Preprints
https://doi.org/10.5194/nhess-2023-224
https://doi.org/10.5194/nhess-2023-224
02 Jan 2024
 | 02 Jan 2024
Status: this preprint is currently under review for the journal NHESS.

A downward counterfactual analysis of flash floods in Germany

Paul Voit and Maik Heistermann

Abstract. In this study, we present the results of a counterfactual search for flash flood events in Germany. We used DWD’s RADKLIM product to identify the ten 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 realisations 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 gauge Altenahr by a factor of two. Compared to the peak flow of 1004 m3/s caused by the event in its original position, the worst case counterfactual of that event led to a peak flow of 1311 m3/s. Shifting another event that had occurred just one month earlier in eastern Germany over the Ahr river valley even effectuated a simulated peak flow of 1651 m3/s.

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: with regard to 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 on what could happen in case certain extreme events occurred elsewhere, and thereby reduce the element of surprise in disaster risk management.

Paul Voit and Maik Heistermann

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • AC1: 'Comment on nhess-2023-224', Paul Voit, 02 Jan 2024
  • RC1: 'Comment on nhess-2023-224', Anonymous Referee #1, 12 Feb 2024
  • RC2: 'Comment on nhess-2023-224', Anonymous Referee #2, 14 Feb 2024
Paul Voit and Maik Heistermann

Interactive computing environment

Examplary model code and notebooks Paul Voit https://github.com/plvoit/counterfactual_flash_flood_analysis

Paul Voit and Maik Heistermann

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Short summary

To identify the flash flood potential in Germany, we shifted the most extreme rainfall events from the last 22 years systematically across Germany and simulated the consequent run off reaction.

Our results show, that almost all areas in Germany have not seen the worst-case scenario of flood peaks within the last 22 years. With a slight spatial change of historical rainfall events, flood peaks by the factor 2 or more would be achieved for most areas. The results can aid disaster risk management.

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