The role of spatial dependence for large-scale flood risk estimation
- Flood risk assessments are typically based on scenarios which assume homogeneous return periods of flood peaks throughout the catchment. This assumption is unrealistic for real flood events and may bias risk estimates for specific return periods. We investigate how three assumptions about the spatial dependence affect risk estimates: (i) spatially homogeneous scenarios (complete dependence), (ii) spatially heterogeneous scenarios (modelled dependence) and (iii) spatially heterogeneous but uncorrelated scenarios (complete independence). To this end, the model chain RFM (regional flood model) is applied to the Elbe catchment in Germany, accounting for the spatio-temporal dynamics of all flood generation processes, from the rainfall through catchment and river system processes to damage mechanisms. Different assumptions about the spatial dependence do not influence the expected annual damage (EAD); however, they bias the risk curve, i.e. the cumulative distribution function of damage. The widespread assumption of complete dependenceFlood risk assessments are typically based on scenarios which assume homogeneous return periods of flood peaks throughout the catchment. This assumption is unrealistic for real flood events and may bias risk estimates for specific return periods. We investigate how three assumptions about the spatial dependence affect risk estimates: (i) spatially homogeneous scenarios (complete dependence), (ii) spatially heterogeneous scenarios (modelled dependence) and (iii) spatially heterogeneous but uncorrelated scenarios (complete independence). To this end, the model chain RFM (regional flood model) is applied to the Elbe catchment in Germany, accounting for the spatio-temporal dynamics of all flood generation processes, from the rainfall through catchment and river system processes to damage mechanisms. Different assumptions about the spatial dependence do not influence the expected annual damage (EAD); however, they bias the risk curve, i.e. the cumulative distribution function of damage. The widespread assumption of complete dependence strongly overestimates flood damage of the order of 100% for return periods larger than approximately 200 years. On the other hand, for small and medium floods with return periods smaller than approximately 50 years, damage is underestimated. The overestimation aggravates when risk is estimated for larger areas. This study demonstrates the importance of representing the spatial dependence of flood peaks and damage for risk assessments.…
Author details: | Ayse Duha MetinORCiDGND, Nguyen Viet DungORCiD, Kai SchröterORCiDGND, Sergiy VorogushynORCiDGND, Björn GuseORCiD, Heidi KreibichORCiDGND, Bruno MerzORCiDGND |
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DOI: | https://doi.org/10.5194/nhess-20-967-2020 |
ISSN: | 1561-8633 |
ISSN: | 1684-9981 |
Title of parent work (English): | Natural hazards and earth system sciences |
Publisher: | European Geosciences Union (EGU) ; Copernicus |
Place of publishing: | Göttingen |
Publication type: | Article |
Language: | English |
Date of first publication: | 2020/04/09 |
Publication year: | 2020 |
Release date: | 2023/06/01 |
Volume: | 20 |
Issue: | 4 |
Number of pages: | 13 |
First page: | 967 |
Last Page: | 979 |
Funding institution: | European Union's Horizon 2020 research and innovation programme under a; Marie Sklodowska-Curie grant [676027]; German Research Foundation; (Deutsche Forschungsgemeinschaft -DFG)German Research Foundation (DFG); [FOR 2416] |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Umweltwissenschaften und Geographie |
DDC classification: | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften |
Peer review: | Referiert |
Publishing method: | Open Access / Gold Open-Access |
DOAJ gelistet | |
License (German): | CC-BY - Namensnennung 4.0 International |