TY  - JOUR
A1  - Metin, Ayse Duha
A1  - Dung, Nguyen Viet
A1  - Schröter, Kai
A1  - Vorogushyn, Sergiy
A1  - Guse, Björn
A1  - Kreibich, Heidi
A1  - Merz, Bruno
T1  - The role of spatial dependence for large-scale flood risk estimation
T2  - Natural hazards and earth system sciences
N2  - 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.
Y1  - 2020
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/59342
SN  - 1561-8633
SN  - 1684-9981
VL  - 20
IS  - 4
SP  - 967
EP  - 979
PB  - European Geosciences Union (EGU) ; Copernicus
CY  - Göttingen
ER  -