the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
It could have been much worse: spatial counterfactuals of the July 2021 flood in the Ahr valley, Germany
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.
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RC1: 'Comment on nhess-2024-97', Anonymous Referee #1, 22 Jul 2024
Herein, the authors create a set of 25 counterfactual extreme precipitation events to simulate the catastrophic flooding seen in the Ahr Valley, Germany during July of 2021. Their use of downscaled precipitation data and hydrological modelling showed that small shifts in the trajectory of the storm systems could have resulted in even worse flooding events than what was experienced. This type of analysis shows stakeholders and policy makers how best to be prepared for natural disasters and emerging climate risks.
Overall, I found the paper to be of excellent quality. I had one major comment on the precipitation data used and a few minor comments (see attached). After those are addressed, I am confident this paper will be ready for publication.- AC1: 'Reply on RC1', Sergiy Vorogushyn, 31 Oct 2024
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RC2: 'Comment on nhess-2024-97', Michael Nones, 19 Sep 2024
Dear Authors,
I really enjoyed reading your manuscript, as it is written clearly and drives all key information in the proper way.
As you can see from my comments below, I do not see critical points in the text, and I am generally in favour of its publication after revision. I hope my comments will help you in clarifying the overall approach and what we can learn from this example.
General comments
I suggest adding some more comments on the numerical model in the Abstract (which one? calibrated/validated how?), as results depend on it.
Ludwig et al. (2023) pointed out a significant role of sediment in the 2021 event. As you used a hydrodynamics model assuming clear water, could you please comment on potential uncertainties connected with river/valley morphodynamics? What about considering other floating materials constituting the accumulated debris?
Figure 4 shows that the model tends to anticipate the observed/reconstructed flood wave. Does this affect your results? Could you please comment a bit more on this, while presenting the results (Sec. 4.2)
Secs. 4.5 & 4.6: As the results are influenced by simplifications in the modelling scheme and uncertainties in the input data, I suggest providing not only final exact results, but also discussing more in detail uncertainties, providing their estimate
In the Discussion, you pointed out that, out of infinite spatial counterfactual scenarios, you used only 25. Could you please provide more details on how you selected them, also expanding the Introduction by adding some more comments on the study rationale?
From your results, one can argue that flood mapping should be done by considering multiple (potentially infinite) scenarios. Do you think that flood risk mapping and communication should be improved? How? In what direction should research go, to help communities to increase their willingness to undertake risk reduction measures for unprecedented events? This point could be discussed also in light of the very recent floods caused by storm Boris.
Specific comments & Technical corrections
Figure 1: please add a world map and a map of Germany to better locate the study area for readers not familiar with the region. DEM elevation is [m asl]
line 200: “RANDOLAN” is wrongly spelled
line 318: please add the units of Manning’s roughness n
line 449: you stated that “differences are small”. Is it possible to have an estimate of how much small?
line 559: I suggest deleting “an apocalyptic scenario beyond the imagination of decision-makers and flood-prone people” as it sounds a bit too personal statement and not a scientific one (even if it’s true)
Figs. A1-A6: I think there is a typo in the legend, as the red box should read “… statistics”
The work of Montanari is now published, so please update the references. Montanari, A., Merz, B., & Blöschl, G. (2024). HESS Opinions: The sword of Damocles of the impossible flood. Hydrology and Earth System Sciences, 28(12), 2603-2615. https://doi.org/10.5194/hess-28-2603-2024
Please update the reference Khosh Bin Ghomash, S., Apel, H., & Caviedes-Voullième, D. (2024). Are 2D shallow-water solvers fast enough for early flood warning? A comparative assessment on the 2021 Ahr valley flood event. Natural Hazards and Earth System Sciences, 24(8), 2857-2874. https://doi.org/10.5194/nhess-24-2857-2024
Citation: https://doi.org/10.5194/nhess-2024-97-RC2 - AC2: 'Reply on RC2', Sergiy Vorogushyn, 31 Oct 2024
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
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