The authors present a method that, through a modeling exercise, combines storm transposition with catchment similarity to improve flood frequency analysis in small and medium catchments. They tested their method on a database of 13000 headwater catchments in Germany, where they applied an uncalibrated lumped hydrological model to 23 years of precipitation.

The method is interesting, well presented, and the results are promising. I think the paper can be accepted for publication once a few points are clarified.

Main comments:

• From a comprehensive analysis of 13000 catchments, I was hoping to see a map with the regional performance of this method, and the areas that might be problematic.
• What is the effect of the catchment area on method performance and the size of the transposition domain?
• The model you applied seems to have multiple limitations, and I am wondering what's the effect on your results. You choose to apply a CN model over lumped (small) basins. This implies that the response is driven by the cumulated value of precipitation and its distribution in time, and not by its intensity. Hortonian runoff is not simulated. The spatial variability of precipitation is lost - might be ok if your subbasins are very small. You represent only "quick runoff", while many of those catchments have annual maxima in winter, when soils are wet and slow runoff has a very high contribution on peaks.
• L121: In SST one of the most critical points is the definition of a similar transposition domain. With your method, you seem to transfer this to catchment similarity. Can you give more information on how the catchment similarity criteria are mixed, and how much your approach is sensitive to this choice?
• How sensitive is your method to not finding similar catchments in the transposition domain?
• One of your conclusions is that "the improvement declines when the radius of the transposition domain is extended beyond 30 km. I think this is based on figure 2 alone. In this figure, performance seems to generally decline with larger radius, but I don't see a performance decline after 30 km2. I'd argue that the performance seems mostly independent from the size of the transposition domain (while it might be more sensitive to the measure of catchment similarity).
• Transposing the HPE to the centroid of the catchment might result in biases (e.g. if the storm and the NC have an orientation, or if spatial distribution over the catchment is important - see Zhou, 2021)

Other comments:

• "Worst-Case scenarios" is in the title and the conclusions, but what do you define as a "worst case"? Is taking the strongest HPE within 10km the worst that can happen to a basin? Sometimes compound scenarios or very high (~500y?) return periods are considered.
• As you say, in your analysis FFA is strongly limited by the relatively short data availability (23 years). You apply a GEV over annual maxima using maximum likelihood, but usually for small data samples, POT and maybe L-moments estimation might be more appropriate.
• You use QS to evaluate particularly high return periods (200 years) over a short data record (23 years). If the quantile q is higher than every observations, is the best QS simply the closest to your observation? Is it correct to say that it's a better estimate?
• L26: I'm not sure why you describe flash floods here. You didn't specifically analyze effect on flash floods, and your approach is general.
• L31: It's subjective, but I would not call a 750km2 basin "small". Maybe small + medium?
• L98: Isn't CORINE updated every 6 years?
• L106: you refer to your other paper for the model application, but I think it would be useful to add some more information on the model setup and characteristics that are important for your results.
• L106: Please clarify: if I understand well, you apply a lumped CN model over basins with a median size of 15.7 km2. These basins are also combining into larger basins. I was confused how sometimes you talk about "upstream catchments" "transposition to each catchment in the CoI".
• L134: do you apply the HPE multiple times by transposing the same HPE to the centroid of each subcatchment? If so, do you think it's generates realistic precipitation fields?
• L157: do you mean that you disregard shape below 0 (0 is ok) and above 0.5?
• L195: GEV CoI is fitted over 22 years?
• L217: I don't see the supplement, also online.
• L220: are the HPE over larger domains less typical than CoI or just less correlated? How much do the HPE of the CoI overlap with the floods over NC?
• L254: aren't NCs analyzed as a set? So with 230 values.
• L258, L266, L267: I can't find those  numbers reflected in figure 4. Am I reading it wrong?
• L284: why would catchment biases cancel out?

Zhou, Zhengzheng, et al. "The impact of spatiotemporal structure of rainfall on flood frequency over a small urban watershed: an approach coupling stochastic storm transposition and hydrologic modeling." Hydrology and Earth System Sciences Discussions 2021 (2021): 1-25.