Reply to RC1
Year: 2024
Type: peer-review
Abstract: . 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. 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, 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 scrutinised with historical records of flood impacts. We found that at least 10 % of them had 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 HANZE flood impact database in terms of persons affected and economic losses, and for 81 % of fatalities. The dataset enables studying drivers of vulnerability and flood adaptation due to a large sample of events with historical impact data. The model chain can further be used to generate counterfactual events, especially related to climate change and human influence on catchments.
Author: Dominik Paprotny
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
OpenAlex ID: W4393949417