Increased flooded area and exposure in the White Volta river basin in Western Africa, identified from multi-source remote sensing data
Increased flooded area and exposure in the White Volta river basin in Western Africa, identified from multi-source remote sensing data
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.
Li, Chengxiu
adaf46fc-1573-4c50-bd7f-b2e7ed048f7e
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8
Asamoah, Moses
8bc7f17a-7432-44e0-ab9f-c2dd1cee1aaf
Sheffield, Justin
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Dzodzomenyo, Mawuli
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Gebrechorkos, Solomon
ff77f8a3-b6ef-4cfd-aebd-a003bf3947a5
Anghileri, Daniela
611ecf6c-55d5-4e63-b051-53e2324a7698
Wright, Jim
94990ecf-f8dd-4649-84f2-b28bf272e464
8 March 2022
Li, Chengxiu
adaf46fc-1573-4c50-bd7f-b2e7ed048f7e
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8
Asamoah, Moses
8bc7f17a-7432-44e0-ab9f-c2dd1cee1aaf
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Dzodzomenyo, Mawuli
f7969c6b-5999-448b-befa-e1c2e0287895
Gebrechorkos, Solomon
ff77f8a3-b6ef-4cfd-aebd-a003bf3947a5
Anghileri, Daniela
611ecf6c-55d5-4e63-b051-53e2324a7698
Wright, Jim
94990ecf-f8dd-4649-84f2-b28bf272e464
Li, Chengxiu, Dash, Jadunandan, Asamoah, Moses, Sheffield, Justin, Dzodzomenyo, Mawuli, Gebrechorkos, Solomon, Anghileri, Daniela and Wright, Jim
(2022)
Increased flooded area and exposure in the White Volta river basin in Western Africa, identified from multi-source remote sensing data.
Scientific Reports, 12 (1), [3701].
(doi:10.1038/s41598-022-07720-4).
Abstract
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.
Text
s41598-022-07720-4
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e-pub ahead of print date: 8 March 2022
Published date: 8 March 2022
Additional Information:
Funding Information:
This work was funded through the ‘Building REsearch Capacity for sustainable water and food security In drylands of sub-saharan Africa’ (BRECcIA) which is supported by UK Research and Innovation as part of the Global Challenges Research Fund, grant number NE/P021093/1.
Publisher Copyright:
© 2022, The Author(s).
Identifiers
Local EPrints ID: 455877
URI: http://eprints.soton.ac.uk/id/eprint/455877
ISSN: 2045-2322
PURE UUID: cc78f62c-1dd4-43b5-97b4-bcb8c53158bd
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Date deposited: 07 Apr 2022 16:40
Last modified: 17 Mar 2024 03:55
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Author:
Moses Asamoah
Author:
Mawuli Dzodzomenyo
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