Development of an operational flood early warning system for Black Volta River Basin, West Africa

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cg.contributor.affiliationInternational Water Management Instituteen_US
cg.contributor.donorLeona M. and Harry B. Helmsley Charitable Trusten_US
cg.contributor.donorCGIAR Trust Funden_US
cg.contributor.initiativeClimate Resilienceen_US
cg.coverage.regionWestern Africaen_US
cg.creator.identifierSuman Kumar Padhee: 0000-0002-1949-6830en_US
cg.creator.identifierGiriraj Amarnath: 0000-0002-7390-9800en_US
cg.creator.identifierYakob Umer: 0000-0002-7325-3450en_US
cg.edition2nd Editionen_US
cg.identifier.doihttps://doi.org/10.1016/b978-0-443-14009-9.00002-xen_US
cg.identifier.iwmilibraryH053136en_US
cg.placeLondon, UKen_US
cg.river.basinVOLTAen_US
dc.contributor.authorPadhee, Suman Kumaren_US
dc.contributor.authorAmarnath, Girirajen_US
dc.contributor.authorUmer, Yakoben_US
dc.date.accessioned2024-09-30T22:43:29Zen_US
dc.date.available2024-09-30T22:43:29Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/152517en_US
dc.titleDevelopment of an operational flood early warning system for Black Volta River Basin, West Africaen_US
dcterms.abstractFloods are the most frequent disaster causing global economic losses in billions and pose a significant threat to modern civilization. The UNDRR strongly advocates for flood early warning system (FEWS) with scientific rationale for all nations by 2027, acknowledging that developing countries face financial and human resource challenges in adopting advanced FEWS infrastructure. This study is focused on the development of a FEWS for the Black Volta Basin (BVB) in West Africa with free data resources and open-source modeling infrastructure. It is based on the approach of integrating the Deltares wflow_sbm hydrologic model and the LISFLOOD-FP hydrodynamic model for forecasting flood and inundation maps. The wflow_sbm is calibrated (1990–1997, NSE value = 0.71) and validated (1998–2007, NSE value = 0.72) by using station-based gridded rainfall from the West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL) and discharge time series from Global Runoff Data Centre (GRDC) portals. Based on the calibrated parameters, wflow_sbm model is utilized to produce hydrograph for the years 2001–2022 with raw and bias-corrected GPM-IMERG rainfall inputs, where the discharge with the latter is found to outperform that from the former. The peak flood event from the produced hydrograph by the wflow model is fed into a 2D hydraulic model, LISFLOOD-FP model, to simulate the flood extent. Evaluation of modeled inundation modeling by comparing with satellite inundation observation during flood 2022 case resulted in an acceptable range (F = 0.527). Hydrograph for the flood 2022 case is overlapped with hydrographs from GEFSv12 weather forecast inputs in 1 day, 2 days, and 3 days. It is found that the absolute error percentage for 1 day throughout most of the season is forecasted under 10% including the peak of the flood. Forecasts lead time of 2 and 3 days are observed to have degraded accuracy as compared to 1-day forecasts due to higher uncertainties. Identification of the onset of hydrograph inclination is also found to underperform by GEFSv12 inputs and possible causes are discussed. The aim of this work is to promote FEWS with limited resources in African river basins, considering the problem of data scarcity.en_US
dcterms.accessRightsLimited Accessen_US
dcterms.available2024-09-27en_US
dcterms.bibliographicCitationPadhee, Suman Kumar; Amarnath, Giriraj; Umer, Yakob. 2025. Development of an operational flood early warning system for Black Volta River Basin, West Africa. In Adams III, T. E.; Gangodagamage, C.; Pagano, T. C. (Eds.). Flood forecasting: a global perspective. 2nd ed. London, UK: Academic Press. pp.27-39. [doi: https://doi.org/10.1016/B978-0-443-14009-9.00002-X]en_US
dcterms.extentpp.27-39.en_US
dcterms.issued2025-01en_US
dcterms.languageenen_US
dcterms.licenseCopyrighted; all rights reserveden_US
dcterms.publisherAcademic Pressen_US
dcterms.subjectflood forecastingen_US
dcterms.subjectearly warning systemsen_US
dcterms.subjectmonitoringen_US
dcterms.subjectmodelsen_US
dcterms.subjectriver basinsen_US
dcterms.subjectrainfallen_US
dcterms.subjectdisaster risk reductionen_US
dcterms.subjectcase studiesen_US
dcterms.typeBook Chapteren_US

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