Litcius/Paper detail

Biases in national and continental flood risk assessments by ignoring spatial dependence

Viet Dung Nguyen, Ayse Duha Metin, Lorenzo Alfieri, Sergiy Vorogushyn, Bruno Merz

2020Scientific Reports28 citationsDOIOpen Access PDF

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.

Topics & Concepts

Homogeneity (statistics)Flood mythEconometricsHomogeneousSpatial variabilityEnvironmental scienceSpatial ecologyStatisticsSpatial dependenceExtreme value theoryRisk assessmentPhysical geographyGeographyEnvironmental resource managementComputer scienceMathematicsEcologyBiologyCombinatoricsArchaeologyComputer securityFlood Risk Assessment and ManagementHydrology and Drought AnalysisHydrology and Watershed Management Studies