Evaluation of river flood extent simulated with multiple global hydrological models and climate forcings. (13th August 2021)

• Record Type: Journal Article
• Authors: Mester, Benedikt; Willner, Sven Norman; Frieler, Katja; Schewe, Jacob
• Is Part Of: Environmental research letters. Volume 16:Number 9(2021)
• Publication Date: 2021-08-13
• Subjects: global flood model -- validation -- model intercomparison -- flood risk -- global hydrological model; Environmental sciences -- Periodicals; Human ecology -- Research -- Periodicals; Environmental health -- Periodicals; 333.7
• DOI: 10.1088/1748-9326/ac188d
• Languages: English
• ISSNs: 1748-9326

Abstract

Abstract: Global flood models (GFMs) are increasingly being used to estimate global-scale societal and economic risks of river flooding. Recent validation studies have highlighted substantial differences in performance between GFMs and between validation sites. However, it has not been systematically quantified to what extent the choice of the underlying climate forcing and global hydrological model (GHM) influence flood model performance. Here, we investigate this sensitivity by comparing simulated flood extent to satellite imagery of past flood events, for an ensemble of three climate reanalyses and 11 GHMs. We study eight historical flood events spread over four continents and various climate zones. For most regions, the simulated inundation extent is relatively insensitive to the choice of GHM. For some events, however, individual GHMs lead to much lower agreement with observations than the others, mostly resulting from an overestimation of inundated areas. Two of the climate forcings show very similar results, while with the third, differences between GHMs become more pronounced. We further show that when flood protection standards are accounted for, many models underestimate flood extent, pointing to deficiencies in their flood frequency distribution. Our study guides future applications of these models, and highlights regions and models where targeted improvements might yield the largest performance gains.