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 spatia...

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Bibliographic Details
Published in:Natural hazards and earth system sciences 2020-04, Vol.20 (4), p.967-979
Main Authors: Metin, Ayse Duha, Dung, Nguyen Viet, Schröter, Kai, Vorogushyn, Sergiy, Guse, Björn, Kreibich, Heidi, Merz, Bruno
Format: Article
Language:English
Subjects:
Accounting
Bias
Catchment area
Catchments
Climate change
Damage assessment
Dependence
Distribution functions
Environmental risk
Estimates
Flood control
Flood damage
Flood risk
Floods
Hydrology
Precipitation
Prejudice
Rain
Rainfall
Risk assessment
River networks
Simulation
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Summary: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 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.
ISSN:1684-9981
1561-8633
1684-9981
DOI:10.5194/nhess-20-967-2020