Key points are not available for this paper at this time.
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.
Paprotny et al. (Fri,) studied this question.