Abstract:
Accurate information on flood extent and exposure is critical for disaster management in datascarce,
vulnerable regions, such as Sub-Saharan Africa (SSA). However, uncertainties in flood extent
affect flood exposure estimates. This study developed a framework to examine the spatiotemporal
pattern of floods and to assess flood exposure through utilization of satellite images, ground-based
participatory mapping of flood extent, and socio-economic data. Drawing on a case study in the
White Volta basin in Western Africa, our results showed that synergetic use of multi-temporal radar
and optical satellite data improved flood mapping accuracy (77% overall agreement compared with
participatory mapping outputs), in comparison with existing global flood datasets (43% overall
agreement for the moderate-resolution imaging spectroradiometer (MODIS) Near Real-Time (NRT)
Global Flood Product). Increases in flood extent were observed according to our classified product,
as well as two existing global flood products. Similarly, increased flood exposure was also observed,
however its estimation remains highly uncertain and sensitive to the input dataset used. Population
exposure varied greatly depending on the population dataset used, while the greatest farmland and
infrastructure exposure was estimated using a composite flood map derived from three products,
with lower exposure estimated from each flood product individually. The study shows that there is
considerable scope to develop an accurate flood mapping system in SSA and thereby improve flood
exposure assessment and develop mitigation and intervention plans.
