Preprints
https://doi.org/10.5194/nhess-2024-97
https://doi.org/10.5194/nhess-2024-97
10 Jun 2024
 | 10 Jun 2024
Status: a revised version of this preprint is currently under review for the journal NHESS.

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

Abstract. After a flood disaster, the question often arises: “What could have happened if the event had gone differently?” For example, what would be the effects of a flood if the path of a pressure system and the precipitation field had taken a different trajectory? In this paper, we use alternative scenarios of precipitation footprints shifted in space, the so-called “spatial counterfactuals” to generate plausible but unprecedented events. We explore the spatial counterfactuals of the deadly July 2021 flood in the Ahr Valley, Germany. We drive a hydrological model of the Ahr catchment with precipitation fields of this event systematically shifted in space. The resulting discharge is used as a boundary condition for a high-resolution two-dimensional hydrodynamic model. We simulate changes in peak flows, hydrograph volumes, maximum inundation extent and depths and affected assets and compare them to the simulations of the actual event. We show that even a slight shift of the precipitation field by 15–25 km eastwards, which does not seem implausible due to orographic conditions, causes an increase in peak flows at the gauge Altenahr of about 32 % and of up to 160 % at the individual tributaries. Also, significantly larger flood volumes of more than 25 % can be expected due to this precipitation shift. This results in significantly larger inundation extents and maximum depths at a number of analyzed focus areas. For example, in the focus area around Altenahr, the increase of mean and maximum depth of up to 1.25 m and 1.75 m, respectively, is simulated. The presented results should encourage flood risk managers as well as the general public to meet precautionary measures for extreme and unprecedented events.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Sergiy Vorogushyn, Li Han, Heiko Apel, Viet Dung Nguyen, Björn Guse, Xiaoxiang Guan, Oldrich Rakovec, Husain Najafi, Luis Samaniego, and Bruno Merz

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2024-97', Anonymous Referee #1, 22 Jul 2024
    • AC1: 'Reply on RC1', Sergiy Vorogushyn, 31 Oct 2024
  • RC2: 'Comment on nhess-2024-97', Michael Nones, 19 Sep 2024
    • AC2: 'Reply on RC2', Sergiy Vorogushyn, 31 Oct 2024
Sergiy Vorogushyn, Li Han, Heiko Apel, Viet Dung Nguyen, Björn Guse, Xiaoxiang Guan, Oldrich Rakovec, Husain Najafi, Luis Samaniego, and Bruno Merz

Data sets

Spatial counterfactuals for the July 2021 flood Sergiy Vorogushyn, Li Han, Heiko Apel, Viet Dung Nguyen, Björn Guse, Xiaoxiang Guan, Oldrich Rakovec, Husain Najafi, Luis Samaniego, and Bruno Merz https://dataservices.gfz-potsdam.de/portal/index.html

Model code and software

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

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

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Latest update: 18 Dec 2024
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Short summary
The July 2021 flood in Central Europe was one of the deadliest floods in Europe in the past 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 was only slightly different. The presented methodology of spatial counterfactuals generates plausible unprecedented events and helps better prepare for future extreme floods.
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