Based on a radar-based precipitation dataset (2001 to 2022) of the German Weather Service, counterfactual studies on flash flood events in Germany are carried out. Counterfactual studies show what happens when an extreme event occurs under different conditions (e.g. at a different location) and can help disaster risk management to better prepare for such events. First, the ten most severe precipitation events in Germany are identified, which then serve as the basis for the counterfactual studies. In particular, the prominent case (floods in July 2021) is discussed in more detail. The TOP10 events are then shifted (depending on the distance from the point of origin) and the potential hydrological response to rare heavy precipitation events is analysed using a hydrological model. One aim is to determine how close the actual historical events are to the worst-case scenarios.

I find it a very nice paper with interesting results. However, these could be presented in a slightly more structured way, some detailed explanations for non-experts would be helpful and some of the highlights could be explained in more detail (especially part 2 of the results).

See attached PDF for details with major and minor comments.

The research work presented in the paper “A downward counterfactual analysis of flash floods in Germany” aims at understanding how high precipitation events in Germany could have resulted in stronger hydrological responses if they had occured elsewhere. To do so, the 10 most extreme HPEs were selected and shifted accross Germany, and a simplified hydrological model was used to calculate the quick runoff response on a large number of small catchments.

The results focus first on the Ahr river catchment, then on all subbasins in Germany. They quantify the exceedance of the maximum original peak by the highest counterfactual peak. More generally, the study presents a methodological framework for a systematic downward counterfactual search for flash floods at the national scale.

In my opinion, the paper is very interesting, and evidence of high-quality research. The paper is very well written, the scientific questions are well defined, and the assumptions are clearly outlined and discussed. The proposed work is very useful since counterfactutal thinking is a recent philosophy in flood risk assessment. I only have a few suggestions for the authors to improve the quality of their manuscript. I think some explanations and illustrations could be added.

Abstract: You should define the concept of counterfactual thinking in the abstract, for non-experts.

Line 72 : It would be good to clearly define the time window analysed (e.g. by just adding "between 2001 and 2022" at the end of line 72).

Line 113: It might be difficult to do, but I think that a figure illustrating the method and its different stages would make it much easier to understand.

Line 116 : Maybe you could briefly explain how is calculated the xWEI, and give some orders of magnitude.

Line 123: Can you detail "Clustered based on their neighborhood" ? Or show it on an example if you decide to include an illustration.

Line 133: Can you explain why the upper limit is precisely 750km2 for the catchment size? Could you give the minimum catchment size?

Table 1: Adding information about impacts (e.g. damage) would help understanding the gravity of these events, which are not well-known by international readers.

Figure 5: Could the legend be standardised?

Section 5/ Section 6: In my opinion it would be interesting to discuss the fact that this counterfactual approach is "only" performed from a hydrological point of view (hazard-based). However if you want to go to the bottom of the question "how close actual historical events have already touched upon the worst case scenario", you would need to shift to an impact-based approach.