Esiama to Elubo road 09/07/2016 RIV 8 Tano Elubo 09/07/2016 RIV 9 Ankasa Ankasa 09/07/2016 Appendix 2: Available data for the Streams sampled in 2016 Sample Name of stream Location Date Sample ID Stre 1 Subile Nkroful 09/05/2016 Stre 2 Abobre Nkroful 09/05/2016 Stre 3 Nobaya(Left) Nkroful 09/05/2016 Stre 4 Franza Nkroful 09/05/2016 Stre 5 Nobaya(right) Nkroful 09/05/2016 Stre 6 Nsuengene Teleku-bokazo to Aluku 09/06/2016 Stre 7 Edwele Teleku-bokazo to Aluku 09/06/2016 Stre 8 Kodubaku Teleku-bokazo to Aluku 09/06/2016 Stre 9 Ngontubile Teleku-bokazo to Aluku 09/06/2016 Stre 10 Broma Teleku-bokazo to Aluku 09/06/2016 Stre 11 Wowule Teleku-bokazo to Aluku 09/06/2016 Stre 12 Unknown name Elubo 09/06/2016 Stre 13 Unknown name Elubo 09/06/2016 Stre 14 Assufofoa Atuabo 09/07/2016 Stre 15 Unknown Name Ayinasi 09/07/2016 Appendix 3: Available data for the Lagoon sampled in 2016 Sample Name of Location Date Sample ID Lagoon Lag1 Amanzura Ampaim 09/06/2016 Lag2 Dominee Old Kablazuazo 09/07/2016 Lag3 Amanzura Axim - Elubo road 09/07/2016 342 University of Ghana http://ugspace.ug.edu.gh Appendix 4: Available data for the Seawater sampled in 2017 Sample ID Location Date Sample SEA 1 Ankobra 09/03/2016 SEA 2 Asanta 09/04/2016 SEA 3 Kikam 09/04/2016 Appendix 5: Available data for Rivers sampled in 2017 Sample Name of River Location Date Sample ID RIV 1 Fia Awiebo 17/03/2017 RIV 2 Ebi Esiama to Elubo road 17/03/2017 RIV 3 Amanzura Esiama to Elubo road 16/04/2017 RIV 4 Eleneano Esiama to Elubo road 16/04/2017 RIV 5 Ankobra Ankobra 31/12/2017 RIV 6 Bile Nkroful 28/12/2017 RIV 7 Anuyayo Ayinasi - Half Assin Road 30/12/2017 RIV 8 Ebi Esiama to Elubo road 28/12/2017 RIV 9 Amanzura Esiama to Elubo road 28/12/2017 RIV 10 Ellonyi Ellonyi 30/12/2017 RIV 11 Ankasa Ankasa 28/12/2017 RIV 12 Unknown river Salman 30/12/2017 RIV 13 Tano Elubo 28/12/2017 RIV 14 Fia Awiebo 28/12/2017 Appendix 6: Available data for Streams sampled in 2017 Sample Name of Stream Location Date Sample number Stre 1 Unknown name Ayinasi 28/12/2017 Stre 2 Unknown name Esiama to Elubo 28/12/2017 Stre 3 Assufo(2) Atuabo 28/12/2017 Stre 4 Unknown name Nkroful 30/12/2017 Stre 5 Subile Nkroful 30/12/2017 Stre 6 Kodubaku Teleku-bokazo to Aluku 30/12/2017 Stre 7 Nsugene Teleku-bokazo to Aluku 30/12/2017 Stre 8 Bonuma Teleku-bokazo to Aluku 30/12/2017 Stre 9 Edweleza Teleku-bokazo to Aluku 30/12/2017 Stre 10 ngontubile Teleku-bokazo to Aluku 30/12/2017 Stre 11 Wowule Teleku-bokazo to Aluku 30/12/2017 Stre 12 Abobre Nkroful 30/12/2017 Stre 13 Nobaya Nkroful 31/12/2017 Stre 14 Franza Nkroful 31/12/2017 343 University of Ghana http://ugspace.ug.edu.gh Appendix 7: Available data for Lagoons sampled in 2017 Sample Number Name of Laoon Location Date Sample Lag1 Dominee Old 28/12/2017 Kablasuazo Lag2 Amanzura Axim - Elubo 31/12/2017 road Lag3 Amanzura Ampaim 31/12/2017 Appendix 8: Available data for Seawater sampled in 2017 Sample ID Location Date Sample SEA 1 Asanta 14/02/2017 SEA 2 Ankobra 14/02/2017 SEA 3 Krisen(2) 15/02/2017 SEA 4 Ebonyi 16/02/2017 SEA 5 Atuabo 16/02/2017 SEA 6 Old Kablasuazo 28/12/2017 SEA 7 Asanta 31/12/2017 SEA 8 Kikam (6) 31/12/2017 SEA 9 Ankobra 31/12/2017 Appendix 9: Available data for the boreholes drilled in 2013 Sample Location Date of sample Sample Location Date of sample ID ID NB1 Alumatoape 05/08/2013 NB16 Nyamebekyere 20/08/2013 NB2 Mpeasem 06/08/2013 NB17 Samenye 21/08/2013 NB3 Kamgbunli 07/08/2013 NB18 Domiabra 22/08/2013 NB4 Elubo 08/08/2013 NB19 Sowudazem 23/08/2013 NB5 Bobrama 09/08/2013 NB20 Alapoke 24/08/2013 NB6 Akanko 10/08/2013 NB21 Aniwafutu 25/08/2013 NB7 Gwira ampansie 11/08/2013 NB22 Ankyernin 26/08/2013 NB8 Ndatiem 12/08/2013 NB23 Fawoman 27/08/2013 NB9 Ayisakro 13/08/2013 NB24 Dadwen 28/08/2013 NB10 Kegyina 14/08/2013 NB25 Akpendue 29/08/2013 NB11 Nyamebekyere 15/08/2013 NB26 Obengkrom 30/08/2013 NB12 Akonu 16/08/2013 NB27 Cocoatown 31/08/2013 NB13 Ellanda Wharf 17/08/2013 NB28 Kutukrom 01/09/2013 NB14 Gwira Aiyinase 18/08/2013 NB29 Ghana Nungua 02/09/2013 NB15 Sanzule 19/08/2013 NB30 Ankajeri 03/09/2013 344 University of Ghana http://ugspace.ug.edu.gh Appendix 10: Available data for the boreholes drilled in 2014 to 2015. Sample ID Location Date of Sample TBH 01 Newtown 28/10/2014 TBH 02 Effasu 29/10/2014 TBH 03 Mangyea 30/10/2014 TBH 04 Mpeasem 31/10/2014 TBH 05 Alumatuape 30/11/2014 TBH 06 Jawey 01/12/2014 TBH 07 Annor Adjaye SHS 02/12/2014 TBH 08 Allengenzule 03/12/2014 TBH 09 Agyeza 04/12/2014 TBH 10 Ehoaka 11/01/2015 TBH 11 Duplicate of Ehoaka 12/01/2015 TBH 12 Twenen 13/01/2015 TBH 13 Kengen 14/01/2015 TBH 14 Elloyin 15/01/2015 TBH 15 Kangbunli 16/01/2015 TBH 16 Azuleleounu 17/01/2015 TBH 17 Asanda(1) 24/06/2015 TBH 18 Asanda (2) 25/06/2015 Appendix 11: Available data for the hand dug wells sampled in 2016. Sample ID Location Date Sample Sample Location Date Sample ID ESI 1 Esiama 09/03/2016 BOB 3 Bobrama 09/04/2016 KIK 5 Kikam 09/03/2016 ANI 1 Aniwa 09/05/2016 ANKO 2 Ankobra 09/03/2016 NKRO 1 Nkroful 09/05/2016 ANKO 1 Ankobra 09/03/2016 ESI 7 Esiama 09/05/2016 ANKO 3 Ankobra 09/03/2016 ESI 4 Esiama 09/05/2016 KIK 3 Kikam 09/04/2016 ESI 6 Esiama 09/05/2016 KIK 1 Kikam 09/04/2016 ESI 8 Esiama 09/05/2016 ASAN 2 Asanta 09/04/2016 ANI 2 Aniwa 09/05/2016 KIK 2 Kikam 09/04/2016 NKR 4 Nkroful 09/05/2016 KIK 4 Kikam 09/04/2016 NKRO 5 Nkroful 09/06/2016 ASAN 4 Asanta 09/04/2016 GYEGYE Gyegyekrom 09/06/2016 2 ASAN 5 Asanta 09/04/2016 BOMUA Bomuakpole 09/06/2016 2 KIK 7 Kikam 09/04/2016 ELU 1 Elubo 09/06/2016 ESI 2 Esiama 09/04/2016 AZULE 1 Azulenloanu 09/06/2016 ASAN 6 Asanta 09/04/2016 GYEGYE Gyegyekrom 09/07/2016 1 BOB 2 Bobrama 09/04/2016 AMP 1 Ampain 09/07/2016 ASAN 7 Asanta 09/04/2016 HAAS 1 Half Assini 09/07/2016 SAN 3 Sanwoma 09/04/2016 ELU 2 Elubo 09/07/2016 345 University of Ghana http://ugspace.ug.edu.gh Appendix 12: Available boreholes sampled in 2016 Sample ID Location Date Sample Sample ID Location Date Sample ASAN 6 Asanta 09/03/2016 ALUK 3 Aluku 09/06/2016 SAN 4 Sanwoma 09/03/2016 AZULEN 2 Azulenloa 09/06/2016 SAN 1 Sanwoma 09/03/2016 AZULEN 3 Azuleno 09/06/2016 SAN 2 Sanwoma 09/04/2016 ELU 3 Elubo 09/06/2016 BOB 1 Bobrama 09/04/2016 BOKPO 1 Bomuakpole 09/06/2016 Ankonew 1 Ankobra 09/04/2016 NEWN 1 New Nzulezu 09/06/2016 newsite BOB 4 Bobrama 09/04/2016 ATWI 2 Atwibaso 09/06/2016 ASEM 1 Asemko 09/05/2016 AWIA 1 Awiafoto 09/06/2016 NKR 2 Nkroful 09/05/2016 ANIWA 1 Aniwafuto(chips) 09/06/2016 ESI 3 Esiama 09/05/2016 NEWN 2 New Nzulezu 09/06/2016 NKR 3 Nkroful 09/05/2016 AWIE 1 Awiebo 09/07/2016 ESI 5 Esiama 09/05/2016 AMP 5 Ampain 09/07/2016 SAL 3 Salman 09/06/2016 AlAB 1 Alabokazo 09/07/2016 KAMG 2 Kamgbuli 09/06/2016 ALAB 2 Alabokazo 09/07/2016 KAMG 1 Kamgbuli 09/06/2016 Teleko 1 Telekobokaso 09/07/2016 Amp 2 Ampaim 09/06/2016 OLD Old Kablasuazo 09/07/2016 KABLA 1 Ani sch Aniwa 09/06/2016 FAN 2 Fante new site 09/07/2016 ALUK 2 Aluku 09/06/2016 NYAN 1 Nyanzinli 09/07/2016 SAL 2 Salman 09/06/2016 ATWI 1 Atwibanso 09/07/2016 BOMUA 3 Bomuakpole 09/06/2016 NEWAN 1 New Ankasa 09/07/2016 ALUK 1 Aluku 09/06/2016 BONY 1 Bonyere 09/07/2016 SAL 1 Salaman 09/06/2016 TIEKO 1 Tiekobo 1 09/07/2016 Appendix 13: Available data for the hand dug well sampled in 2017. Sample number Location Date Sample Sample Location Date Sample number Asem 1 Asemda 14/02/2017 NKR 1 Nkroful 30/12/2017 EIK 1 Eikwe 15/02/2017 ANI 2 Aniwa 30/12/2017 ATUA 1 Atuabo 16/02/2017 ANI 1 Aniwa 30/12/2017 BEN 1 Benyin 16/02/2017 KIK 1 Kikam 31/12/2017 ELU 5 Elubo 28/12/2017 ESI 8 Esiama 31/12/2017 ELU 2 Elubo 28/12/2017 KIK 2 Kikam 31/12/2017 ELU 1 Elubo 28/12/2017 KIK 3 Kikam 31/12/2017 GYEGYE 1 Gyegyekrom 28/12/2017 KIK 7 Kikam 31/12/2017 GYEGYE 2 Gyegyekrom 28/12/2017 ESI 4 Esiama 31/12/2017 HASS 1 Half Assini 29/12/2017 AMP 1 Ampaim 31/12/2017 NKR 5 Nkroful 30/12/2017 ESI 7 Esiama 31/12/2017 ALUK1 Aluku 3 30/12/2017 BOB 2 Bobrama 31/12/2017 NKR4 Nkroful 30/12/2017 KIK 4 Kikam 31/12/2017 BOMUA 1 Bomuakpole 30/12/2017 KIK 5 Kikam 31/12/2017 NKR 3 Nkroful 30/12/2017 AZULE 1 Azuleno 31/12/2017 346 University of Ghana http://ugspace.ug.edu.gh Appendix 14: Available data for the boreholes sampled in 2017 Sample Location Date Sample Sample Location Date number number Sample Sanzu1 Sanzule(1) 15/02/2017 AWIA 1 Awiafotu 28/12/2017 junction SAN 2 Sanzule(2) 15/02/2017 NEWN 1 New Nzulazu 29/12/2017 EIK 2 Eikwe(2) 15/02/2017 NEWN 2 New Nzulazu(2) 29/12/2017 SAN 3 sanzule (3) 15/02/2017 BONY 1 Bonyere 29/12/2017 KRIS 1 Krisan(1) 15/02/2017 KAMG 1 Kamgbunli 29/12/2017 NGELEK 2 ngelekpolley(2) 15/02/2017 KAMG 2 Kamgbunli 2 29/12/2017 BA 1 Baku 15/02/2017 SAL 3 Salman 3 29/12/2017 NGE 1 Ngelekyi 15/02/2017 SAL 2 Salman 2 30/12/2017 NGELEK 1 Ngelekazo 16/02/2017 SAL1 Salman 1 30/12/2017 NGELEK 2 Ngelekazo(2) 16/02/2017 SAL 3 Salman(3) 30/12/2017 KEEG 1 Keegan(1) 16/02/2017 NKR4 Nkroful(4) 30/12/2017 ASEM2 Asemda 16/02/2017 BOKPO 1 Bomuakpolley 30/12/2017 TWEN 2 Twenen(2) 16/02/2017 NKR 6 Nkroful (6) 30/12/2017 NKR Nkroful 17/02/2017 ALUK 2 Aluku 2 30/12/2017 ATWI 1 Atwinbanso(1) 28/12/2017 AZULEN 3 Azeneluno 3 30/12/2017 ELU 2 Elubo (2) 28/12/2017 ALUK1 Aluku 1 30/12/2017 AWIA 1 Awiefoto 28/12/2017 Teleko 2 Telekobokaso(2) 30/12/2017 OLD Old 28/12/2017 Amp 5 Ampaim(5) 31/12/2017 KABLA 1 Kablazuaso FAN 2 Fante New 28/12/2017 ESI 6 Esiama (6) 31/12/2017 SITE HAAS 1 Half Assini 28/12/2017 ESI1 Esiama (1) 31/12/2017 TIEKO 1 Tiekobo (1) 28/12/2017 AZULEN 2 Azuleno (2) 31/12/2017 ATWI 2 Atwinbanso (2) 28/12/2017 ESI 5 Esiama(5) 31/12/2017 SAL 5 Salman 5 28/12/2017 ANKONEW Ankobra newsite 31/12/2017 1 ALAB 2 Alabokazo 2 28/12/2017 AMP 2 Ampiam 31/12/2017 NEWAN2 New Ankasa 2 28/12/2017 BOB 4 Bobrama(4) 31/12/2017 ALAB 1 Alabokazo 1 28/12/2017 ASEM1 Asemko(1) 31/12/2017 AZULEN2 Azulenenuo 2 31/12/2017 347 University of Ghana http://ugspace.ug.edu.gh Appendix 15: Available cations and anion data with their ionic balances for boreholes drilled in 2014 to 2015 Sample Location Ca2+ Mg2+ Na+(meq/l) K+(meq/l) Cl- HCO-3(meq/l) SO 2- 4(meq/l) NO - 3 (A/B)*100(Ionic Id (meq/l) (meq/l) (meq/l) (meq/l) Balance NB1 Newtown 1.90 1.86 6.79 0.35 6.32 2.65 0.35 0.00 7.73 NB2 Effasu 0.75 0.06 0.58 0.07 0.56 0.62 0.12 0.00 5.26 NB3 Mangyea 0.55 0.16 0.60 0.03 0.74 0.51 0.00 0.00 3.73 NB4 Mpeasem 1.80 0.27 0.49 0.04 0.99 1.23 0.02 0.00 7.39 NB5 Alumatuape 0.35 0.15 0.32 0.02 0.28 0.33 0.04 0.00 12.37 NB6 Jawey 0.90 0.18 0.24 0.07 0.24 0.82 0.04 0.00 11.71 NB7 Annor 0.60 0.21 0.52 0.04 0.50 0.59 0.12 0.00 6.14 Adjaye SHS NB8 Allengenzule 0.30 0.22 0.71 0.01 0.71 0.25 0.08 0.00 8.64 NB9 Agyeza 1.05 0.37 0.99 0.15 0.85 0.43 0.69 0.00 13.35 NB10 Ehoaka 3.44 0.21 0.13 0.02 0.16 2.65 0.31 0.00 9.93 NB11 Ehoaka 3.44 0.21 0.13 0.02 0.16 2.59 0.31 0.00 11.03 NB12 Twenen 0.30 0.28 0.75 0.04 1.02 0.31 0.23 0.00 -6.17 NB13 Kengen 0.25 0.12 0.43 0.01 0.64 0.10 0.02 0.00 3.61 NB14 Elloyin 0.15 0.18 0.82 0.03 0.88 0.08 0.17 0.00 2.17 NB15 Kangbunli 2.20 1.72 0.94 0.07 0.72 2.80 0.19 0.00 14.10 NB16 Azuleleounu 0.75 0.43 0.63 0.05 0.65 0.59 0.17 0.00 13.97 NB17 Asanda 0.70 0.26 0.85 0.23 0.76 0.54 0.21 0.00 14.87 NB18 Asanda 0.65 0.12 0.33 0.01 0.30 0.49 0.04 0.00 13.86 348 University of Ghana http://ugspace.ug.edu.gh Appendix 16: Available cations and anion data with their ionic balances for hand dug wells sampled in 2016 Sample ID Name of Ca2+ Mg2+ Na+ K+ Cl- HCO -3 SO 2- 4 NO - 3 (A/B)*100 Town (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) ESI 1 Esiama 0.97 0.22 1.43 0.01 0.90 1.00 0.82 0.01 -1.95 NKR 5 Nkroful 0.14 0.12 5.44 1.46 2.20 0.60 3.11 0.02 9.36 KIK 5 Kikam 1.99 0.10 3.12 0.70 2.65 0.80 1.23 0.17 9.88 KIK 3 Kikam 1.76 0.10 3.76 1.06 2.88 0.80 1.52 0.03 12.22 ANI 1 Aniwa 0.43 0.17 1.02 0.27 0.56 0.20 0.61 0.02 14.90 KIK 1 Kikam 0.93 0.25 1.14 0.17 0.85 0.20 0.98 0.09 7.96 AMP 1 Ampain 0.31 0.04 0.23 0.02 0.51 0.08 0.22 0.01 -15.21 ASAN 2 Asanta 0.66 0.21 1.87 0.16 0.62 1.97 0.45 0.02 -2.67 NKR 1 Nkroful 0.46 0.17 0.78 0.15 0.45 0.40 0.46 0.02 8.17 KIK 2 Kikam 0.83 0.31 1.78 0.19 1.18 0.84 0.84 0.02 3.79 BOMUA 2 Bomuakpole 0.55 0.20 1.33 0.02 0.62 0.08 0.85 0.02 14.87 KIK 4 Kikam 1.04 0.44 1.94 0.58 1.47 0.40 1.34 0.04 10.45 ANKO 1 Ankobra 1.25 2.58 4.25 0.20 4.85 0.32 0.99 0.03 14.46 ASAN 4 Asanta 0.90 0.14 0.85 0.06 0.79 0.36 0.77 0.02 0.12 GYEGYE Gyegyekrom 0.67 0.09 0.31 0.01 0.17 0.48 0.42 0.02 -0.99 2 KIK 7 Kikam 0.97 0.41 1.38 0.27 2.09 0.16 0.47 0.01 5.49 ASAN 5 Asanta 0.84 0.19 0.92 0.04 1.13 0.20 1.30 0.02 -14.22 ESI 6 Esiama 0.73 0.04 2.96 0.55 1.86 0.20 1.22 0.04 12.53 349 University of Ghana http://ugspace.ug.edu.gh Appendix 16: Available cations and anion data with their ionic balances for hand dug wells sampled in 2016(Continuation) Sample ID Name of Ca2+ Mg2+ Na+ K+ Cl- HCO - 3 SO 2- NO - 4 3 (A/B)*100 Town (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) ANI 2 Aniwa 0.12 0.32 1.26 0.20 0.23 0.20 1.68 0.00 -5.05 ESI 2 Esiama 0.44 0.14 0.85 0.04 0.45 0.12 0.59 0.02 10.68 ELU 2 Elubo 1.06 0.06 3.57 2.09 2.37 0.24 3.07 0.18 7.30 ASAN 6 Asanta 1.34 0.09 2.98 0.73 1.64 1.20 1.22 0.03 11.37 ANKO 2 Ankobra 1.06 0.76 2.78 0.06 1.75 0.92 0.88 0.01 13.34 ESI 7 Esiama 2.22 0.62 4.88 0.88 3.27 2.80 1.57 0.16 4.93 ESI 4 Esiama 1.65 0.35 0.93 0.13 0.62 1.00 1.11 0.02 5.44 NKR 4 Nkroful 2.01 0.64 1.47 0.25 0.51 0.24 3.08 0.01 6.59 ESI 8 Esiama 3.45 0.17 2.32 0.62 1.64 0.68 3.08 0.02 9.49 GYEGYE Gyegyekrom 0.08 0.09 0.66 0.01 0.39 0.12 0.32 0.01 -0.63 1 ELU 1 Elubo 1.64 0.12 0.99 0.27 0.62 0.76 1.19 0.01 7.88 AZULE 1 Azulenloanu 0.27 0.27 0.99 0.06 0.56 0.28 0.46 0.01 9.65 HAAS 1 Half Assini 1.32 0.03 1.25 0.22 0.68 0.48 1.12 0.01 10.59 BOB 2 Bobrama 0.10 0.10 0.95 0.02 0.56 0.40 0.15 0.02 1.48 ASAN 7 Asanta 0.76 0.67 2.09 0.52 1.07 1.00 1.82 0.01 1.78 SAN 3 Sanwoma 0.18 0.24 0.98 0.05 0.56 0.82 0.13 0.01 -2.46 BOB 3 Bobrama 0.07 0.07 2.78 0.02 1.13 1.47 0.94 0.04 -9.87 ANKO 3 Ankobra 1.91 0.93 4.20 0.37 4.68 1.04 0.96 0.08 4.57 350 University of Ghana http://ugspace.ug.edu.gh Appendix 17: Available cations and anion data with their ionic balances for boreholes sampled in 2016. Sample Id Sample Ca2+ Mg2+ Na+ K+ Cl- HCO - SO 2- NO - 3 4 3 (A/B)*100 Location (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) SAL 3 Salman 1.53 0.16 1.68 0.08 0.17 3.00 0.76 0.01 -6.47 KAMG 2 Kamgbuli 1.44 0.12 0.94 0.04 0.23 0.40 2.53 0.03 -11.44 KAMG 1 Kamgbuli 1.08 0.61 0.30 0.01 1.18 0.60 0.53 0.00 -7.30 ASEM 1 Asemko 0.34 0.30 1.63 0.40 0.68 0.80 0.96 0.02 4.12 Amp 2 Ampaim 0.31 0.54 1.22 0.21 1.02 0.44 0.37 0.01 10.95 Ani sch Aniwa 0.08 0.26 1.22 0.02 0.34 0.24 0.63 0.03 12.31 NKR 2 Nkroful 0.21 0.17 1.98 0.05 0.73 1.20 0.38 0.02 1.75 SAN 2 Sanwoma 0.56 0.04 1.47 0.04 1.47 0.44 0.20 0.03 -0.34 ALUK 2 Aluku 0.56 0.20 3.75 0.25 1.52 0.12 3.02 0.01 1.10 AWIE 1 Awiebo 0.21 0.31 0.59 0.04 0.17 1.00 0.09 0.01 -4.56 ESI 3 Esiama 0.47 0.21 0.69 0.05 0.34 0.24 0.94 0.02 -4.00 AMP 5 Ampain 1.20 0.48 2.81 0.40 0.96 0.28 3.08 0.01 6.00 SAL 2 Salman 0.28 0.21 0.34 0.01 0.45 0.04 0.46 0.03 -8.11 NKR 3 Nkroful 1.63 0.33 1.52 0.03 0.56 1.24 0.93 0.03 11.97 BOB 1 Bobrama 0.11 1.03 1.29 0.04 0.79 0.44 0.88 0.04 6.89 BOMUA 3 Bomuakpole 0.64 0.38 0.81 0.02 0.90 0.20 0.99 0.01 -6.50 SAN 4 Sanwoma 0.41 0.52 0.62 0.03 1.52 0.48 0.00 0.00 -11.76 AlAB 1 Alabokazo 0.78 0.55 0.23 0.01 0.39 0.28 1.31 0.01 -11.99 ALUK 1 Aluku 0.25 0.10 1.01 0.03 0.34 0.98 0.10 0.00 -1.29 ALAB 2 Alabokazo 0.16 0.53 0.86 0.08 1.02 0.44 0.13 0.02 0.65 ASAN 6 Asanta 0.78 0.25 1.31 0.22 0.73 1.20 0.27 0.03 6.88 351 University of Ghana http://ugspace.ug.edu.gh Appendix 17: Available cations and anion data with their ionic balances for boreholes sampled in 2016 (Continuation). Sample Id Sample Location Ca2+ Mg2+ Na+ K+ Cl- HCO - SO 2- NO - 3 4 3 (A/B)*100 (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) SAL 1 Salaman 0.18 0.14 0.31 0.01 0.11 0.08 0.52 0.02 -6.31 Teleko 1 Telekobokaso 0.85 0.39 1.27 0.02 1.02 0.04 1.38 0.01 1.56 ALUK 3 Aluku 0.49 0.21 1.79 0.26 1.41 0.12 1.01 0.02 3.53 ESI 5 Esiama 0.12 0.13 0.65 0.04 0.45 0.60 0.03 0.01 -7.58 Ankonew 1 Ankobra newsite 2.90 0.20 1.49 0.10 1.97 1.52 0.85 0.00 3.72 SAN 1 Sanwoma 1.87 0.10 1.24 0.08 0.51 2.95 0.08 0.02 -3.98 OLD KABLA 1 Old Kablasuazo 0.08 0.08 1.49 0.01 0.68 0.20 0.95 0.01 -5.00 AZULEN 2 Azulenloa 0.48 0.09 0.81 0.02 0.62 0.40 0.03 0.01 13.73 AZULEN 3 Azuleno 0.78 1.35 1.29 0.07 1.13 0.20 1.40 0.01 12.24 FAN 2 Fante new site 0.70 0.79 0.37 0.08 0.23 0.36 0.80 0.02 15.59 ELU 3 Elubo 0.47 0.45 2.11 0.20 1.18 0.12 1.36 0.01 9.70 BOKPO 1 Bomuakpole 0.79 0.73 1.17 0.02 0.39 1.97 0.12 0.02 4.18 NYAN 1 NyanZinli 0.68 0.03 1.10 0.44 0.68 0.80 0.21 0.00 14.21 ATWI 1 Atwibanso 0.09 0.11 0.52 0.01 0.28 0.16 0.24 0.02 1.62 NEWN 1 New Nzulezu 0.18 0.07 0.16 0.01 0.17 0.08 0.21 0.01 -5.20 NEWAN 1 NEW Ankasa 1.24 0.06 0.40 0.02 0.28 0.28 0.82 0.01 10.98 BONY 1 Bonyere 0.18 0.17 2.49 0.17 1.41 0.84 0.54 0.04 3.34 ATWI 2 Atwibaso 0.03 0.14 1.25 0.02 0.56 0.20 0.38 0.01 10.62 AWIA 1 Awiafoto 0.94 0.67 0.35 0.09 0.56 0.68 0.43 0.04 8.77 ANIWA 1 Aniwafuto(chips) 0.15 0.17 0.70 0.14 0.17 0.60 0.58 0.03 -8.53 NEWN 2 New Nzulezu 1.11 0.54 0.63 0.06 2.37 0.08 0.34 0.07 -10.20 TIEKO 1 Tiekobo 1 0.31 0.01 0.80 0.09 0.11 0.28 0.50 0.01 15.17 BOB 4 Bobrama 0.93 0.23 1.05 0.01 1.13 0.12 0.60 0.01 8.77 352 University of Ghana http://ugspace.ug.edu.gh Appendix 18: Available cations and anion data with their ionic balances for hand dug wells sampled in 2017. Sample Sample Location Ca2+ Mg2+ Na+ K+ Cl- HCO - SO 2- NO -3 4 3 (B/A)*100 Id (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) NKR 5 Nkroful 0.31 0.11 0.80 0.03 0.68 0.24 0.14 0.01 8.28 ALU 3 Aluku 0.53 0.49 1.96 0.19 1.64 0.28 0.61 0.01 11.08 KIK 1 Kikam 1.30 0.49 1.61 0.19 0.56 3.00 0.04 0.01 -0.08 NKR 4 Nkroful 0.24 0.06 0.53 0.02 0.51 0.20 0.00 0.01 8.55 ESI 8 Esiama 3.60 1.05 1.76 0.53 3.38 2.08 0.42 0.00 8.30 Elu 5 Elubo 0.46 0.57 3.69 0.68 3.78 0.20 0.17 0.05 12.59 Kik2 Kikam 1.06 0.48 1.61 0.47 1.30 1.80 0.00 0.01 7.67 Half Ass Half Assini 0.79 0.13 0.47 0.09 0.73 0.30 0.17 0.01 10.12 1 Bomua Bomuakpole 1.12 0.38 1.16 0.18 1.52 1.20 0.28 0.02 -3.07 1 NKR 3 Nkroful 0.56 0.33 1.15 0.15 0.45 1.00 0.17 0.03 14.06 KIK 3 Kikam 2.30 0.58 3.14 0.82 2.14 4.80 0.96 0.02 -7.38 KIK7 Kikam 0.66 0.36 1.03 0.30 2.26 0.28 0.04 0.02 -4.99 ELU2 Elubo 1.76 0.05 3.18 0.21 3.78 0.04 0.17 0.05 12.54 NKR1 Nkroful 2.47 1.24 4.79 1.02 1.58 3.80 1.61 0.02 15.19 ANI 2 Aniwa 1.12 0.38 1.16 0.18 0.73 2.00 0.75 0.01 -10.31 353 University of Ghana http://ugspace.ug.edu.gh Appendix 18: Available cations and anion data with their ionic balances for hand dug wells sampled in 2017 (Continuation). Sample Id Sample Location Ca2+ Mg2+ Na+ K+ Cl- HCO - SO 2-3 4 NO - 3 (B/A)*100 (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) ASEM 1 Asemda 0.24 1.07 0.80 0.13 0.11 1.47 0.97 0.02 -7.18 GYEGYE Gyegyekrom 0.52 0.12 0.37 0.02 0.17 0.32 0.39 0.02 6.65 2 ESI 4 Esiama 3.25 0.83 1.48 0.21 0.90 5.79 0.28 0.01 -9.57 AMP 1 Ampaim 0.18 0.10 0.36 0.04 0.56 0.24 0.00 0.01 -8.64 EIK 1 Eikwe 1.22 0.66 3.78 0.28 1.52 2.89 1.43 0.04 0.54 ATU 1 Atuabo 1.05 0.79 2.12 0.12 0.11 2.00 1.01 0.02 12.92 BENY 1 Benyin 2.98 1.16 3.50 0.28 2.99 1.96 1.03 0.00 13.88 ESI 7 Esiama 2.47 0.78 4.47 0.87 0.73 4.00 1.93 0.02 12.57 GYEGYE Gyegyekrom 0.07 0.13 0.26 0.02 0.11 0.40 0.01 0.00 -5.14 1 BOB 2 Bobrama 0.41 0.56 1.58 0.51 1.30 0.80 0.27 0.01 12.41 ELU 1 Elubo 2.06 0.24 0.83 0.36 0.68 1.00 0.98 0.06 12.52 KIK 4 Kikam 0.85 0.51 1.25 0.18 0.79 0.60 2.04 0.02 -10.38 KIK 5 Kikam 0.48 0.37 1.77 0.21 1.41 1.60 0.58 0.01 -12.03 Azule 1 Azuleno 0.35 0.39 1.07 0.08 0.56 0.98 0.00 0.01 9.43 ANI 1 Aniwa 0.39 0.27 1.03 0.23 0.39 1.00 0.76 0.01 -6.33 354 University of Ghana http://ugspace.ug.edu.gh Appendix 19: Available cations and anion data with their ionic balances for the boreholes sampled in 2017. Sample ID Sample Ca2+ Mg2+ Na+ K+ Cl- HCO - 2- -3 SO4 NO3 (A/B)*100 Location (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) Sanzu 1 Sanzule 0.08 0.08 0.82 0.06 0.23 0.16 0.83 0.01 -8.10 NKR 2 Nkroful 0.42 0.36 2.01 0.04 1.07 0.32 1.36 0.00 1.21 AMP 2 Ampaim 0.15 0.65 0.92 0.07 0.85 0.52 0.14 0.00 8.85 ATWI 1 Atwinbanso 0.06 0.17 0.64 0.04 0.56 0.40 0.00 0.00 -3.23 ELU 2 Elubo 0.32 0.59 1.96 0.19 1.58 0.80 0.00 0.02 12.13 AWI 1 Awiefoto 0.14 0.14 0.42 0.13 0.17 0.80 0.00 0.03 -9.63 ESI 6 Esiama 1.59 0.78 3.73 0.94 2.54 1.40 2.96 0.03 0.77 OLD Old Kablazuaso 0.05 0.14 0.48 0.01 0.56 0.24 0.01 0.01 -9.30 KABLA 1 FAN 2 Fante New 0.57 0.16 0.85 0.15 0.23 0.96 0.34 0.02 6.06 Town HAAS 1 Half Assini 0.16 0.04 1.60 0.07 0.90 0.20 0.56 0.00 5.67 SAL 1 Salman 0.15 0.22 0.33 0.00 0.17 0.66 0.00 0.00 -7.84 SAL 2 Salman 0.68 0.77 0.73 0.01 0.17 1.80 0.04 0.00 4.24 ESI 1 Esiama 1.35 0.40 2.39 0.07 1.30 2.80 0.26 0.02 -1.95 AZULEN 2 Azuleno 1.00 1.90 1.50 0.08 0.39 1.40 3.45 0.01 -7.87 BOKPO 1 Bomuakpolley 0.11 0.41 0.58 0.02 0.34 1.15 0.00 0.00 -14.19 SAL 3 Salman 0.24 0.28 0.35 0.01 0.11 0.44 0.21 0.02 5.92 NKR 4 Nkroful 0.18 0.22 0.63 0.03 0.56 0.44 0.00 0.01 2.61 355 University of Ghana http://ugspace.ug.edu.gh Appendix 19: Available cations and anion data with their ionic balances for the boreholes sampled in 2017 (Continuation). Sample ID Sampling Ca2+ Mg2+ Na+ K+ Cl- HCO - 2- -3 SO4 NO3 (A/B)*100 Location (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) ESI 5 Esiama 0.10 0.92 0.60 0.05 0.45 0.44 0.31 0.05 14.51 ANKONEW Ankobra 0.32 0.78 0.78 0.03 0.34 1.00 0.14 0.01 12.18 1 newsite AMP 5 Ampin 0.27 0.33 0.52 0.04 0.11 1.20 0.00 0.01 -6.61 NKR 6 Nkroful 0.92 0.39 1.22 0.03 0.68 0.72 0.53 0.03 13.52 NEWN 1 New Nzulazu 0.06 0.08 0.28 0.02 0.17 0.16 0.00 0.01 11.61 TIEKO 1 Tiekobo 0.04 0.05 0.16 0.02 0.11 0.16 0.05 0.00 -8.76 BOB 4 Bobrama 0.12 1.42 1.34 0.03 1.18 1.20 0.10 0.01 7.91 NEWN 2 New Nzulazu 0.88 0.68 0.70 0.07 0.06 2.20 0.15 0.01 -1.68 BONY 1 Bonyere 0.18 0.25 1.15 0.16 0.51 1.00 0.10 0.00 3.64 KAMG 1 Kamgbunli 1.91 2.97 1.13 0.05 0.90 3.00 0.88 0.00 11.67 ALU 2 Aluku 0.32 0.29 1.97 0.28 1.64 0.16 0.74 0.02 5.89 ATW 2 Atwinbanso 0.04 0.18 0.75 0.05 0.62 0.04 0.22 0.01 6.94 ASEM1 Asemko 0.20 0.44 0.72 0.02 0.23 0.98 0.00 0.01 6.42 SAL 5 Salman 2.40 1.32 0.74 0.02 0.11 3.60 0.38 0.01 4.46 Azulen 3 Azeneluno 1.00 1.98 1.50 0.08 0.39 1.40 3.45 0.01 -7.00 ALUK 1 Aluku 0.28 0.15 0.52 0.01 0.34 0.20 0.16 0.02 14.47 ALAB 2 Alabokazo 0.69 0.55 0.23 0.01 0.96 0.80 0.07 0.01 -10.87 KAM 2 Kamgbunli 0.48 0.70 0.36 0.02 0.34 0.56 0.39 0.01 9.66 NEWAN 2 New Ankasa 0.32 0.37 0.51 0.03 0.96 0.40 0.17 0.02 -11.69 TELEKO 2 Telekobokaso 0.84 0.56 1.42 0.03 0.56 2.00 0.63 0.00 -5.71 356 University of Ghana http://ugspace.ug.edu.gh Appendix 19: Available cations and anion data with their ionic balances for the boreholes sampled in 2017(Continuation) Sample ID Sampling Ca2+ Mg2+ Na+ (meq/l) K+ (meq/l) Cl- (meq/l) HCO -3 SO 2- 4 NO - 3 (A/B)*100 Location (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) ALAB 1 Alabokazo 0.19 0.70 0.96 0.09 0.62 1.80 0.00 0.02 -11.47 AWIA 1 Awiafotu 0.40 0.93 0.44 0.02 0.51 0.56 0.26 0.00 14.63 junction AZULEN 2 Azulenenuo 0.75 0.88 1.00 0.04 0.62 1.80 0.05 0.02 3.37 SAL 3 Salman 0.32 0.54 1.49 0.04 0.85 0.98 0.00 0.07 11.57 SAN 2 Sanzule 0.14 0.54 2.14 0.06 0.85 0.44 0.97 0.01 12.16 NGELEK 1 Ngelekazo 1.01 0.19 0.64 0.02 0.11 0.32 1.12 0.02 8.58 EIK 2 Eikwe 0.27 1.78 0.56 0.11 0.23 1.08 1.43 0.02 -0.74 NGELEK 2 Ngelekazo 0.53 0.07 0.66 0.08 0.34 0.32 0.62 0.00 2.20 SAN 3 Sanzule 0.68 1.53 0.57 0.07 0.34 1.24 1.09 0.03 2.75 KRIS 1 Krisan 0.12 0.30 1.97 0.17 0.68 0.40 1.56 0.00 -1.55 NGELEK 2 Ngelekpolley 0.53 0.19 1.04 0.19 0.45 0.44 1.40 0.02 -8.68 BA 1 Baku 0.14 1.18 1.36 0.08 0.56 0.92 1.48 0.00 -3.77 KEEG 1 Keegan 0.41 0.76 2.46 0.25 0.34 1.20 1.46 0.03 12.47 ASEM 2 Asemda 0.36 0.43 2.18 0.17 0.79 0.60 1.62 0.02 1.88 TWENE 2 Twenen 0.05 0.43 1.50 0.03 0.62 0.40 1.47 0.02 -10.74 NGE 1 Ngelekyi 0.58 0.02 0.74 0.08 0.34 0.04 1.40 0.00 -11.61 357 University of Ghana http://ugspace.ug.edu.gh Appendix 20: Lithological Logs of the Boreholes Drilled Across the Lower Tano River Basin 358 University of Ghana http://ugspace.ug.edu.gh Appendix 20: Lithological Logs of the Boreholes Drilled Across the Lower Tano River Basin (Continuation) 359 University of Ghana http://ugspace.ug.edu.gh Appendix 20: Lithological Logs of the Boreholes Drilled Across the Lower Tano River Basin(Continuation) 360 University of Ghana http://ugspace.ug.edu.gh Appendix 20: Lithological Logs of the Boreholes Drilled Across the Lower Tano River Basin (Continuation) 361 University of Ghana http://ugspace.ug.edu.gh Appendix 20: Lithological Logs of the Boreholes Drilled Across the Lower Tano River Basin (Continuation) 362 University of Ghana http://ugspace.ug.edu.gh Appendix 20: Lithological Logs of the Boreholes Drilled Across the Lower Tano River Basin 363 University of Ghana http://ugspace.ug.edu.gh Appendix 21: Fe2+/SO 2- 4 ratio data for the boreholes drilled in 2013 within the Lower Tano river Basin. Towns latitude longitude Fe2+ SO 2+ Fe2+/SO 2- 4 4 Alumatoape 5.06432 -2.9435 0.00 4.97 0.00 Mpeasem 5.07096 -2.99782 0.39 6.09 0.06 Kamgbunli 4.97656 -2.41541 0.47 6.09 0.08 Elubo 5.28333 -2.76667 0.04 5.06 0.01 Bobrama 4.923303 -2.31477 0.01 6.31 0.00 Akanko 5.002748 -2.2372 0.30 11.00 0.03 Gwira ampansie 5.085727 -2.21155 0.32 4.19 0.08 Ndatiem 4.890833 -2.205 0.00 8.00 0.00 Ayisakro 4.89283 -2.21284 0.00 6.91 0.00 Kegyina 4.91667 -2.13333 0.00 4.11 0.00 Nyamebekyere 5.2 -2.4333 0.00 9.04 0.00 Akonu 4.83502 -2.20599 0.00 6.02 0.00 Ellanda Wharf 5.116 -2.733 0.21 10.00 0.02 Gwira Aiyinase 5.04476 -2.14201 0.01 7.00 0.00 Sanzule 4.96305 -2.4549 0.00 4.61 0.00 Nyamebekyere 5.21094 -2.43261 0.52 6.81 0.08 Samenye 5.08333 -2.55 0.00 10.00 0.00 Domiabra 5.15 -2.3 0.00 7.05 0.00 Sowudazem 5.05175 -2.88052 0.00 4.00 0.00 Alapoke 5.0127 -2.466 0.00 7.21 0.00 Aniwafutu 5.16213 -2.68665 0.22 7.00 0.03 Ankyernin 4.86833 -2.24139 0.02 0.01 2.00 Fawoman 5.347301 -2.71136 0.08 9.00 0.01 Dadwen 4.90286 -2.16061 0.37 10.00 0.04 Akpendue 5.01 667 -2. 45 0.00 7.01 0.00 Obengkrom 0.00 7.19 0.00 Cocoatown 5.31952 -2.73677 0.00 6.14 0.00 Kutukrom 5.298 -2.203 0.28 11.00 0.03 Ghana Nungua 5.35 -2.7667 0.00 6.01 0.00 Ankajeri 4.99812 -2.22773 0.00 5.13 0.00 Appendix 22: Fe2+/SO 2- 4 ratio data for boreholes drilled from 2014 to 2015 within the Lower Tano river Basin. Sample Location Latitude Longitude Fe2+ SO 2- 4 Fe2+/SO 2- 4 Newtown 5.08956 -3.09263 0.30 17.00 0.02 Effasu 5.08291 -3.04876 0.30 6.00 0.0 5 Mangyea 5.07755 -3.02855 5.00 BDL Mpeasem 5.07096 -2.99782 0.20 1.00 0.20 Alumatuape 5.06432 -2.9435 0.20 2.00 0.10 Jawey 5.06369 -2.93488 0.40 2.00 0.20 Annor Adjaye SHS 5.02144 -2.71708 0.00 6.00 0.00 Allengenzule 5.0098 -2.68806 0.00 4.00 0.00 Agyeza 5.01104 -2.69478 0.30 33.00 0.01 Ehoaka 5.02567 -2.68519 0.20 15.00 0.01 Ehoaka 5.02567 -2.68519 0.30 15.00 0.02 Twenen 5.0065 -2.67694 1.80 11.00 0.16 Kengen 5.00228 -2.64697 0.60 1.00 0.60 Elloyin 4.99467 -2.62214 0.20 8.00 0.03 Kangbunli 4.97656 -2.41541 0.20 9.00 0.02 Azuleleounu 4.94913 -2.3782 0.00 8.00 0.00 Asanda(1) 4.91546 -2.29158 0.10 10.00 0.01 Asanda (2) 4.91425 -2.2863 0.30 2.00 0.15 364 University of Ghana http://ugspace.ug.edu.gh Appendix 23: Fe2+ /SO 2-4 ratio data for hand dug wells sampled in 2016 within the Lower Tano river Basin. fCommunity Latitude(˚N Longitude(˚W Fe2+ SO 2- Fe2+/SO 2 Community Latitude(˚N Longitude(˚W Fe2+ SO 2- 2+4 4 4 Fe ) ) - ) ) /SO 2- 4 Esiama 4.9344 -2.33813 0.33 39.62 0.01 Aniwa 4.9233 -2.32594 0.2 80.49 0.00 6 Nkroful 4.98655 -2.32747 8.74 149.51 0.06 Esiama 4.93219 -2.34206 0.1 28.44 0.00 2 Kikam 4.92662 -2.32500 0.86 59.23 0.01 Elubo 5.29211 -2.77604 0.5 147.2 0.00 7 1 Kikam 4.92529 -2.32464 0.52 72.85 0.01 Asanta 4.91073 -2.29116 0.4 58.74 0.01 7 Aniwa 4.93604 -2.35132 0.27 29.52 0.01 Ankobra 4.90062 -2.27150 0.5 42.26 0.01 0 Kikam 4.92585 -2.32154 0.19 47.17 0.00 Esiama 4.93607 -2.35018 0.6 75.30 0.01 7 Ampain 4.95799 -2.39705 0.01 10.45 0.00 Esiama 4.93521 -2.34561 0.5 53.25 0.01 3 Asanta 4.90925 -2.28399 0.16 21.48 0.01 Nkroful 4.98629 -2.32675 0.5 147.7 0.00 8 6 Nkroful 4.9545 -2.33259 0.14 21.87 0.01 Esiama 4.93604 -2.35132 1.0 148.1 0.01 1 6 Kikam 4.92629 -2.32084 0.11 40.30 0.00 Gyegyekro 5.22398 -2.72766 2.7 15.28 0.18 m 1 Bomuakpole 4.99964 -2.33299 0.15 40.66 0.00 Elubo 5.28919 -2.77933 0.9 57.26 0.02 3 Kikam 4.92601 -2.32429 0.27 64.23 0.00 Azulenloan 4.94966 -2.37797 0.3 21.97 0.01 u 3 Ankobra 4.90094 -2.27204 0.36 47.38 0.01 Half 5.05041 -2.88695 0.0 53.93 0.00 Assin(1) 6 Asanta 4.91254 -2.29152 0.24 37.07 0.01 Bobrama 4.91499 -2.29979 7.00 0.00 gyegyEKRO 5.22464 -2.72497 0.14 20.40 0.01 Asanta 4.91105 -2.29195 0.0 87.38 0.00 M 6 365 University of Ghana http://ugspace.ug.edu.gh Kikam 4.92884 -2.32364 0.18 22.56 0.01 Sanwoma 4.90392 -2.27359 0.3 6.23 0.05 1 Asanta 4.91587 -2.29252 0.12 62.46 0.00 Bobrama 4.91781 -2.29679 0.0 45.25 0.00 3 Esiama 4.94086 -2.34531 0.46 58.64 0.01 Ankobra (3) 4.90124 -2.2707 0.0 45.89 0.00 4 Appendix 24: Fe2+ /SO 2-4 ratio data for boreholes sampled in 2016 within the Lower Tano river Basin. Community Latitude(˚N) Longitude(˚W) Fe2+ SO 2- 2+4 Fe /SO 2- 4 Community Latitude(˚N) Longitude(˚W) Fe2+ SO 2- Fe2+/SO 2- 4 4 Salman(3) 5.00087 -2.22071 2.58 36.58 0.07 Telekobokaso 4.98707 -2.32713 0.17 66.28 0.00 Kamgbuli 4.98212 -2.41549 6.22 121.36 0.05 Aluku 4.99479 -2.26450 0.12 48.74 0.00 Kamgbuli 4.97767 -2.41583 3.78 25.24 0.15 Esiama 4.93708 -2.34753 0.04 1.58 0.03 Asemko 4.92277 -2.31524 0.14 46.28 0.00 Ankobra newsite 4.90565 -2.27132 1.46 40.70 0.04 Ampaim 4.95724 -2.40086 0.05 17.76 0.00 Sanwoma 4.90395 -2.27412 0.63 3.64 0.17 Aniwa 4.99158 -2.32870 1.17 30.30 0.04 Old Kablasuazo 5.027914 -2.773563 0.00 45.40 0.00 Nkroful 4.95619 -2.33067 0.04 18.20 0.00 Azulenloa 4.94894 -2.37827 9.85 1.48 6.66 Sanwoma 4.90604 -2.27475 0.08 9.50 0.01 Azuleno 4.94827 -2.38005 0.24 67.07 0.00 Aluku 4.99554 -2.26439 0.17 144.96 0.00 Fante new site 5.18559 -2.68215 3.93 38.64 0.10 Awiebo 5.03249 -2.44930 0.09 4.26 0.02 Elubo 5.29322 -2.77609 0.07 65.08 0.00 Esiama 4.93109 -2.34287 0.08 44.91 0.00 Bomuakpole(1) 4.99989 -2.33273 1.36 5.60 0.24 Ampain 4.95673 -2.40156 0.98 148.16 0.01 NyanZinli(1) 4.96455 -2.41607 0.17 10.01 0.02 Salman 5.00452 -2.22655 0.05 21.97 0.00 Atwibanso(1) 5.04212 -2.84168 1.79 11.54 0.15 Nkroful 4.97647 -2.32104 1.84 44.72 0.04 New Nzulezu(1) 5.09191 -2.57354 0.00 10.29 0.00 Bobrama 4.91557 -2.30108 0.07 42.17 0.00 NEW Ankasa 5.19929 -2.69873 0.00 39.32 0.00 Bomuakpole 5.00052 -2.33228 0.76 47.56 0.02 Bonyere 5.01905 -2.72693 0.04 25.70 0.00 Sanwoma 4.90566 -2.27330 0.91 0.23 4.02 Atwibaso(2) 5.04154 -2.84074 0.01 18.34 0.00 Alabokazo 4.9948 -2.43112 0.20 62.79 0.00 Awiafoto 5.16214 -2.68664 41.98 20.79 2.02 366 University of Ghana http://ugspace.ug.edu.gh Aluku (1) 4.997 -2.26425 0.05 4.80 0.01 Aniwafuto(chips) 5.16436 -2.68576 0.06 27.95 0.00 Alabokazo 4.99548 -2.43462 0.04 6.15 0.01 New Nzulezu(2) 5.09097 -2.57487 0.32 16.50 0.02 Asanta(6) 4.91073 -2.29116 0.16 12.95 0.01 Tiekobo 1 5.05328 -2.69204 BDL 23.83 BDL Salaman(1) 4.99815 -2.2779 47.42 25.01 1.90 Bobrama 4.91497 -2.29765 0.02 29.03 0.00 Appendix 25: Fe2+ /SO 2-4 ratio data for hand dug wells sampled in 2017 within the Lower Tano river Basin. Community Latitude(˚N) Longitude(˚W) Fe SO Fe/SO Community Latitude(˚N) Longitude(˚W) Fe SO Fe/SO Nkroful (5) 4.94362 -2.34148 6.56 0.00 Asemda 4.98893 -2.53825 0.1472 46.60 0.00 Aluku 3 4.99472 -2.26495 0.02 29.34 0.00 Gyegyekrom(2) 5.22475 -2.72503 0.02149 18.96 0.00 Kikam 1 4.92572 -2.32163 0.11 1.80 0.06 Esiama 4 4.93525 -2.34557 0.3096 13.44 0.02 Nkroful (2) 4.96518 -2.32432 BDL BDL BDL Ampaim (4) 4.94765 -2.37477 BDL BDL BDL Esiama 8 4.93602 -2.35132 0.37 20.00 0.02 Eikwe 4.9641 -2.47050 0.2805 68.61 0.00 Elubo (5) 5.29075 -2.77642 0.06 8.16 0.01 Atuabo 4.98172 -2.55733 0.3033 48.52 0.01 Kikam 2 4.927 -2.32365 0.09 BDL BDL Benyin 4.98743 -2.58693 0.6054 49.67 0.01 Half Assin 5.05047 -2.88690 0.06 8.03 0.01 Esiama 7 4.93607 -2.35018 0.2236 92.56 0.00 Bomuakpole(1) 4.99963 -2.33297 BDL 13.28 BDL Gyegyekrom(1) 5.22397 -2.72767 BDL 0.49 BDL Nkroful(3) 4.96425 -2.32393 BDL 8.36 BDL bobrama(2) 4.91482 -2.29978 BDL 12.95 BDL Kikam (3) 4.9265 -2.32498 0.2073 46.23 0.00 Elubo(1) 5.28915 -2.77917 0.2869 46.96 0.01 Kikam (7) 4.92832 -2.32653 0.03468 1.74 0.02 Kikam 4.92885 -2.32460 0.06027 97.76 0.00 Elubo(5) 5.29387 -2.77643 BDL 8.16 BDL Kikam (5) 4.92887 -2.32362 0.02421 27.87 0.00 Nkroful(1) 4.96638 -2.32527 0.2168 77.36 0.00 Azuleno(1) 4.9497 -2.37797 BDL BDL BDL Aniwa(2) 4.98707 -2.32712 0.05197 36.07 0.00 Aniwa(1) 4.98655 -2.32747 BDL 36.56 BDL 367 University of Ghana http://ugspace.ug.edu.gh Appendix 26: Fe2+ /SO 2-4 ratio data for Boreholes sampled in 2017 within the Lower Tano river Basin. Community Latitude(˚N) Longitude(˚W) Fe2+ SO 2- Fe2+/SO 2- 4 4 Community Latitude(˚N) Longitude(˚W) Fe 2+ SO 2- Fe2+/SO 2- 4 4 Sanzule(1) 4.96523 -2.45497 BDL 39.91 Aluku 2 4.99477 -2.26457 BDL 35.36 Nyaniba 4.94373 -2.34152 0.15 65.08 0.00 Atwinbanso (2) 5.04155 -2.84072 BDL 10.49 Ampaim(5) 4.95667 -2.40162 0.04 6.56 0.0 1 Asemko(1) 4.92278 -2.31527 0.28 0.00 Atwinbanso(1) 5.0421 -2.84163 BDL 0.00 Salman 5 5.00088 -2.22070 0.04 18.16 0.0 0 Elubo (2) 5.29315 -2.77600 0.01 0.0 0.0 0 Azeneluno 3 4.94827 -2.38005 BDL 165.76 Awiefoto 5.16213 -2.68665 BDL 0.00 Aluku 1 4.99697 -2.26427 0.03 7.76 0.00 Esiama (6) 4.93705 -2.34757 0.14 142.16 0.00 Alabokazo 2 4.99483 -2.43112 0.02 3.44 0.0 1 Old Kablazuaso 5.02812 -2.77367 0.01 0.33 0.03 Kamgbunli 2 4.98212 -2.41548 BDL 18.56 Fante New 5.18602 -2.68060 0.01 16.16 0.00 Ankasa 2 5.19878 -2.69985 0.07 8.36 0.01 Town(2) half Assin SHS 5.05462 -2.87702 BDL 27.05 Telekobokaso(2) 4.97647 -2.32103 BDL 30.33 Salman 2 4.99812 -2.22773 BDL 0.00 Alabokazo 1 4.99548 -2.43460 BDL 0.00 Salman 1 4.99588 -2.22602 0.05 1.97 0.02 Awiafotu junction 5.17885 -2.67742 0.01 12.62 0.00 Esiama (1) 4.93485 -2.33815 0.10 12.62 0.01 Azulenenuo 2 4.94893 -2.37828 0.00 2.62 0.00 Azuleno (2) 4.94857 -2.38005 0.04 165.76 0.0 0 Salman 3 4.9983 -2.22575 0.10 0.00 103.90 Bomuakpolley 4.99158 -2.32867 BDL 0.00 Sanzule(2) 4.96305 -2.45490 0.10 46.56 0.00 Salman(3) 5.00152 -2.22655 BDL 10.16 Ngelekazo(kerrela hotel) 4.99107 -2.60290 0.09 53.61 0.00 Nkroful(4) 4.95625 -2.33073 BDL 0.00 Eikwe(2) 4.96878 -2.47097 0.10 68.61 0.00 Esiama(5) 4.93623 -2.34815 0.01 14.96 0.0 0 Ngelekazo(2) 4.99123 -2.60715 0.20 30.00 0.01 Ankobra newsite 4.90605 -2.27475 BDL 6.89 sanzule (3) 4.96128 -2.45525 0.06 52.46 0.00 Ampin 4.9583 -2.39888 0.04 0.00 0.0 0 Krisan(1) 4.96312 -2.46242 0.12 74.84 0.00 Nkroful (6) 4.944 -2.34132 BDL 25.36 ngelekpolley(2) 4.96728 -2.48238 0.11 67.30 0.00 New Nzulazu 5.09192 -2.57355 BDL 0.00 Baku 4.97165 -2.50010 0.14 71.23 0.00 Tiekobo (1) 5.05327 -2.69207 BDL 2.46 Keegan(1) 4.99907 -2.63940 0.21 70.25 0.00 Bobrama(4) 4.91557 -2.30108 0.07 4.75 0.0 1 Asemda 4.98817 -2.54078 0.19 77.95 0.00 New Nzulazu(2) 5.09097 -2.57483 BDL 7.36 Twenen(2) 5.0081 -2.67930 0.11 70.50 0.00 Bonyere 5.01908 -2.72690 0.17 4.92 0.03 Ngel ekyi 4.96 935 -2.49 282 0.1 4 67. 30 0.0 0 Kamgbunli 4.97768 -2.41582 0.00 42.46 0.00 368 University of Ghana http://ugspace.ug.edu.gh Appendix 27 Statistical summary of Chemical indices for the boreholes (Sampled years: 2013 and 2014 to 2015) 2013 2014-2015 Parameters WQI MH% WQI SAR Na% RSC (meq/L) MH% PI% Number of samples 30 30 18 18 18 18 18 18 Mean 7.15 35.96 130.04 1.17 41.15 -0.42 27.60 82.82 Standard Error 3.22 1.57 19.46 0.26 4.63 0.05 3.48 4.28 Median 0.10 39.46 93.99 0.94 43.41 -0.38 26.94 85.02 Mode N/A 18.46 N/A N/A N/A N/A N/A N/A Standard Deviation 17.66 8.61 82.57 1.12 19.63 0.23 14.77 18.15 Sample Variance 311.86 74.21 6817.76 1.25 385.20 0.05 218.04 329.34 Kurtosis 6.54 -0.55 -0.60 9.98 -0.47 -0.22 -1.25 -0.77 Skewness 2.70 -0.70 0.74 2.85 -0.48 -0.43 -0.03 -0.58 Range 67.87 28.98 262.89 5.03 67.10 0.85 43.74 56.27 Minimum 0.00 18.46 26.64 0.11 4.47 -0.90 5.77 49.26 Maximum 67.87 47.45 289.52 5.14 71.57 -0.05 49.51 105.53 Sum 214.45 1078.88 2340.80 21.00 740.71 -7.57 496.82 1490.69 Confidence Level (95.0%) 6.59 3.22 41.06 0.56 9.76 0.11 7.34 9.02 369 University of Ghana http://ugspace.ug.edu.gh Appendix 28 Statistical summary of Chemical indices for the hand dug wells (Sampled years: 2016 and 2017) 2016 2017 Parameters WQI SAR Na% RSC MH% PI% WQI SAR Na% RSC MH% PI% (mg/L) (mg/L) Number of samples 36 36 36 36 36 36 30 30 30 30 30 30 Mean 1376.58 2.86 62.19 -0.66 27.28 87.75 59.48 1.97 55.33 -0.11 33.98 93.64 Standard Error 706.37 0.45 2.65 0.16 3.18 3.67 8.22 0.20 2.30 0.18 3.08 4.93 Median 43.76 2.21 63.16 -0.51 24.16 85.73 41.06 1.72 58.09 0.03 32.21 90.71 Mode N/A N/A N/A N/A N/A N/A N/A 1.33 46.97 N/A 25.52 N/A Standard Deviation 4238.24 2.72 15.88 0.95 19.07 22.02 45.04 1.08 12.60 1.01 16.88 26.99 Sample Variance 17962637.16 7.41 252.32 0.90 363.85 485.07 2028.31 1.17 158.68 1.02 285.02 728.20 Kurtosis 16.50 12.76 -0.17 2.32 -0.41 0.35 -0.10 1.10 -0.39 0.69 1.00 5.92 Skewness 4.04 3.33 0.10 -0.91 0.65 0.70 1.01 1.12 -0.43 -0.41 0.81 1.78 Range 21310.22 14.61 66.56 4.84 69.93 90.00 162.88 4.48 51.55 4.49 78.48 144.87 Minimum -0.01 0.51 29.82 -3.51 2.48 47.55 -0.04 0.65 29.27 -2.57 2.95 49.98 Maximum 21310.21 15.12 96.38 1.33 72.41 137.56 162.84 5.12 80.82 1.92 81.44 194.85 Sum 49556.79 103.07 2238.80 -23.73 982.13 3158.94 1784.51 58.96 1659.96 -3.25 1019.32 2809.23 Confidence Level (95.0%) 1434.01 0.92 5.37 0.32 6.45 7.45 16.82 0.40 4.70 0.38 6.30 10.08 Appendix 29 Statistical summary of Chemical indices for the Boreholes (Sampled years: 2016 and 2017) 2016 2017 Parameters WQI SAR Na% RSC MH% PI% WQI SAR Na% RSC MH% PI% (mg/L) (mg/L) Number of samples 44 44 44 44 44 44 54 54 54 54 54 54 Mean 681.07 1.94 55.57 -0.36 38.10 91.93 12266.82 1.69 53.91 -0.17 56.10 103.40 Standard Error 210.33 0.22 3.11 0.11 3.40 4.48 3956.58 0.15 2.64 0.08 2.98 4.72 Median 36.32 1.58 54.21 -0.33 39.37 91.69 71.54 1.34 55.19 -0.11 57.09 97.69 Mode N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A Standard Deviation 1395.14 1.44 20.60 0.73 22.52 29.73 29074.81 1.10 19.19 0.59 21.73 34.36 Sample Variance 1946426.11 2.07 424.23 0.53 507.20 883.72 845344447.23 1.21 368.19 0.35 472.16 1180.45 Kurtosis 5.65 1.81 -0.83 -0.38 -0.44 -0.65 18.95 0.60 -0.83 0.96 -0.28 2.13 370 University of Ghana http://ugspace.ug.edu.gh Skewness 2.48 1.47 -0.17 0.06 0.26 0.27 4.07 1.13 -0.25 -0.62 -0.46 1.19 Range 5684.42 5.79 75.36 3.24 85.66 118.00 172996.74 4.73 72.94 2.92 89.40 176.06 Minimum -0.01 0.28 15.26 -1.93 4.37 39.92 6.44 0.29 16.21 -1.88 2.75 47.68 Maximum 5684.41 6.07 90.63 1.30 90.03 157.92 173003.17 5.02 89.15 1.05 92.15 223.74 Sum 29966.94 85.18 2445.23 -16.01 1676.49 4045.09 662408.30 89.45 2857.08 -9.09 2973.10 5480.20 Confidence Level 424.16 0.44 6.26 0.22 6.85 9.04 7935.89 0.30 5.29 0.16 5.99 9.47 (95.0%) Appendix 30 Calculated chloro-alkaline indices (Schoeller, 1965) for the boreholes drilled from 2014 to 2015 Sample Location Na+ Cl- K+ Cl- HCO -3 SO 2-4 NO -3 Na +K Na + CA1 - 1 Na + CAI- 2 Id K/Cl K/SO NB1 Newtown 6.79 6.32 0.35 6.32 2.65 0.35 0 7.14 1.13 5.19 20.16 -11.19 NB2 Effasu 0.58 0.56 0.07 0.56 0.62 0.12 0 0.65 1.15 -0.60 5.16 -3.98 NB3 Mangyea 0.60 0.74 0.03 0.74 0.51 0.00 0 0.63 0.85 -0.11 0.00 1.25 NB4 Mpeasem 0.49 0.99 0.04 0.99 1.23 0.02 0 0.53 0.54 0.45 25.45 -23.23 NB5 Alumatuape 0.32 0.28 0.02 0.28 0.33 0.04 0 0.34 1.20 -0.92 8.12 -7.51 NB6 Jawey 0.24 0.24 0.07 0.24 0.82 0.04 0 0.31 1.31 -1.07 7.45 -6.39 NB7 Annor Adjaye 0.52 0.50 0.04 0.50 0.59 0.12 0 0.57 1.14 -0.64 4.53 -3.44 SHS NB8 Allengenzule 0.71 0.71 0.01 0.71 0.25 0.08 0 0.72 1.01 -0.29 8.63 -7.67 NB9 Agyeza 0.99 0.85 0.15 0.85 0.43 0.69 0 1.15 1.35 -0.51 1.67 -0.39 NB10 Ehoaka 0.13 0.16 0.02 0.16 2.65 0.31 0 0.15 0.99 -0.83 0.49 2.32 NB11 Ehoaka 0.13 0.16 0.02 0.16 2.59 0.31 0 0.16 1.02 -0.86 0.51 2.24 NB12 Twenen 0.75 1.02 0.04 1.02 0.31 0.23 0 0.80 0.78 0.23 3.48 -2.15 NB13 Kengen 0.43 0.64 0.01 0.64 0.10 0.02 0 0.44 0.69 -0.05 21.30 -20.56 NB14 Elloyin 0.82 0.88 0.03 0.88 0.08 0.17 0 0.85 0.96 -0.08 5.11 -4.14 NB15 Kangbunli 0.94 0.72 0.07 0.72 2.80 0.19 0 1.01 1.41 -0.69 5.40 -1.87 NB16 Azuleleounu 0.63 0.65 0.05 0.65 0.59 0.17 0 0.68 1.06 -0.41 4.09 -2.86 371 University of Ghana http://ugspace.ug.edu.gh NB17 Asanda 0.85 0.76 0.23 0.76 0.54 0.21 0 1.08 1.41 -0.65 5.19 -3.88 NB18 Asanda 0.33 0.30 0.01 0.30 0.49 0.04 0 0.34 1.13 -0.82 8.17 -7.37 All values are in meq/L and NB =New drilled borehole Appendix 31 Calculated chloro-alkaline indices (Schoeller, 1965) for the hand dug wells sampled in 2016. Sample Community Na+ Cl- K+ HCO - SO 2- NO - Na+ + K+ +3 4 3 Na + CAI-1 Na+ + K+ CAI - 2 number K+/ Cl- / SO 2- 4 HDW1 Esiama 1.43 0.90 0.01 1.00 0.82 0.01 1.44 1.60 -1.43 1.75 0.16 HDW2 Nkroful 5.44 2.20 1.46 0.60 3.11 0.02 6.90 3.14 -2.91 2.22 0.61 HDW3 Kikam 3.12 2.65 0.70 0.80 1.23 0.17 3.83 1.44 -0.26 3.11 0.51 HDW4 Kikam 3.76 2.88 1.06 0.80 1.52 0.03 4.82 1.68 -1.00 3.18 0.53 HDW5 Aniwa 1.02 0.56 0.27 0.20 0.61 0.02 1.28 2.28 -1.26 2.09 -1.30 HDW6 Kikam 1.14 0.85 0.17 0.20 0.98 0.09 1.31 1.54 -1.21 1.33 -0.19 HDW7 Ampain 0.23 0.51 0.02 0.08 0.22 0.01 0.24 0.48 0.26 1.11 -0.52 HDW8 Asanta 1.87 0.62 0.16 1.97 0.45 0.02 2.03 3.26 -1.80 4.53 -1.92 HDW9 Nkroful 0.78 0.45 0.15 0.40 0.46 0.02 0.93 2.07 -0.54 2.05 -1.18 HDW10 Kikam 1.78 1.18 0.19 0.84 0.84 0.02 1.97 1.66 -1.50 2.35 -0.30 HDW11 Bomuakpole 1.33 0.62 0.02 0.08 0.85 0.02 1.35 2.18 -1.84 1.60 -0.88 HDW12 Kikam 1.94 1.47 0.58 0.40 1.34 0.04 2.52 1.72 -0.76 1.88 0.02 HDW13 Ankobra 4.25 4.85 0.20 0.32 0.99 0.03 4.45 0.92 -0.47 4.51 0.69 HDW14 Asanta 0.85 0.79 0.06 0.36 0.77 0.02 0.90 1.14 -0.58 1.17 0.00 HDW15 Gyegyekrom 0.31 0.17 0.01 0.48 0.42 0.02 0.32 1.89 -1.10 0.75 -0.08 HDW16 Kikam 1.38 2.09 0.27 0.16 0.47 0.01 1.65 0.79 0.11 3.51 -1.26 HDW17 Asanta 0.92 1.13 0.04 0.20 1.30 0.02 0.96 0.85 0.67 0.74 0.60 HDW18 Esiama 2.96 1.86 0.55 0.20 1.22 0.04 3.51 1.89 -1.49 2.88 -0.77 HDW19 Aniwa 1.26 0.23 0.20 0.20 1.68 0.00 1.46 6.46 -6.12 0.87 -0.44 HDW20 Esiama 0.85 0.45 0.04 0.12 0.59 0.02 0.89 1.97 -0.95 1.50 -0.91 HDW21 Elubo 3.57 2.37 2.09 0.24 3.07 0.18 5.66 2.39 -1.66 1.85 0.94 372 University of Ghana http://ugspace.ug.edu.gh HDW22 Asanta 2.98 1.64 0.73 1.20 1.22 0.03 3.71 2.27 -2.15 3.03 -0.17 HDW23 Ankobra 2.78 1.75 0.06 0.92 0.88 0.01 2.84 1.62 -0.61 3.22 -0.54 HDW24 Esiama 4.88 3.27 0.88 2.80 1.57 0.16 5.77 1.76 -0.35 3.68 2.55 HDW25 Esiama 0.93 0.62 0.13 1.00 1.11 0.02 1.06 1.71 -1.25 0.95 0.69 HDW26 Nkroful 1.47 0.51 0.25 0.24 3.08 0.01 1.72 3.39 -1.42 0.56 0.20 HDW27 Esiama 2.32 1.64 0.62 0.68 3.08 0.02 2.94 1.80 -1.29 0.95 1.38 HDW28 Gyegyekrom 0.66 0.39 0.01 0.12 0.32 0.01 0.67 1.68 -1.01 2.09 -1.57 HDW29 Elubo 0.99 0.62 0.27 0.76 1.19 0.01 1.27 2.04 -1.42 1.06 0.33 HDW30 Azulenloanu 0.99 0.56 0.06 0.28 0.46 0.01 1.05 1.85 -0.73 2.29 -1.44 HDW31 Half Assin 1.25 0.68 0.22 0.48 1.12 0.01 1.47 2.17 -1.94 1.31 -0.15 HDW32 Bobrama 0.95 0.56 0.02 0.40 0.15 0.02 0.96 1.71 -0.53 6.62 -5.63 HDW33 Asanta 2.09 1.07 0.52 1.00 1.82 0.01 2.61 2.44 -2.04 1.44 0.64 HDW34 Sanwoma 0.98 0.56 0.05 0.82 0.13 0.01 1.03 1.82 -1.14 7.92 -6.53 HDW35 Bobrama 2.78 1.13 0.02 1.47 0.94 0.04 2.80 2.48 -2.20 2.97 -0.33 HDW36 Ankobra (3) 4.20 4.68 0.37 1.04 0.96 0.08 4.56 0.97 -0.81 4.78 1.02 All values are in meq/L and HDW = Hand dug well Appendix 32 Calculated chloro-alkaline indices (Schoeller, 1965) for the Boreholes sampled in 2016. Sample Id Sample Location Ca2+ Mg2+ Na+ K+ Cl- HCO - SO 2-3 4 NO -3 Na+ + Na+ + CA-1 Na+ + K+/SO 2-4 CA-2 K+ K+/Cl- BH 1 Salman 1.53 0.16 1.68 0.08 0.17 3.00 0.76 0.01 1.76 10.42 -10.25 2.32 0.86 BH 2 Kamgbuli 1.44 0.12 0.94 0.04 0.23 0.40 2.53 0.03 0.97 4.30 -4.08 0.38 0.27 BH 3 Kamgbuli 1.08 0.61 0.30 0.01 1.18 0.60 0.53 0.00 0.31 0.26 0.92 0.59 1.20 BH 4 Asemko 0.34 0.30 1.63 0.40 0.68 0.80 0.96 0.02 2.02 2.99 -2.31 2.10 -0.61 BH 5 Ampaim 0.31 0.54 1.22 0.21 1.02 0.44 0.37 0.01 1.43 1.41 -0.39 3.87 -2.41 BH 6 Aniwa 0.08 0.26 1.22 0.02 0.34 0.24 0.63 0.03 1.24 3.67 -3.33 1.97 -1.36 BH 7 Nkroful 0.21 0.17 1.98 0.05 0.73 1.20 0.38 0.02 2.03 2.77 -2.04 5.37 -3.42 BH 8 Sanwoma 0.56 0.04 1.47 0.04 1.47 0.44 0.20 0.03 1.51 1.03 0.44 7.63 -5.70 BH 9 Aluku 0.56 0.20 3.75 0.25 1.52 0.12 3.02 0.01 4.01 2.63 -1.11 1.33 0.32 BH 10 Awiebo 0.21 0.31 0.59 0.04 0.17 1.00 0.09 0.01 0.63 3.72 -3.55 7.09 -5.91 373 University of Ghana http://ugspace.ug.edu.gh BH 11 Esiama 0.47 0.21 0.69 0.05 0.34 0.24 0.94 0.02 0.74 2.18 -1.84 0.79 -0.19 BH 12 Ampain 1.20 0.48 2.81 0.40 0.96 0.28 3.08 0.01 3.21 3.34 -2.39 1.04 0.21 BH 13 Salman 0.28 0.21 0.34 0.01 0.45 0.04 0.46 0.03 0.35 0.77 -0.32 0.76 -0.24 BH 14 Nkroful 1.63 0.33 1.52 0.03 0.56 1.24 0.93 0.03 1.55 2.76 -2.19 1.67 0.16 BH 15 Bobrama 0.11 1.03 1.29 0.04 0.79 0.44 0.88 0.04 1.33 1.68 -0.89 1.51 -0.24 BH 16 Bomuakpole 0.64 0.38 0.81 0.02 0.90 0.20 0.99 0.01 0.82 0.91 -0.01 0.83 0.28 BH 17 Sanwoma 0.41 0.52 0.62 0.03 1.52 0.48 0.00 0.00 0.66 0.43 1.09 139.91 -137.91 BH 18 Alabokazo 0.78 0.55 0.23 0.01 0.39 0.28 1.31 0.01 0.24 0.60 -0.21 0.18 0.50 BH 19 Aluku 0.25 0.10 1.01 0.03 0.34 0.98 0.10 0.00 1.04 3.07 -2.73 10.40 -9.07 BH 20 Alabokazo 0.16 0.53 0.86 0.08 1.02 0.44 0.13 0.02 0.94 0.93 0.09 7.34 -5.86 BH 21 Asanta(6) 0.78 0.25 1.31 0.22 0.73 1.20 0.27 0.03 1.53 2.09 -1.35 5.68 -3.72 BH 23 Salaman 0.18 0.14 0.31 0.01 0.11 0.08 0.52 0.02 0.32 2.84 -2.73 0.62 -0.40 BH 24 Telekobokaso 0.85 0.39 1.27 0.02 1.02 0.04 1.38 0.01 1.29 1.27 -0.26 0.94 0.13 BH 25 Aluku 0.49 0.21 1.79 0.26 1.41 0.12 1.01 0.02 2.05 1.45 -0.04 2.02 -0.47 BH 26 Esiama 0.12 0.13 0.65 0.04 0.45 0.60 0.03 0.01 0.69 1.53 -1.08 20.99 -19.93 BH 27 Ankobra newsite 2.90 0.20 1.49 0.10 1.97 1.52 0.85 0.00 1.58 0.80 1.17 1.87 1.63 BH 28 Sanwoma 1.87 0.10 1.24 0.08 0.51 2.95 0.08 0.02 1.32 2.59 -2.09 17.38 -13.91 BH 29 Old Kablasuazo 0.08 0.08 1.49 0.01 0.68 0.20 0.95 0.01 1.50 2.22 -1.54 1.59 -0.70 BH 30 Azulenloa 0.48 0.09 0.81 0.02 0.62 0.40 0.03 0.01 0.83 1.33 -0.71 26.79 -25.77 BH 31 Azuleno 0.78 1.35 1.29 0.07 1.13 0.20 1.40 0.01 1.36 1.21 -0.08 0.97 0.36 BH 32 Fante new site 0.70 0.79 0.37 0.08 0.23 0.36 0.80 0.02 0.45 1.98 -1.76 0.56 0.05 BH 33 Elubo 0.47 0.45 2.11 0.20 1.18 0.12 1.36 0.01 2.31 1.95 -0.77 1.71 -0.40 BH 34 Bomuakpole 0.79 0.73 1.17 0.02 0.39 1.97 0.12 0.02 1.19 3.02 -2.62 10.23 -7.85 BH 35 NyanZinli 0.68 0.03 1.10 0.44 0.68 0.80 0.21 0.00 1.53 2.26 -1.59 7.35 -5.87 BH 36 Atwibanso 0.09 0.11 0.52 0.01 0.28 0.16 0.24 0.02 0.53 1.86 -1.58 2.19 -1.73 BH 37 New Nzulezu 0.18 0.07 0.16 0.01 0.17 0.08 0.21 0.01 0.17 1.03 -0.86 0.81 -0.56 BH 38 NEW Ankasa 1.24 0.06 0.40 0.02 0.28 0.28 0.82 0.01 0.42 1.51 -1.22 0.52 0.05 BH 39 Bonyere 0.18 0.17 2.49 0.17 1.41 0.84 0.54 0.04 2.66 1.89 -0.48 4.97 -2.68 BH 40 Atwibaso 0.03 0.14 1.25 0.02 0.56 0.20 0.38 0.01 1.27 2.25 -1.69 3.32 -2.55 BH 41 Awiafoto 0.94 0.67 0.35 0.09 0.56 0.68 0.43 0.04 0.44 0.77 -0.21 1.01 0.28 BH 42 Aniwafuto(chips) 0.15 0.17 0.70 0.14 0.17 0.60 0.58 0.03 0.84 4.95 -4.79 1.44 -0.65 BH 43 New Nzulezu 1.11 0.54 0.63 0.06 2.37 0.08 0.34 0.07 0.69 0.29 2.08 2.00 0.53 BH 44 Tiekobo 1 0.31 0.01 0.80 0.09 0.11 0.28 0.50 0.01 0.90 7.97 -7.86 1.81 -1.41 BH 45 Bobrama 0.93 0.23 1.05 0.01 1.13 0.12 0.60 0.01 1.06 0.94 0.19 1.75 -0.50 All values are in meq/L and BH = Boreholes 374 University of Ghana http://ugspace.ug.edu.gh Appendix 33 Calculated chloro-alkaline indices (Schoeller, 1965) for the hand dug wells sampled in 2017. Sample Community Ca2+ Mg2+ Na+ K+ Cl - HCO - SO 2- NO - Na++K+ Na+ + CAI- Na+ + K +/SO 2-3 4 3 4 CAI-2 Id K+/Cl- 1 HDW1 Nkroful (5) 0.31 0.11 0.80 0.03 0.68 0.24 0.14 0.01 0.82 1.22 -0.54 8.93 -8.00 HDW2 Aluku 3 0.53 0.49 1.96 0.19 1.64 0.28 0.61 0.01 2.15 1.32 0.32 2.15 -0.23 HDW3 Kikam 1 1.30 0.49 1.61 0.19 0.56 3.00 0.04 0.01 1.80 3.20 -2.64 85.21 -81.64 HDW4 Nkroful (2) 0.24 0.06 0.53 0.02 0.51 0.20 0.00 0.01 0.55 1.08 -0.57 0.00 0.72 HDW5 Esiama 8 3.60 1.05 1.76 0.53 3.38 2.08 0.42 0.00 2.30 0.68 2.70 1.63 3.84 HDW6 Elubo (5) 0.46 0.57 3.69 0.68 3.78 0.20 0.17 0.05 4.37 1.16 2.62 6.81 -2.78 HDW7 Kikam 2 1.06 0.48 1.61 0.47 1.30 1.80 0.00 0.01 2.08 1.60 -0.31 0.00 3.11 HDW8 Half Assin 0.79 0.13 0.47 0.09 0.73 0.30 0.17 0.01 0.56 0.77 -0.03 4.57 -3.54 HDW9 Bomuakpole(1) 1.12 0.38 1.16 0.18 1.52 1.20 0.28 0.02 1.33 0.88 0.65 3.17 -0.43 HDW10 Nkroful(3) 0.56 0.33 1.15 0.15 0.45 1.00 0.17 0.03 1.30 2.89 -2.44 16.61 -15.12 HDW11 Kikam (3) 2.30 0.58 3.14 0.82 2.14 4.80 0.96 0.02 3.96 1.85 0.30 1.92 5.04 HDW12 Kikam (7) 0.66 0.36 1.03 0.30 2.26 0.28 0.04 0.02 1.32 0.59 1.67 16.25 -13.69 HDW13 Elubo(5) 1.76 0.05 3.18 0.21 3.78 0.04 0.17 0.05 3.39 0.90 2.88 5.28 -1.41 HDW14 Nkroful(1) 2.47 1.24 4.79 1.02 1.58 3.80 1.61 0.02 5.81 3.68 -2.10 2.28 3.11 HDW15 Aniwa(2) 1.12 0.38 1.16 0.18 0.73 2.00 0.75 0.01 1.33 1.82 -1.09 2.42 0.32 HDW16 Asemda 0.24 1.07 0.80 0.13 0.11 1.47 0.97 0.02 0.92 8.17 -8.06 8.43 -6.82 HDW17 Gyegyekrom(2) 0.52 0.12 0.37 0.02 0.17 0.32 0.39 0.02 0.39 2.29 -2.12 5.80 -5.29 HDW18 esiama 4 3.25 0.83 1.48 0.21 0.90 5.79 0.28 0.01 1.69 1.87 -0.97 6.68 0.02 HDW19 Ampaim (4) 0.18 0.10 0.36 0.04 0.56 0.24 0.00 0.01 0.40 0.71 -0.15 0.00 0.81 HDW20 Eikwe 1.22 0.66 3.78 0.28 1.52 2.89 1.43 0.04 4.06 2.67 -1.15 1.87 2.58 HDW21 Atuabo 1.05 0.79 2.12 0.12 0.11 2.00 1.01 0.02 2.24 19.84 - 19.64 -17.51 19.73 HDW22 Benyin 2.98 1.16 3.50 0.28 2.99 1.96 1.03 0.00 3.78 1.26 1.73 1.22 3.73 HDW23 Esiama 7 2.47 0.78 4.47 0.87 0.73 4.00 1.93 0.02 5.34 7.29 -6.55 3.78 0.97 HDW24 Gyegyekrom(1) 0.07 0.13 0.26 0.02 0.11 0.40 0.01 0.00 0.28 2.46 -2.34 239.92 - 239.40 HDW25 bobrama(2) 0.41 0.56 1.58 0.51 1.30 0.80 0.27 0.01 2.08 1.61 -0.31 5.96 -3.85 HDW26 Elubo(1) 2.06 0.24 0.83 0.36 0.68 1.00 0.98 0.06 1.19 1.75 -1.08 1.79 -0.06 HDW27 Kikam 0.85 0.51 1.25 0.18 0.79 0.60 2.04 0.02 1.43 1.81 -1.02 0.89 0.52 HDW28 Kikam (5) 0.48 0.37 1.77 0.21 1.41 1.60 0.58 0.01 1.97 1.40 0.01 2.41 0.61 HDW29 Azuleno(1) 0.35 0.39 1.07 0.08 0.56 0.98 0.00 0.01 1.15 2.03 -1.47 0.00 1.56 HDW30 Aniwa(1) 0.39 0.27 1.03 0.23 0.39 1.00 0.76 0.01 1.25 3.18 -2.78 4.17 -2.77 All values are in meq/L and HDW = hand dug well 375 University of Ghana http://ugspace.ug.edu.gh Appendix 34 Calculated chloro-alkaline indices (Schoeller, 1965) for the Boreholes sampled in 2017. Sample Location Ca2+ Mg2+ Na+ K+ Cl- HCO - SO 2- NO - Na+ Na+ + K+ CAI - Na+3 4 3 + K+ / CAI-2 Id + K+ /Cl- 1 SO 2-4 BH1 Sanzule 0.08 0.08 0.82 0.06 0.23 0.16 0.83 0.01 0.87 3.87 -3.65 4.66 -4.27 BH2 Nyaniba 0.42 0.36 2.01 0.04 1.07 0.32 1.36 0.005 2.05 1.91 -0.84 1.41 -0.01 BH3 Ampaim 0.15 0.65 0.92 0.07 0.85 0.52 0.14 0.00 0.99 1.17 -0.33 8.60 -7.23 BH4 Atwinbanso 0.06 0.17 0.64 0.04 0.56 0.40 0.00 0.004 0.68 1.20 -0.63 0.00 0.97 BH5 Elubo 0.32 0.59 1.96 0.19 1.58 0.80 0.000 0.02 2.15 1.36 0.22 0.00 2.40 BH6 Awiefoto 0.14 0.14 0.42 0.13 0.17 0.80 0.00 0.03 0.55 3.23 -3.06 0.00 0.99 BH7 Esiama 1.59 0.78 3.73 0.94 2.54 1.40 2.96 0.03 4.66 1.84 0.70 0.62 3.35 BH8 Old Kablazuaso 0.05 0.14 0.48 0.01 0.56 0.24 0.01 0.01 0.49 0.87 -0.31 127.95 -127.14 BH9 Fante New Town 0.57 0.16 0.85 0.15 0.23 0.96 0.34 0.02 1.01 4.46 -4.23 13.25 -12.05 BH10 Half Assin SHS 0.16 0.04 1.60 0.07 0.90 0.20 0.56 0.00 1.66 1.84 -0.94 3.27 -2.17 BH11 Salman 0.15 0.22 0.33 0.00 0.17 0.66 0.00 0.00 0.33 1.97 -1.80 0.00 0.82 BH12 Salman 0.68 0.77 0.73 0.01 0.17 1.80 0.04 0.00 0.74 4.38 -4.21 106.85 -104.88 BH13 Esiama 1.35 0.40 2.39 0.07 1.30 2.80 0.26 0.02 2.46 1.90 -0.60 7.22 -3.11 BH14 Azuleno 1.00 1.90 1.50 0.08 0.39 1.40 3.45 0.01 1.59 4.02 -3.63 1.17 0.64 BH15 Bomuakpolley 0.11 0.41 0.58 0.02 0.34 1.15 0.00 0.00 0.60 1.77 -1.43 0.00 1.49 BH16 Salman 0.24 0.28 0.35 0.01 0.11 0.44 0.21 0.02 0.36 3.19 -3.08 15.09 -14.52 BH17 Nkroful 0.18 0.22 0.63 0.03 0.56 0.44 0.00 0.01 0.66 1.17 -0.61 0.00 1.01 BH18 Esiama 0.10 0.92 0.60 0.05 0.45 0.44 0.31 0.05 0.65 1.45 -1.00 4.65 -3.71 BH19 Ankobra newsite 0.32 0.78 0.78 0.03 0.34 1.00 0.14 0.01 0.81 2.39 -2.05 16.68 -15.33 BH20 Ampin 0.27 0.33 0.52 0.04 0.11 1.20 0.00 0.01 0.56 4.99 -4.87 0.00 1.32 BH21 Nkroful 0.92 0.39 1.22 0.03 0.68 0.72 0.53 0.03 1.25 1.85 -1.17 3.50 -2.08 BH22 New Nzulazu 0.06 0.08 0.28 0.02 0.17 0.16 0.00 0.01 0.30 1.78 -1.61 0.00 0.34 BH23 Tiekobo 0.04 0.05 0.16 0.02 0.11 0.16 0.05 0.00 0.18 1.59 -1.48 31.02 -30.75 BH24 Bobrama 0.12 1.42 1.34 0.03 1.18 1.20 0.10 0.01 1.37 1.16 0.02 11.72 -9.33 BH25 New Nzulazu 0.88 0.68 0.70 0.07 0.06 2.20 0.15 0.01 0.77 13.69 -13.63 89.35 -87.09 BH26 Bonyere 0.18 0.25 1.15 0.16 0.51 1.00 0.10 0.00 1.31 2.58 -2.07 25.20 -23.69 BH27 Kamgbunli 1.91 2.97 1.13 0.05 0.90 3.00 0.88 0.00 1.18 1.31 -0.40 1.48 2.43 BH28 Aluku 0.32 0.29 1.97 0.28 1.64 0.16 0.74 0.02 2.25 1.38 0.26 1.87 -0.06 BH29 Atwinbanso 0.04 0.18 0.75 0.05 0.62 0.04 0.22 0.01 0.80 1.28 -0.66 5.87 -5.20 BH30 Asemko 0.20 0.44 0.72 0.02 0.23 0.98 0.00 0.01 0.74 3.28 -3.06 0.00 1.21 BH31 Salman 2.40 1.32 0.74 0.02 0.11 3.60 0.38 0.01 0.76 6.75 -6.64 17.86 -14.14 BH32 Azeneluno 1.00 1.98 1.50 0.08 0.39 1.40 3.45 0.01 1.59 4.02 -3.63 1.17 0.64 BH33 Aluku 0.28 0.15 0.52 0.01 0.34 0.20 0.16 0.02 0.53 1.58 -1.24 9.76 -9.20 376 University of Ghana http://ugspace.ug.edu.gh BH34 Alabokazo 0.69 0.55 0.23 0.01 0.96 0.80 0.07 0.01 0.24 0.25 0.71 3.48 -1.72 BH35 Kamgbunli 0.48 0.70 0.36 0.02 0.34 0.56 0.39 0.01 0.38 1.13 -0.79 2.93 -2.03 BH36 Ankasa 0.32 0.37 0.51 0.03 0.96 0.40 0.17 0.02 0.54 0.56 0.40 3.23 -1.85 BH37 Telekobokaso 0.84 0.56 1.42 0.03 0.56 2.00 0.63 0.00 1.45 2.57 -2.01 4.08 -1.51 BH38 Alabokazo 0.19 0.70 0.96 0.09 0.62 1.80 0.00 0.02 1.05 1.69 -1.07 0.00 2.44 BH39 Awiafotu junction 0.40 0.93 0.44 0.02 0.51 0.56 0.26 0.00 0.46 0.90 -0.39 3.42 -2.35 BH40 Azulenenuo 0.75 0.88 1.00 0.04 0.62 1.80 0.05 0.02 1.04 1.68 -1.06 30.79 -28.35 BH41 Salman 0.32 0.54 1.49 0.04 0.85 0.98 0.00 0.07 1.53 1.81 -0.96 86861.05 -86859.16 BH42 Sanzule 0.14 0.54 2.14 0.06 0.85 0.44 0.97 0.01 2.21 2.61 -1.76 2.69 -1.39 BH43 Ngelekazo(kerrela 1.01 0.19 0.64 0.02 0.11 0.32 1.12 0.02 0.66 5.87 -5.76 5.26 -4.81 hotel) BH44 Eikwe 0.27 1.78 0.56 0.11 0.23 1.08 1.43 0.02 0.67 2.97 -2.74 2.08 -0.75 BH45 Ngelekazo 0.53 0.07 0.66 0.08 0.34 0.32 0.62 0.00 0.74 2.20 -1.86 3.52 -2.86 BH46 sanzule 0.68 1.53 0.57 0.07 0.34 1.24 1.09 0.03 0.64 1.90 -1.56 1.74 -0.13 BH47 Krisan 0.12 0.30 1.97 0.17 0.68 0.40 1.56 0.00 2.14 3.16 -2.48 2.03 -0.95 BH48 Ngelekpolley 0.53 0.19 1.04 0.19 0.45 0.44 1.40 0.02 1.23 2.72 -2.27 1.94 -1.03 BH49 Baku 0.14 1.18 1.36 0.08 0.56 0.92 1.48 0.00 1.43 2.54 -1.98 1.71 -0.23 BH50 Keegan 0.41 0.76 2.46 0.25 0.34 1.20 1.46 0.03 2.71 8.02 -7.68 5.48 -3.92 BH51 Asemda 0.36 0.43 2.18 0.17 0.79 0.60 1.62 0.02 2.35 2.98 -2.19 1.84 -0.43 BH52 Twenen 0.05 0.43 1.50 0.03 0.62 0.40 1.47 0.02 1.54 2.48 -1.86 1.69 -0.65 BH53 Ngelekyi 0.58 0.02 0.74 0.08 0.34 0.04 1.40 0.00 0.81 2.41 -2.07 1.72 -1.33 All values are in meq/L and BH = Boreholes Appendix 35: Saturation indices computed for the sampled groundwater in the aquifer of the Apollonian formation and the aBirimian supergroup using using Phreeqc for Windows. Sample Albite Aragonite Ca- Calcite Chalcedony Dolomite Gibbsite Gypsum Halite K- K- Kaolinite Quartz SiO Sy = number Montmorillonite feldspar Mica syg- Sy k 1 -10.8 -3.1 -8.5 -3.0 -2.3 -5.5 0.2 -4.4 -7.4 -8.8 -2.8 -2.5 -1.8 -3.1 2.7 2 -6.4 -4.0 -2.4 -3.9 -0.5 -7.8 0.1 -3.5 -8.4 -5.4 0.5 0.9 -0.1 -1.4 -0.8 3 -6.3 -0.7 -2.8 -0.6 -1.6 -1.8 1.3 -2.5 -7.9 -4.9 4.0 1.1 -1.1 -2.4 0.2 4 -7.7 -2.4 -3.1 -2.2 -1.7 -4.1 1.5 -3.0 -8.8 -6.4 2.2 1.3 -1.2 -2.5 0.2 377 University of Ghana http://ugspace.ug.edu.gh 5 -4.0 -2.3 0.0 -2.2 -0.5 -4.5 0.9 -2.5 -7.4 -2.0 5.3 2.5 -0.1 -1.3 -1.6 6 0.0 -2.3 -2.2 -4.3 0.1 -2.6 -7.7 0.1 7 -6.3 -3.2 -2.4 -3.0 -0.6 -6.0 0.3 -4.4 -8.1 -4.4 1.8 0.9 -0.2 -1.5 -0.7 8 0.0 -1.8 -1.7 -2.3 -3.4 -2.2 -6.7 -1.9 -3.1 0.0 9 0.0 -3.1 -2.9 0.7 -8.4 0.7 10 -4.0 -3.3 1.5 -3.1 0.0 -6.7 0.9 -2.9 -8.9 -2.7 4.8 3.5 0.4 -0.8 -2.6 11 0.0 -1.0 -0.9 -2.4 0.4 -4.2 -8.1 0.4 12 -0.5 -2.6 6.2 -2.4 0.3 -5.7 2.4 -2.1 -7.4 0.1 10.4 7.1 0.8 -0.5 -4.7 13 -4.4 -3.3 0.5 -3.1 -0.2 -6.0 0.8 -3.5 -7.9 -3.2 4.1 2.9 0.2 -1.1 -2.0 14 0.0 -3.6 -3.5 -7.0 0.8 -4.2 -9.0 0.8 15 -8.7 -0.7 -4.6 -0.5 -2.3 -1.1 1.6 -2.5 -8.7 -7.7 1.2 0.4 -1.8 -3.1 1.2 16 -11.0 -5.3 -7.9 -5.2 -1.7 -9.8 -0.3 -5.7 -8.2 -10.3 -5.2 -2.3 -1.3 -2.5 2.0 17 -7.8 -3.3 -1.8 -3.1 -2.3 -5.1 3.0 -3.7 -8.2 -6.3 5.4 3.2 -1.9 -3.1 -0.1 18 0.0 -5.8 -5.6 -10.6 -1.2 -8.1 -1.2 19 -11.2 -4.8 -6.4 -4.7 -2.2 -8.9 1.2 -5.3 -9.1 -9.8 -1.8 -0.4 -1.8 -3.1 1.6 20 -8.2 -4.6 -3.7 -4.5 -0.9 -8.8 0.3 -8.0 -6.8 -0.6 0.5 -0.5 -1.7 -0.2 21 -2.1 0.0 2.9 0.1 -0.3 -0.2 1.8 -3.6 -7.5 -0.4 8.8 4.6 0.1 -1.2 -2.8 22 0.0 -2.3 -2.2 -4.3 0.1 -2.6 -7.7 0.1 23 -9.1 -4.4 -6.1 -4.2 -1.1 -8.9 -0.6 -8.2 -8.0 -3.6 -1.7 -0.6 -1.9 1.1 24 0.0 -1.2 -1.1 -2.2 0.9 -2.4 -6.8 0.9 25 0.0 -4.6 -4.4 -8.5 -0.1 -7.1 -0.1 26 -9.8 -3.9 -7.9 -3.8 -1.5 -7.5 -0.7 -2.8 -7.1 -8.3 -4.1 -2.7 -1.1 -2.3 2.0 27 -5.4 -4.1 0.0 -3.9 -0.3 -7.1 0.9 -7.9 -3.9 3.5 2.9 0.1 -1.1 -2.0 28 0.0 -3.7 -3.6 -7.0 0.5 -7.3 0.5 29 -3.8 -2.7 0.1 -2.6 0.3 -4.7 -0.2 -3.2 .8.28 -2.5 2.8 1.8 0.7 -0.6 -2.0 30 -4.1 -1.0 -0.7 -0.9 -0.5 -2.4 0.4 -4.2 -8.1 -2.3 4.2 1.6 0.0 -1.3 -1.2 31 0.0 -3.7 -3.5 -0.3 -6.3 -8.3 0.1 -1.1 0.0 32 -12.1 -5.7 -9.0 -5.6 -1.8 -10.9 -0.6 -8.9 -10.7 -6.2 -3.0 -1.4 -2.6 2.5 33 -6.5 -5.0 -2.2 -4.8 -0.3 -11.0 0.1 -2.9 -6.6 -5.2 0.6 1.1 0.1 -1.2 -1.1 378 University of Ghana http://ugspace.ug.edu.gh 34 -4.1 -2.8 0.6 -2.7 -0.2 -5.6 0.8 -2.4 -7.7 -2.4 4.9 2.9 0.2 -1.1 -2.1 35 -6.9 -3.9 -4.2 -3.8 -0.5 -7.5 -0.7 -2.8 -7.1 -5.3 -1.1 -0.7 -0.1 -1.3 0.0 36 0.0 -2.7 -2.5 -1.0 -4.7 -3.0 -8.5 -0.6 -1.8 0.0 37 -9.4 -3.7 -6.3 -3.6 -1.8 -7.0 0.4 -7.3 -7.7 -1.3 -1.1 -1.4 -2.6 1.5 38 -13.4 -6.5 -12.5 -6.4 -1.7 -11.9 -2.2 -4.2 -7.9 -12.1 -10.8 -6.0 -1.3 -2.5 3.9 39 -2.9 -3.3 2.4 -3.1 0.3 -6.0 0.8 -3.5 -7.9 -1.6 5.7 3.9 0.7 -0.5 -3.1 40 -11.4 -3.8 -8.7 -3.6 -1.9 -6.7 -0.3 -8.9 -10.7 -5.7 -2.8 -1.5 -2.8 2.5 41 -1.4 0.0 2.1 0.2 -0.4 0.4 1.4 -2.7 -6.0 -0.1 8.3 3.8 0.1 -1.2 -2.4 42 -2.8 -2.1 4.6 -2.0 -0.7 -4.9 3.2 -3.3 -8.1 -1.2 10.8 6.7 -0.3 -1.5 -3.5 43 -4.0 -3.0 3.1 -2.9 -0.7 -6.1 2.7 -8.0 -2.8 8.1 5.7 -0.3 -1.5 -3.0 44 -2.9 -1.1 3.3 -1.0 -0.5 -2.7 2.2 -3.7 -7.9 -1.4 8.6 5.2 0.0 -1.3 -3.0 45 -3.2 -3.0 4.3 -2.9 -0.6 -6.0 3.0 -4.0 -8.7 -1.8 9.7 6.4 -0.2 -1.4 -3.5 46 -3.9 -1.9 3.2 -1.7 -0.8 -4.1 2.8 -3.7 -8.9 -1.9 9.3 5.6 -0.4 -1.7 -2.8 47 -4.4 -2.9 2.3 -2.7 -0.8 -5.8 2.4 -3.3 -8.2 -2.9 7.5 5.0 -0.3 -1.6 -2.6 48 -5.1 -3.9 0.8 -3.7 -0.7 -7.5 1.8 -3.8 -7.9 -4.6 4.5 3.8 -0.3 -1.6 -2.0 49 -3.3 -2.5 3.6 -2.4 -0.6 -5.1 2.7 -2.4 -7.7 -1.5 9.5 5.9 -0.2 -1.5 -3.2 50 -4.7 -0.5 1.5 -0.3 -0.8 -1.2 2.0 -2.4 -9.3 -2.9 6.7 4.0 -0.4 -1.7 -2.0 51 -4.7 -0.5 1.5 -0.3 -0.8 -1.7 2.0 -2.4 -9.3 -2.9 6.7 4.0 -0.4 -1.7 -2.0 52 -2.9 -4.0 5.3 -3.8 -0.4 -7.6 3.3 -3.4 -7.7 -1.5 10.7 7.4 0.0 -1.3 -4.1 53 -5.5 -4.7 1.2 -4.5 -0.7 -9.2 2.0 -4.5 -8.2 -4.4 5.2 4.3 -0.3 -1.5 -2.3 54 -6.4 -4.8 -0.7 -4.7 -1.0 -9.2 1.7 -3.8 -7.8 -5.2 3.7 3.0 -0.6 -1.9 -1.3 55 -0.9 -0.8 5.5 -0.7 0.1 -1.4 2.3 -2.8 -7.8 0.5 10.6 6.5 0.6 -0.7 -4.2 56 -3.3 -2.9 3.2 -2.8 -0.3 -5.6 2.1 -3.1 -8.0 -1.8 8.1 5.3 0.1 -1.2 -3.2 57 -3.5 -2.1 2.4 -2.0 -0.7 -4.3 2.3 -3.1 -7.8 -1.5 8.7 4.8 -0.3 -1.6 -2.5 58 -3.6 -2.7 3.8 -2.6 -0.6 -5.7 2.7 -3.8 -8.6 -2.8 8.2 6.0 -0.1 -1.4 -3.3 379 University of Ghana http://ugspace.ug.edu.gh Appendix 36: Publication And Conferences 1. Edjah, A. & Banoeng-Yakubo, Bruce & Akiti, T. & Stenni, Barbara & Dreossi, Giuliano & Doku-Amponsah, Kwabena. (2019). Characterization of water chemistry in some communities of the Lower Tano river basin, Ghana, West Africa. Arabian Journal of Geosciences. 12. 10.1007/s12517-019-4305-4. 2. Characterization of Surface Water and Groundwater Quality in the Lower Tano River Basin Using Statistical and Isotopic Approach. AAEdjah, Adwoba & ABStenni, Barbara & ACCozzi, Giulio & ADTuretta, Clara & AEDreossi, Giuliano & AFTetteh Akiti, Thomas & AGYidana, Sandow. AA (Department of Earth Science, University of Ghana Legon, Ghana West- Africa), AB(Department of Enviromental Sciences, Informatics and Statistics, Ca Foscari University of Venice, Italy), AC(Department of Enviromental Sciences, Informatics and Statistics, Ca Foscari University of Venic e, Italy), AD(Department of Enviromental Sciences, Informatics and Statistics, Ca Foscari University of Venice Italy), AE(Institute for the Dynamics of Environmental Processes, CNR, Venice, Italy), AF(Department of Nuclear Application and Techniques, Graduate School of Nuclear and Allied Sciences University of Ghana Legon), AG (Department of Earth Science, University of Ghana Legon, West - Africa). EGU General Assembly Conference Abstract, 2017/04/1, 447 https://ui.adsabs.harvard.edu/abs/2017EGUGA..19..447E. 380 University of Ghana http://ugspace.ug.edu.gh Appendix 37: Contribution to knowledge This study being the first detailed groundwater research in the Lower Tano River Basin has: 1. Contributed to the current hydrogeological knowledge on the Lower Tano River basin. This knowledge will contribute to a successful future groundwater study. 2. Successfully determined isotopic rainfall regression lines with equations δ2 H = 7.69 δ18 O + 11.68 for the dry period and δ2 H = 8δ18O + 11.31 for the wet period. These two lines together with the local meteoric water line (Akiti,1986) could be used as reference lines for future research on aquifer recharge in the basin. 3. Provided a base line information on ages of the groundwater and recharge sources which will support groundwater management. 381