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Merging modelled and reported flood impacts in Europe in a combined flood event catalogue for 1950–2020

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/persons/resource/Dominik.Paprotny

Paprotny,  Dominik
Potsdam Institute for Climate Impact Research;
Submitting Corresponding Author, Potsdam Institute for Climate Impact Research;

Rhein,  Belinda
External Organizations;

Vousdoukas,  Michalis I.
External Organizations;

Terefenko,  Paweł
External Organizations;

Dottori,  Francesco
External Organizations;

/persons/resource/Simon.Treu

Treu,  Simon
Potsdam Institute for Climate Impact Research;

Śledziowski,  Jakub
External Organizations;

Feyen,  Luc
External Organizations;

Kreibich,  Heidi
External Organizations;

Externe Ressourcen

https://doi.org/10.5281/zenodo.10678820
(Ergänzendes Material)

https://doi.org/10.5281/zenodo.12635205
(Ergänzendes Material)

Volltexte (frei zugänglich)

hess-28-3983-2024.pdf
(Verlagsversion), 10MB

Ergänzendes Material (frei zugänglich)
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Zitation

Paprotny, D., Rhein, B., Vousdoukas, M. I., Terefenko, P., Dottori, F., Treu, S., Śledziowski, J., Feyen, L., Kreibich, H. (2024): Merging modelled and reported flood impacts in Europe in a combined flood event catalogue for 1950–2020. - Hydrology and Earth System Sciences, 28, 17, 3983-4010.
https://doi.org/10.5194/hess-28-3983-2024


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_30264
Zusammenfassung
Long-term trends in flood losses are regulated by multiple factors including climate variation, demographic dynamics, economic growth, land-use transitions, reservoir construction and flood risk reduction measures. The attribution of those drivers through the use of counterfactual scenarios of hazard, exposure or vulnerability first requires a good representation of historical events, including their location, their intensity and the factual circumstances in which they occurred. Here, we develop a chain of models that is capable of recreating riverine, coastal and compound floods in Europe between 1950 and 2020 that had a potential to cause significant socioeconomic impacts. This factual catalogue of almost 15 000 such events was scrutinized with historical records of flood impacts. We found that at least 10 % of them led to significant socioeconomic impacts (including fatalities) according to available sources. The model chain was able to capture events responsible for 96 % of known impacts contained in the Historical Analysis of Natural Hazards in Europe (HANZE) flood impact database in terms of persons affected and economic losses and for 81 % of fatalities. The dataset enables the study of the drivers of vulnerability and flood adaptation due to a large sample of events with historical impact data. The model chain can be further used to generate counterfactual events, especially those related to climate change and human influence on catchments.