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dc.contributor.authorBERNHOFEN MARKen_GB
dc.contributor.authorWYMAN CHARLIEen_GB
dc.contributor.authorTRIGG MARKen_GB
dc.contributor.authorSLEIGH ANDREWen_GB
dc.contributor.authorSMITH ANDREWen_GB
dc.contributor.authorSAMPSON CHRISTOPHERen_GB
dc.contributor.authorYAMAZAKI DAIen_GB
dc.contributor.authorWARD PHILIPen_GB
dc.contributor.authorRUDARI ROBERTOen_GB
dc.contributor.authorPAPPENBERGER FLORIANen_GB
dc.contributor.authorDOTTORI FRANCESCOen_GB
dc.contributor.authorSALAMON PETERen_GB
dc.contributor.authorWINSEMIUS HESSEL C.en_GB
dc.identifier.citationENVIRONMENTAL RESEARCH LETTERS vol. 13 no. 10 p. 104007en_GB
dc.identifier.issn1748-9326 (online)en_GB
dc.description.abstractGlobal flood models (GFMs) are becoming increasingly important for disaster risk management internationally. However, these models have had little validation against observed flood events, making it difficult to compare model performance. In this paper, we introduce the first collective validation of multiple GFMs against the same events and we analyze how different model structures influence performance. We identify three hydraulically diverse regions in Africa with recent large scale flood events: Lokoja, Nigeria; Idah, Nigeria; and Chemba, Mozambique.We then evaluate the flood extent output provided by six GFMs against satellite observations of historical flood extents in these regions. The Critical Success Index of individual models across the three regions ranges from 0.45 to 0.7 and the percentage of flood captured ranges from 52% to 97%. Site specific conditions influence performance as the models score better in the confined floodplain of Lokoja but score poorly in Idah’s flat extensive floodplain. 2D hydrodynamic models are shown to perform favourably. The models forced by gauged flow data show a greater level of return period accuracy compared to those forced by climate reanalysis data. Using the results of our analysis, we create and validate a three-model ensemble to investigate the usefulness of ensemble modelling in a flood hazard context. We find the ensemble model performs similarly to the best individual and aggregated models. In the three study regions, we found no correlation between performance and the spatial resolution of the models. The best individual models show an acceptable level of performance for these large rivers.en_GB
dc.description.sponsorshipJRC.E.1-Disaster Risk Managementen_GB
dc.titleA first collective validation of global fluvial flood models for major floods in Nigeria and Mozambiqueen_GB
dc.typeArticles in periodicals and booksen_GB
dc.identifier.doi10.1088/1748-9326/aae014 (online)en_GB
JRC Directorate:Space, Security and Migration

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