Abstract
Recently, flood risk assessments have been extended to national and continental scales. Most of these assessments assume homogeneous scenarios, i.e. the regional risk estimate is obtained by summing up the local estimates, whereas each local damage value has the same probability of exceedance. This homogeneity assumption ignores the spatial variability in the flood generation processes. Here, we develop a multi-site, extreme value statistical model for 379 catchments across Europe, generate synthetic flood time series which consider the spatial correlation between flood peaks in all catchments, and compute corresponding economic damages. We find that the homogeneity assumption overestimates the 200-year flood damage, a benchmark indicator for the insurance industry, by 139%, 188% and 246% for the United Kingdom (UK), Germany and Europe, respectively. Our study demonstrates the importance of considering the spatial dependence patterns, particularly of extremes, in large-scale risk assessments.
Highlights
Flood risk assessments have been extended to national and continental scales
Hall et al.[19] and Dumas et al.[20] quantify economic damage and/or number of people exposed to the 100-year flood apart from expected annual damage (EAD) for England and Wales and for France, respectively
Lamb et al.[26], Wyncoll and G ouldby[27] and Metin et al.[12] compare three spatial dependence assumptions: (1) complete dependence, i.e. spatially homogeneous flood scenarios, (2) modelled dependence, i.e. spatially dependent scenarios, attempting to represent the real-world spatial dependence, and (3) complete independence, i.e. flood magnitudes vary randomly in space. These studies suggest that the often-used complete dependence assumption overestimates flood damages for large return periods and underestimate damages for small return periods, whereas the EAD values are marginally affected by spatial dependence according to Metin et al.[12]
Summary
Flood risk assessments have been extended to national and continental scales. In contrast to the homogeneity assumption, floods show substantial spatial variability in the associated atmospheric, catchment and river network processes, and as a consequence, the return periods of discharge peaks vary considerably along the river, across the catchment and across larger regions (e.g. Ref.[22]). This interplay of different processes in the generation of floods leads to distinct flood regimes, i.e. flood timing and magnitude, and spatially heterogeneous dependence patterns in flood peaks[23,24,25]. The effects of tail dependence have not been sufficiently investigated for regional flood risk assessments
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