Articles | Volume 25, issue 6
https://doi.org/10.5194/nhess-25-2007-2025
https://doi.org/10.5194/nhess-25-2007-2025
Research article
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23 Jun 2025
Research article | Highlight paper |  | 23 Jun 2025

It could have been much worse: spatial counterfactuals of the July 2021 flood in the Ahr Valley, Germany

Sergiy Vorogushyn, Li Han, Heiko Apel, Viet Dung Nguyen, Björn Guse, Xiaoxiang Guan, Oldrich Rakovec, Husain Najafi, Luis Samaniego, and Bruno Merz

Data sets

Data sets of spatial counterfactuals Sergiy Vorogushyn et al. https://doi.org/10.5880/GFZ.RDOQ.2025.002

Model code and software

mHM hydrological model Luis Samaniego et al. https://doi.org/10.5281/zenodo.8279545

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Executive editor
The Ahr valley flood of 2021 has been one of the most severe flooding events in Germany, with the highest death toll since the coastal storm surge event of 1962, and severe destruction across the valley associated also with extreme financial loss. Deficits in the warning procedures were re-visited after this event, and major improvements like cell broadcast warnings were introduced. The question remains open if the event could have been even more devastating under (almost) the same weather situation. The spatial shift of the rainfall fields the authors conduct is a simple but very reasonable approach as input for estimating counterfactual flooding scenarios with their numerical models. In the paper they demonstrate that the flood could have been much worse in terms of the flood peaks, inundation areas and maximum depths as well as exposed assets, given a shift of the rainfall fields of only about 20 km.
Short summary
The July 2021 flood in central Europe was one of the deadliest floods in Europe in the recent decades and the most expensive flood in Germany. In this paper, we show that the hydrological impact of this event in the Ahr valley could have been even worse if the rainfall footprint trajectory had been only slightly different. The presented methodology of spatial counterfactuals generates plausible unprecedented events and helps to better prepare for future extreme floods.
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