A downward-counterfactual analysis of flash floods in Germany

Abstract

Counterfactuals are scenarios that describe alternative ways of how an event, in this case an extreme rainfall event, could have unfolded. In this study, we present the results of a counterfactual search for flash flood events in Germany. We used a radar-based precipitation dataset from Germany's national meteorological service (Deutscher Wetterdienst) to identify the 10 most extreme precipitation events in Germany from 2001 to 2022 and then assumed that any of these top 10 events could have happened anywhere in Germany. In other words, the events were shifted around all over Germany. For all resulting positions of the precipitation fields, we simulated the corresponding peak discharge for any affected catchment smaller than 750 km2. From all the realizations of this simulation experiment, the maximum peak discharge was identified for each catchment. In a case study, we first focused on the devastating flood event in July 2021 in western Germany. We found that a moderate shifting of the event in space could change the event peak flow at the Altenahr gauge by a factor of 2. Compared to the peak flow of 1004 m3 s−1 caused by the event in its original position, the worst-case counterfactual of that event led to a peak flow of 1311 m3 s−1. Shifting another event that had occurred just 1 month earlier in eastern Germany over the Ahr River valley even effectuated a simulated peak flow of 1651 m3 s−1. For all analysed subbasins in Germany, we found that, on average, the highest counterfactual peak exceeded the maximum original peak (between 2001 and 2022) by a factor of 5.3. For 98 % of the basins, the factor was higher than 2. We discuss various limitations of our analysis, which are important to be aware of, namely, the quantification and selection of candidate rainfall events, the hydrological model, and the design of the counterfactual search experiment. Still, we think that these results might help to expand the view of what could happen in the case that certain extreme events occurred elsewhere and thereby reduce the element of surprise in disaster risk management.