Regional Environmental Change (2018) 18:1829–1842
https://doi.org/10.1007/s10113-018-1311-0
ORIGINAL ARTICLE
What are the implications of sea-level rise for a 1.5, 2 and 3 °C rise
in global mean temperatures in the Ganges-Brahmaputra-Meghna
and other vulnerable deltas?
Sally Brown1 & Robert J. Nicholls1 & Attila N. Lázár1 & Duncan D. Hornby2 & Chris Hill2 & Sugata Hazra3 &
Kwasi Appeaning Addo4 & Anisul Haque5 & John Caesar6 & Emma L. Tompkins7
Received: 27 October 2017 /Accepted: 18 February 2018 /Published online: 16 March 2018
# The Author(s) 2018
Abstract
Even if climate change mitigation is successful, sea levels will keep rising. With subsidence, relative sea-level rise
represents a long-term threat to low-lying deltas. A large part of coastal Bangladesh was analysed using the Delta
Dynamic Integrated Emulator Model to determine changes in flood depth, area and population affected given sea-level
rise equivalent to global mean temperature rises of 1.5, 2.0 and 3.0 °C with respect to pre-industrial for three ensemble
members of a modified A1B scenario. Annual climate variability today (with approximately 1.0 °C of warming) is
potentially more important, in terms of coastal impacts, than an additional 0.5 °C warming. In coastal Bangladesh, the
average depth of flooding in protected areas is projected to double to between 0.07 and 0.09 m when temperatures are
projected at 3.0 °C compared with 1.5 °C. In unprotected areas, the depth of flooding is projected to increase by
approximately 50% to 0.21–0.27 m, whilst the average area inundated increases 2.5 times (from 5 to 13% of the
region) in the same temperature frame. The greatest area of land flooded is projected in the central and north-east
regions. In contrast, lower flood depths, less land area flooded and fewer people are projected in the poldered west of
the region. Over multi-centennial timescales, climate change mitigation and controlled sedimentation to maintain
relative delta height are key to a delta’s survival. With slow rates of sea-level rise, adaptation remains possible, but
Editor:Wolfgang Cramer.
Electronic supplementary material The online version of this article
(https://doi.org/10.1007/s10113-018-1311-0) contains supplementary
material, which is available to authorized users.
* Sally Brown John Caesar
sb20@soton.ac.uk john.caesar@metoffice.gov.uk
Robert J. Nicholls Emma L. Tompkins
R.J.Nicholls@soton.ac.uk E.L.Tompkins@soton.ac.uk
1
Duncan D. Hornby Faculty of Engineering and the Environment, University of
ddh@geodata.soton.ac.uk Southampton, Highfield, Southampton SO17 1BJ, UK
2 GeoData, University of Southampton, Southampton SO17 1BJ, UK
Chris Hill 3 School of Oceanographic Studies, Jadavpur University,
cth@geodata.soton.ac.uk
Kolkata, India
4
Sugata Hazra Department of Marine and Fisheries Sciences, University of Ghana,
sugata_hazra@yahoo.com P. O. Box Lg 99, Legon-Accra, Ghana
5 Institute of Water and Flood Management, Bangladesh University of
Kwasi Appeaning Addo Engineering and Technology, Dhaka, Bangladesh
kappeaningaddo@ug.edu.gh 6 Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3PB, UK
Anisul Haque 7 Geography and Environment, University of Southampton, Highfield,
anisul.buet@gmail.com Southampton SO17 1BJ, UK
1830 S. Brown et al.
further support is required. Monitoring of sea-level rise and subsidence in deltas is recommended, together with
improved datasets of elevation.
Keywords Sea-level rise . Flooding, delta . Ganges-Brahmaputra-Meghna . Volta .Mahanadi
Abbreviations analysed for a 18,600-km2 sub-region of the delta containing
ΔDIEM Delta Dynamic Integrated Emulator Model 14 million people (Fig. 1). Largely rural, the study area is
BAU Business-as-usual located less than 3 m above mean sea level. The dominant
GBM Ganges-Brahmaputra-Meghna land use is agriculture, and there is a high reliance onmonsoon
GCM Global climate model rainfall conditions to sustain livelihoods. There is strong tidal
LS Less sustainable influence in the delta (Kausher et al. 1996).
MS More sustainable In 1975, the building of the Farakka barrage resulted in an
RCM Regional climate model annual decrease in sediment load of 31% (Gupta et al. 2012)
RCP Representative Concentration Pathway and in south-west Bangladesh resulted in decreased river dis-
SLR Sea-level rise charge and increased salinity (Mizra 1998). Separately, from
SRES Special Report on Emissions Scenarios 1989 to 2009, there was erosion along the seaward side of the
Sundarbans in western Bangladesh (Sarwar and Woodroffe
2013), with erosion and accretion elsewhere along the coast-
Introduction line (Brammer 2014; Sarwar and Woodroffe 2013; Shearman
et al. 2013).
The Paris Agreement (United Nations 2015) aims for tempera- Polders (i.e. low-lying lands surrounded by embankments)
ture stabilisation to ‘well below 2 °C above pre-industrial levels’ are used for agriculture improvement and water management.
and pursue ‘efforts to limit the temperature increase to 1.5 °C’. One hundred twenty-six were built between 1960 and 1990 to
Climate change mitigation has many benefits; yet for the impacts protect farmers from tidal and saline water inundation and to
of sea-level rise (SLR), this takes time to manifest as there re- regulate water levels (World Bank 2005). However, they re-
mains a long-term commitment to SLRdue to historical warming stricted sediment deposition causing significant land subsidence
(Goodwin et al. 2018; Nicholls et al. 2018; Nicholls and Lowe of up to 20 mm/year within polders (Auerbach et al. 2015),
2004). Global mean rises of 0.75 to 0.80 m (with a probability of whereas 2.6 mm/year subsidence is recorded regionally
greater than 50%) are projected by 2100 (for a 1.5 and 2.0 °C (Brown and Nicholls 2015). Relative SLR (eustatic SLR plus
scenario) with respect to 2000 (Schaeffer et al. 2012). subsidence) is recorded as 9mm/year (Charchanga to the south-
Presently, there is limited understanding of the impacts of east of the study region, from 1979 to 2000) (Holgate et al.
SLR at 1.5 and 2.0 °C in vulnerable low-lying deltas (e.g. 2013; Permanent Service for Mean Sea Level 2017), but is
Zaman et al. 2017), whose problems are compounded by sed- variable due to natural cycles, plus throughout the region due
iment starvation and subsidence, leading to salinisation, to subsidence and polders where the latter has a long-term affect
flooding and erosion. Deltas are subject to multiple drivers on river discharge and tidal flow (Pethick and Orford 2013).
of change, as society responses to this planned and unplanned Thus, relative SLR poses a major threat in coastal Bangladesh.
ways. Thus, this paper analyses the implications of tempera-
ture and equivalent SLR at 1.5, 2.0 and 3.0 °C in the world’s
largest delta which is highly populated, the Ganges- Determining impacts of sea-level rise
Brahmaputra-Meghna (GBM), plus the wider implications
for other deltas. This will be achieved by (i) reviewing the Scenarios were generated based on climate change and socio-
setting of the GBM; (ii) describing the modelling methodolo- economic development conditions and modelled numerically
gy used; (iii) analysing impacts at 1.5, 2.0 and 3.0 °C; and (iv) using the Delta Dynamic Integrated Emulator Model (ΔDIEM)
discussing the caveats and consequences of these findings in (Lázár et al. 2018). These are described in the following section,
the context of other deltas, plus the potential for adaptation. with further details in the Supplementary Material.
Scenarios
Setting
Climate change scenarios
The GBM delta is a large delta occupying more than
100,000 km2, depending on definition, and contains the Climate change scenarios for global temperature rises 1.5, 2.0
Sundarbans mangrove forest. The impacts of SLR have been and 3.0 °C were generated from a modified version of the
What are the implications of sea-level rise for a 1.5, 2 and 3 °C rise in global mean temperatures in the... 1831
Fig. 1 Region of detailed study in the Ganges-Brahmaputra, Bangladesh
Special Report on Emissions Scenarios (SRES) A1B scenario historical forcing factors, there were inconsistencies in
(Caesar et al. 2015). A1B is a medium to high emissions defining temperature change today. For instance, Q16 in-
scenario (Nakicenovic and Swart 2000) lying between dicates that 1.5 °C was reached in 2011, which is incon-
Representative Concentration Pathways (RCP) 6.0 and 8.5 sistent with observations. Additionally, there is a common
(Moss et al. 2010). An output from an ensemble of the global issue across climate science regarding defining the pre-
climate model (GCM) HadCM3 (Collins et al. 2006) was used industrial baseline (Hawkins et al. 2017). Importantly, if
to drive regional climate model (RCM) simulations at a 25-km temperatures rise to 1.5 °C quickly (e.g. Q16), sea-level
spatial resolution over South Asia using HadRM3P (Massey rise will be less when 1.5 °C first occurs compared with a
et al. 2015). Three ensemble members (out of 17) were select- temperature rise which happens over a longer time period
ed for detailed analysis: (i) Q0 (a moderate increase in tem- (e.g. Q8). Apart from historic forcing factors, this is also
perature and precipitation), (ii) Q8 (a warmer but drier future due to the commitment to sea-level rise (for long-term
around mid-century, then wetter) and (iii) Q16 (a larger in- implications of this, see discussion on ‘Commitment to
crease in temperature). These members represented a wide sea-level rise’). Apart from SLR, high water levels took
range of possible futures as explained by Caesar et al. (2015). account of surges, tides, bathymetry and local river flows
Each temperature scenario was referenced by a decadal (Kay et al. 2015) and included an additional 2.5 mm/year
average time period (with respect to pre-industrial, i.e. of subsidence (Brown and Nicholls 2015).
1850–1900). A single SLR scenario (of 0.24 m by 2050
and 0.54 m by 2100 with respect to 1986–2005) was Socio-economic development scenarios
applied to each ensemble member (Kay et al. 2015).
This represented a median scenario, and it is recognised Socio-economic conditions were adapted from the five
there is considerable uncertainty around these scenarios Shared Socioeconomic Pathways (Moss et al. 2010;
(as described by Kay et al. (2015)), particularly as time O’Neill et al. 2014) to form three new scenarios of de-
progresses. This could mean that impacts could occur lat- velopment: business-as-usual (BAU) less sustainable
er or earlier than anticipated. Figure 2 shows global mean (LS) and more sustainable (MS) (for definitions, see
temperature, SLR and the reference period (for values, see Supplementary Material). In the simulations, polder
Supplementary Material). Due to different model height was maintained at design height.
1832 S. Brown et al.
Methods Fig. 3 Left-hand side: impact for each reference period 1.5, 2.0 and„
3.0 °C is reached under the business as usual scenario. The less
ΔDIEM is a modelling framework designed to analyse link- sustainable and more sustainable illustrated similar results. Average
decadal mean, mean ± 1 standard deviation, maximum and minimum
ages between climatic change, environmental change, liveli- depth shown. a Depth of flooding in unprotected upazilas for the study
hoods, well-being and governance. It couples environmental, region. c Depth of flooding in protected upazilas for the study region. e
social and economic simulations by providing a novel inte- Area inundated due to flooding in protected and unprotected upazilas for
grated assessment platform for dynamic delta planning (Lázár the study region. Right-hand side: impact against time, using each year in
the decade where the reference temperature is reached for the business as
et al. 2018; Nicholls et al. 2016). usual, less sustainable and more sustainable scenarios. The average an-
Impacts were based on the decadal average mean, nual mean, maximum and minimum depth are shown. b Depth of
maximum, minimum and standard deviation of floods flooding in unprotected upazilas for the study region. dDepth of flooding
for the study regions and 70 upazilas (i.e. sub-district, in protected upazilas for the study region. fArea inundated due to flood in
2 protected and unprotected upazilas for the study regionmean area 270 km ). More than 90% of the upazilas
experience some daily (tidal) flooding in the model re-
The model was run for the ensemble members (Q0, Q8 and
gardless of reference temperature or ensemble member,
Q16) and three socio-economic conditions (BAU, LS and
reflecting low-lying areas outside polders. Cyclones were
MS) and reported for the 1.5, 2.0 and 3.0 °C decadal mean
not considered due to modelling complexities, but these
temperature intervals.
would exacerbate impacts. Three primary impact metrics
were analysed:
& Depth of flooding in areas which are unprotected from Results
flood waters, i.e. the floodplain;
& Depth of flooding in areas which are protected from flood Regional impacts
waters;
& Area of land inundated. Impacts are shown in Fig. 3. The left-hand side illustrates for
A further parameter was analysed (average decadal each reference period where 1.5, 2.0 and 3.0 °C are reached
mean only): under the BAU scenario for the average decadal mean, mean ±
& Number of people affected by flooding derived as a pro- 1 standard deviation, maximum and minimum of depth with-
portion of the area affected inundated assuming a uniform out protection, depth with protection and area inundated. The
population density per upazila. LS andMS scenarios produce similar results except for Q16 at
Fig. 2 a Global mean surface temperature (with respect to pre-industrial) the mean annual value in the decade that 1.5, 2.0 and 3.0 °C is reached.
and b SLR (with respect to 1986–2005) when 1.5, 2.0 and 3.0 °C is Multiple temperature reference periods even for the present day due to
reached for the Q0, Q8 and Q16 ensemble members. Each dot represents historical drivers in the model (see main text)
What are the implications of sea-level rise for a 1.5, 2 and 3 °C rise in global mean temperatures in the... 1833
1834 S. Brown et al.
2 and 3 °C, so are not shown. Q16 is projected to experience Spatial impacts
greater flooding due to more seasonal extremes (a drier dry
season and a wetter monsoon season), despite annual precipi- Figures 4, 5 and 6 illustrate mean impacts at upazila
tation levels being similar between each ensemble member level where there is high variability in the flooding for
(see Supplementary Material). The right-hand side illustrates the BAU scenario.
average annual mean, maximum and minimum depth without At 1.5 °C, the greatest depths of flooding without pro-
protection, depth with protection and area inundated against tection (Fig. 4), for each ensemble member, are projected
time, using each year in the decade where the reference tem- for the north-east upazilas, adjacent to the Meghna
perature is reached for the BAU, LS and MS scenarios. Estuary where there are fewer polders, reflecting higher
For the depth of flooding without protection (Fig. 3a) land elevations. Upazilas in the central region report the
in the 1.5 °C reference period, the mean depth of flooding lowest depths, although large variations around the mean
ranges from 0.16 m (Q16 2006–2016) to 0.19 m (Q8 are projected. At 2.0 °C, a similar pattern emerges, with
2028–2038). The average maximum depth of flooding is depths increasing in the southern and western upazilas,
0.14 m across all ensemble members. At 2.0 °C, the depth despite being poldered. The greatest increase in flood
ranges from 0.17 m (Q16 2019–2029) to 0.21 m (Q8 depths are projected at 3.0 °C, especially for the north-
2043–2053). The average decadal maximum depth is west, south-west upazilas and those north of Khulna.
projected as 0.10 to 0.14 m higher than the mean. At High variability in depths (i.e. where the decadal variabil-
3.0 °C, the mean depth of flooding without protection is ity is > 4 time larger than the mean value) is limited to
projected to be between 0.21 m (Q16 2041–2051) and nine upazilas.
0.27 m (Q8 2072–2082). In absolute values, the spread The depth of flooding with protection (Fig. 5) is lower
between the mean and the maximum is the greatest for across all upazilas compared with flooding without pro-
higher rises in temperature. The standard deviation of tection, but there is a greater variability in the maximum
flood depth remains similar through time and across cli- projected depth (particularly Q8). Across all scenarios,
matic and development scenarios. flood depth is the greatest in the west and south, which
Figure 3b illustrates these changes with time, where there is is the opposite finding of flood depth without protection.
an overlap between the 1.5 and the 2.0 °C scenarios. There is Hence, model results indicate polders are effective.
no clear impact signal at 1.5 °C until at least the 2040s. The The area inundated by flooding (Fig. 6) shows much
average maximum depth is rising in proportion to the average variability in area across all upazilas. The largest area of
mean depth, with both having a small acceleration in the rate flooding occurs in the south (where the highest flood depth
of impacts under the 3.0 °C scenario. with protection was reported) despite being poldered. The
For the depth of flooding with protection, the greatest un- area least flooded is projected away from the main river
certainty in impacts is between climate scenarios (Fig. 3c) and systems. Adjacent to the Meghna Estuary, the upazilas
annual variability (Fig. 3d). For the 1.5 °C reference frame, the with the greatest flooding (in the north-east) have fewer
mean depth ranges between 0.04 m (Q16 2006–2016) and polders than those with less flooding in the south-east.
0.06 m (Q8 2028–2038). At 2.0 °C, the mean depth ranges Relatively, the greatest proportion of flooding per upazila
between 0.05 m (Q8 2043–2053) and 0.07 m (Q16 2019– (> 20%) is projected to occur in the north and centre of the
2029), and at 3.0 °C, the mean depth ranges between 0.07 m region, including Khulna (see Supplementary Material).
(Q16 2041–2051) and 0.09 m (Q8 2072–2082). Again, simi- The number of people affected by flooding and the
lar to Fig. 3b, the implications of 1.5 °C is not clearly seen number of people affected by flooding per square
over annual mean variations until at least the 2040s. At 3.0 °C, kilometre was analysed (see Supplementary Material).
the minimum flood depth increases with respect to the mean, The areas with the lowest population flooded per upazila
and flooding is more frequent. and per square kilometre are in the west, south-west and
Figure 3e illustrates the mean area inundated from east of the study region. In the west, this reflects low
flooding. This ranges from 980 km2 (Q16 in 2006– flood depth and area flooded, particularly in a poldered
2016) to 1,470 km2 (Q8 in 2028–2038) for 1.5 °C de- area (despite a high population density in the region). In
pending of the model ensemble member (5–8% of the the south-west and east, this is because of lower popula-
region) . The mean area inundated ranges from tion densities. The greatest number of people projected to
1,150 km2 (Q16 in 2019–2029) to 1,770 km2 (Q8 2043– be affected by flooding per upazila and per square
53) for 2.0 °C and indicates an overlap with the 1.5 °C kilometre occurs around Khulna, which has partial protec-
scenario (Fig. 3f). For the 3.0 °C reference period, the tion. These trends remain the same regardless of ensemble
mean area inundated increases to between 1,620 km2 member or temperature threshold.
(Q16 in 2041–2051) and 2,490 km2 (Q8 in 2072–2082) Regional differences in the flood depth (with protection)
(9–13% of the region). and inundated areas under the Q16 climate and the 2.0 and
What are the implications of sea-level rise for a 1.5, 2 and 3 °C rise in global mean temperatures in the... 1835
Fig. 4 Illustration of the average decadal mean depth of flooding without protection for across the 70 upazilas. Source base maps: National Water
Resources Database
3.0 °C temperature profiles under BAU compared with LS longer due to the commitment to SLR (Goodwin et al.
and MS occur due to extreme flooding in six upazilas. 2018; Nicholls et al. 2018; Nicholls and Lowe 2004),
Here, flood depths are projected to be four times higher and there remains considerable uncertainty in the rate of
under BAU than LS or MS (Fig SM3). These upazilas rise (e.g. Goodwin et al. 2018). Therefore, a progressive
are spread throughout the study region, with the exception increase in flooding can be expected in coastal
of south-east area. For population, there are fewer extremes Bangladesh unless there is adaptation. Furthermore,
in regional variations for the LS and MS scenarios com- changes to high river flows are also worthy of consider-
pared with BAU (see Supplementary Material). ation as there is uncertainty in precipitation and ice melt
from glaciers (Kraaijenbrink et al. 2017; Mohammed et al.
Context within the Paris Agreement 2017), which contributes to flooding in the study area.
Discernible impacts of 1.5 °C are not projected until
In this study, 1.5 °C is projected to occur in the decades the 2040s across all impact metrics. The mean depth of
from 2006–2016 to 2028–2038 (with respect to pre-indus- flooding with and without protection is projected to in-
trial). Hence, sea level is essentially at today’s level, so crease by approximately 2-fold across the range from a
future impacts will not be dissimilar to today. This is 1.5 °C to 3 °C reference period. Over the same reference
particularly important given uncertainties in modelling frame, the area flooded could increase 2.5-fold.
(e.g. polder height, elevation models, river flows, see Furthermore, local land level change, reflecting natural
Payo et al. (2017)). Even if climate change mitigation is and anthropogenic subsidence, may have greater control
successful, sea levels will keep rising for decades and on flood impacts than climate-induced SLR itself.
1836 S. Brown et al.
Fig. 5 Illustration of the average decadal mean depth of flooding with protection across the 70 upazilas. Source base maps: National Water Resources
Database
Regionally, without protection, the greatest flood depths & subsidence (which locally under human influence, could
and area flooded are projected in the north-east of the region, be two or three times the average value used here of
whilst the lowest is projected in the west away from the main 2.5 mm/year, see Brown and Nicholls (2015));
river. In terms of people affected by flooding, the upazilas & sea-level rise (particularly high ice melt, which could lead
with the higher population density to the west experience the to a sea-level rise of 1.14 m in 2100 for an unmitigated
least number of people affected. Large numbers are projected climate change scenario, see Goodwin et al. 2018);
to be flooded in the urban areas of Khulna and Barisal. These & socio-economic change (population is declining in the
areas could be targets for adaptation, and new polders are study area, and Szabo et al. (2015) estimated a population
under consideration for these areas. of between 11.4 and 14.1 million people by 2050 for the
three scenarios compared with a population of 14.1 mil-
Caveats lion people in 2011);
& polder design and maintenance (variation of polder height
As demonstrated in Fig. 3, natural annual variability is a major to design height is on average ± 0.4 m if extreme events
source of uncertainty in the magnitude of flooding. The results are considered, see Supplementary Material)
presented are internally consistent with each other and present & added ‘internal’ uncertainties of ΔDIEM (Lázár et al.
day observations, although the absolute differences in the 2018; Payo et al.2017).
model are hard to validate as the uncertainty surrounding the
data is poorly defined (see Supplementary Material). These uncertainties indicate potentially large variations
Uncertainties include in the timing and magnitude of flooding. In agreement with
What are the implications of sea-level rise for a 1.5, 2 and 3 °C rise in global mean temperatures in the... 1837
Fig. 6 Illustration of the average decadal mean area inundated due to flooding without protection across the 70 upazilas. Source base maps: National
Water Resources Database
previous research (e.g. Lewis et al. 2012), further knowl- Implications of a 1.5 °C+ world
edge and data are required of the topography, particularly
as the area is relatively flat and low-lying. Furthermore, it Past human changes are significant
is human actions that may affect impacts the greatest, such
as maintenance of poldered areas or human induced subsi- Humans have endeavoured to control rivers through the build-
dence. Additional research is required to better quantify ing of dams, barrages and embankments affecting flow and
these affects, including better estimates of land elevation sediment yield which can adversely affect drainage land use,
and embankment breaching (Krien et al. 2017) and appro- livelihoods, socio-ecological systems and flood risk (Roy
priate scenarios for the future. et al. 2017). This can have a greater affect than climate change.
Cyclones have not been considered in this analysis due to For instance, Pethick and Orford (2013) and Wilson et al.
their unpredictable nature and the need for thousands of sim- (2017) found tidal and morphodynamic changes due to
ulations to provide a full explanation on impacts. They could polderisation. Auerbach et al. (2015) found the height differ-
potentially cause significant damage, and further research is ence between natural and polderised land differed by an aver-
required to determine impacts or potential breaching of em- age of 0.02 m for each year a polder was present. This reflects
bankments based on cyclone strength, landfall location, restricted sedimentation and enhanced subsidence within pol-
timing and stage in the tidal cycle. The latter is particularly ders. In contrast, global mean SLRwas one tenth of this value.
important as if a cyclone coincides with the highest tides, Human factors will to continue to operate in the coming de-
impacts are most severe. cades, interacting with any climate change that occurs.
1838 S. Brown et al.
Fig. 7 a Location and elevation
of the four vulnerable deltas. b
Hypsometric curve illustrating the
elevation as a percentage of the
study area for each delta. The
vertical lines indicate the 5-m el-
evation levels
Commitment to sea-level rise of the land is located below the 5-m contour, respectively. In
the Mahanadi and Volta deltas, 83 and 88% of the deltas are
The threat of long-term flooding does not stop even if temper- below 5 m in elevation. Although errors in data elevation are
atures are stabilised, threatening deltas world-wide. Figure 7a expected (see Supplementary Material), it indicates that all
illustrates land below the 5-m contour line for four deltas (a) deltas are threatened by long-term SLR and subsidence.
Bangladeshi Ganges-Brahmaputra, (b) Indian Bengal (note Using multi-centennial stringent climate change mitiga-
these two are a wider region that the sub-section previously tion (at 1.5 °C) and high emission scenarios (Goodwin
described), (c) Indian Mahanadi and (d) Ghanaian Volta deltas et al. 2018), together with extreme sea levels (Muis et al.
extracted from the Shuttle Radar Topographic Mission dataset 2016), the area of each delta potential inundated by SLR
(USGS 2017) (for methodology, see SupplementaryMaterial). and a 100-year event is plotted in Fig. 8. SLR in 2300 is
These deltas in developing nations were selected as they are projected to be between 0.59 and 1.55 m (climate change
low lying, containing significant populations vulnerable to mitigation scenario) and 2.76 and 6.86 m (high emission
SLR. The elevation of each delta with respect to mean sea scenario) (for further details, see Supplementary Material).
level is shown in Fig. 7b. For the Bangladesh Ganges- These unmitigated scenarios are lower than projections of
Brahmaputra delta and the Indian Bengal delta, 53 and 77% multi-centennial or millennium sea-level change, such as
What are the implications of sea-level rise for a 1.5, 2 and 3 °C rise in global mean temperatures in the... 1839
Fig. 8 Area exposed to flooding with SLR and a 1-in-100-year extreme sea level over time for a high emissions and climate change mitigation scenario
for a Bangladesh Ganges-Brahmaputra; b Indian Bengal Delta; c Mahanadi Delta, India and d Volta Delta, Ghana
Clark et al. (2016) who suggest 2–4 m per century. populated deltas is challenging, but deserves more inves-
Reinforcing Fig. 7b, today, a large proportion of each delta tigation. At centennial timescales, and given the impacts
is at risk from being flooded. By 2200, 95% of the Indian that are projected in Fig. 7, the strategy of damming may
Bengal delta is projected to be exposed and 99% in 2300 need to be rethought, as witnessed in the removal of the
(reducing to 83 and 86% with climate change mitigation, Marmot Dam, Oregon, USA (Major et al. 2012).
respectively). In the Indian Bengal, Mahanadi and Volta Delta populations have a history of adaptation. For exam-
deltas nearly 100% of their deltas will be exposed by ple, surges during cyclones can have significant effects on
2300, with substantial reductions under climate change livelihoods, but improved warning and disaster risk manage-
mitigation. Hence, climate change mitigation reduces ex- ment in recent years have reduced risk (Iwasaki 2016).
posure over multi-centennial timescales. Adaptation in large deltas represents significant challenges
Promoting sedimentation in deltas is a good long-term given the geographic scale. Autonomous adaptation (at house-
strategy against SLR. In the deltas that are presented in hold or community levels) to SLR and other environmental
Fig. 8, sediment reduction and dispersion have been in- change, e.g. sale of assets, switching livelihoods or accessing
fluenced through dams (Bastia and Equeenuddin 2016; financial support will continue, provided the environment
Gupta et al. 2012; Gyau-Boakye 2001) and embankment changes slowly (Duncan et al. 2017). Appropriate adaptation
building (Auerbach et al. 2015) plus localised beach min- buys time, but will not ultimately solve the problem of multi-
ing (Appeaning Addo 2015; Mensah 1997). This has im- millennium climate-induced SLR without further mitigation.
proved livelihoods and development but also enhanced Planned adaptations in deltas, guided by the government and
flood and erosion risk, as each delta reports land loss other national or international organisations, are already doc-
today (Akhand et al. 2017; Armah and Amlalo 1998; umented, such as flood risk management plans and disaster
Sarwar and Woodroffe 2013) and growing flood plains risk reducing infrastructure (Tompkins et al. 2017). Planned
(Syvitski et al. 2009). The ability to raise land with con- adaptation at the national level could support autonomous
trolled sedimentation to combat SLR and subsidence in action at a local level at a larger geographical scale.
1840 S. Brown et al.
Planning for 1.5 °C further from the main river channel and is poldered. The
upazilas with the greatest projected flood depths are in the
For coastal impacts, a 1.5 °C world when the temperature is north-west near the river where the land is unprotected.
first reached will not be too dissimilar to conditions seen to- The greatest number of people affected by flooding are
day. Greater climate stabilisation appears to reduce impacts projected to be in the major population centres. Thus,
slightly in coastal Bangladesh. The benefits of climate change planned adaptation resources and skill building to create
mitigationwill have significant advantages on centennial scale adaptive capacity need to be targeted appropriately.
(e.g. by allowing time for humans and natural systems to & Climate change mitigation has significant benefits over
respond), particularly if sediment availability does not further centennial scales, to reduce both the rate and the magni-
decline or is maintained at present day levels. However, on- tude of SLR. Numerous deltas world-wide are under threat
going sea-level rise and subsidence means that whatever the from SLR and sediment starvation. Under a high emis-
stabilisation level, a growing requirement to adapt remains sions scenario, and without sufficient sedimentation or
extending beyond 2100. A response will require more fo- adaptation, nearly all deltaic land in the regions analysed
cussed and planned adaptation than is current. As an example, will be exposed to significant flooding by 2200 unless
the Bangladesh Delta Plan 2100 provides an institutional adaptation occurs. Over multi-centennial timescales, cli-
mechanism that has the potential to address this challenge. mate change mitigation to reduce SLR and sedimentation
Developing nations will feel the impacts of climate change in response to residual SLR and subsidence is key to the
first, in part due to their geographic location (e.g. Harrington deltas’ survival.
et al. 2016), but also due to their reliance on the environment & Planned adaptation today changes the physical landscape
for their livelihoods and the challenges of adaptation. The in the delta, and it is in this context that people will con-
Paris Agreement fails to recognise regional differences in cli- tinue to adapt. SLR is likely to make sustainable develop-
matic parameters. Adaptation funding needs to take account of ment more challenging particularly as assets and people
these regional differences in the context of sustainable devel- living in risky areas are likely to increase.
opment and ‘different national circumstances’ (United
Nations 2015). Adaptation planning is challenging due to Acknowledgements This work is carried out under the Deltas, vulnera-
multiple levels of co-ordination and integration into existing bility and Climate Change: Migration and Adaptation (DECCMA) pro-
ject (IDRC 107642) under the Collaborative Adaptation Research
policies and development (e.g. Stanturf et al. 2011). The Initiative in Africa and Asia (CARIAA) programme with financial sup-
greatest threat is the long-term commitment to SLR where port from the UK Government’s Department for international
additional adaptation is encouraged both nationally and local- Development (DFID) and the International Development Research
ly. Monitoring of SLR and subsidence remains important, as it Centre (IDRC), Canada. The views expressed in this work are those of
the creators and do not necessarily represent those of DFID and IDRC or
provides evidence of change and informs when to act. its Boards of Governors. Thanks to Susan Kay for advice on the SLR
scenarios. For data availability, see Supplementary Material.
Conclusions Open Access This article is distributed under the terms of the Creative
Commons At t r ibut ion 4 .0 In te rna t ional License (h t tp : / /
This study has assessed the impacts of SLR at temperatures creativecommons.org/licenses/by/4.0/), which permits unrestricted use,
equivalent to 1.5, 2.0 and 3.0 °C in coastal Bangladesh and the distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a link
wider implications for other vulnerable deltas. The immediate to the Creative Commons license, and indicate if changes were made.
effects of a 1.5 °C rise in temperature on the sea level may be
relatively small, but sea-level rise will have an important leg-
acy in delta regions. The following conclusions were drawn:
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