Increased flooded area and exposure in the White Volta river basin in Western Africa, identified from multi-source remote sensing data

• Published in: Scientific reports Vol. 12; no. 1; p. 3701
• Main Authors: Li, Chengxiu, Dash, Jadunandan, Asamoah, Moses, Sheffield, Justin, Dzodzomenyo, Mawuli, Gebrechorkos, Solomon Hailu, Anghileri, Daniela, Wright, Jim
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 08.03.2022; Nature Publishing Group UK; Nature Portfolio
• Subjects: Agricultural land; Disaster management; Emergency preparedness; Environmental Monitoring - methods; Exposure; Floods; Mapping; Remote sensing; Remote Sensing Technology; River basins; Rivers; Satellite Imagery; Africa
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-022-07720-4

Accurate information on flood extent and exposure is critical for disaster management in data-scarce, 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.