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A consistent approach for probabilistic residential flood loss modeling in Europe

Authors
/persons/resource/sluedtke

Lüdtke,  Stefan
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/kschroet

Schröter,  Kai
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/mstein

Steinhausen,  Max
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/lweise

Weise,  Laura
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Figueiredo,  Rui
External Organizations;

/persons/resource/kreib

Kreibich,  H.
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

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4812890.pdf
(Publisher version), 16MB

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Citation

Lüdtke, S., Schröter, K., Steinhausen, M., Weise, L., Figueiredo, R., Kreibich, H. (2019): A consistent approach for probabilistic residential flood loss modeling in Europe. - Water Resources Research, 55, 12, 10616-10635.
https://doi.org/10.1029/2019WR026213


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_4812890
Abstract
In view of globally increasing flood losses, a significantly improved and more efficient flood risk management and adaptation policy are needed. One prerequisite is reliable risk assessments on the continental scale. Flood loss modeling and risk assessments for Europe are until now based on regional approaches using deterministic depth‐damage functions. Uncertainties associated with the risk estimation are hardly known. To reduce these shortcomings, we present a novel, consistent approach for probabilistic flood loss modeling for Europe, based on the upscaling of the Bayesian Network Flood Loss Estimation MOdel for the private sector, BN‐FLEMOps. The model is applied on the mesoscale in the whole of Europe and can be adapted to regional situations. BN‐FLEMOps is validated in three case studies in Italy, Austria, and Germany. The officially reported loss figures of the past flood events are within the 95% quantile range of the probabilistic loss estimation, for all three case studies. In the Italian, Austrian, and German case studies, the median loss estimate shows an overestimation by 28% (2.1 million euro) and 305% (5.8 million euro) and an underestimation by 43% (104 million euro), respectively. In two of the three case studies, the performance of the model improved, when updated with empirical damage data from the area of interest. This approach represents a step forward in European wide flood risk modeling, since it delivers consistent flood loss estimates and inherently provides uncertainty information. Further validation and tests with respect to adapting the model to different European regions are recommended.