the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 20 May 2026
Towards improved integration of hydrological uncertainty and hydraulic model sensitivity in flood hazard mapping
Abstract. The study investigates the impact of hydrological uncertainties and the related sensitivity of the hydrodynamic modelling results on flood hazard mapping. Uncertainties in flood frequency analysis (FFA), including anticipated impact of climate change and sensitivity to channel and floodplain roughness, were examined. The study area is the lower Vipava river, a transboundary catchment shared between Slovenia and Italy with variable floodplain topography. Sensitivity analysis revealed that uncertainty in FFA and river channel roughness significantly influenced the inundation spatial extent and inundation depth, the impact of floodplain roughness appears to be limited. The analysis shows that natural successional changes in river channel roughness substantially impact the results of a 10-year RP event, increasing flood extent by 45%. The increase in inundated areas is less pronounced for 100- and 500-year RP floods, with increases of 15% and 11%, respectively. The assessed probability of inundation based on scenario ensembles provided an informative identification of areas most susceptible to potential changes in flood hazard. Our findings highlight the need to address critical scenario ensembles that incorporate FFA uncertainty and hydraulic roughness sensitivity, leading to more informative flood hazard mapping for steering future land use planning.
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Status: open (until 02 Jul 2026)
- RC1: 'Comment on egusphere-2026-2602', Michael Nones, 25 May 2026 reply
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AC1: 'Comment on egusphere-2026-2602', Simon Rusjan, 24 Jun 2026
reply
Reply to Reviewer comments
We would like to thank Dr. Nones for his insightful comments and suggestions, which we found very helpful for improving our manuscript and presenting the results more concisely. Please find below our detailed replies, where we explain how we will address the general and specific comments. All changes will be tracked in the revised version of the manuscript (with track changes), which we will resubmit after receiving comments from all reviewers. We will also indicate where (i.e. by giving line numbers) each point of the reviewers' comments has been incorporated.
General comments:
The work presents an interesting approach on flood mapping, which includes the analysis of hydrological uncertainty and model sensitivity while developing flood hazard maps. The case study is a reach of the Vipava River, a transboundary river flowing from Slovenia to Italy.
The goal of the study is proper and timely, but, in my opinion, the manuscript should be significantly better developed before publication, starting from a more explicit stressing of the novelty, and how this specific work goes beyond the current state of the art. Indeed, the need for considering uncertainty in flood mapping is not a new topic, and there are examples in the literature, which should be addressed in the Introduction to point out knowledge gaps.
General comment #1 reply: Thank you for this comment. We will extend the “Introduction” section and add examples from the literature to better emphasize the novelty of the proposed approach and explain how our work goes beyond the current state of the art. We agree with the reviewer that considering uncertainty in flood mapping is not a new topic; however, in our view, and as noted by the reviewer, there is still a substantial knowledge gap between most theoretical approaches proposed for incorporating uncertainty and sensitivity into flood hazard mapping and the more practical implementation of these approaches.
The methodological part could be further expanded, also following my detailed comments below, to better guide readers through all the steps needed to produce the maps you show, and also what is needed to evaluate them from a quantitative point of view.
General comment #2 reply: We will incorporate the reviewer’s suggestions to improve the methodological part of the paper and better present the steps involved in the proposed methodological approach and the resulting maps.
I strongly advise separating the Results from the Discussion, expanding the latter section to better highlight the novelty of the study and what other scholars and stakeholders can learn from your application. Likely in the Introduction, a more in-depth review of the state of the art would support your statements in a more thorough manner, moving from reporting results to actually discussing them from a critical point of view.
General comment #3 reply: Following the reviewer’s comments, we will extend the Introduction section by providing a more in-depth review of the state of the art on different approaches for incorporating uncertainty and sensitivity analysis into flood hazard mapping. We will make a clearer distinction between the “Results” and “Discussion” sections to highlight the novelty of the study and provide a more concise overview of our results in relation to previous studies.
Detailed comments:
Introduction
- please avoid excessive use of AI-generated text. The first line of the Introduction could be found in many other similar studies, always with the same phrasing.
Detailed comment #1 reply: Following the reviewer comment we will rewrite the first sentence to improve the introduction into the topic. We would like to point out that we used AI tools only to support us in grammar and syntax review.
- there are no such things as “natural disasters”. As pointed out by UNDRR (https://www.undrr.org/our-impact/campaigns/no-natural-disasters), we have to change the way we communicate, and acknowledge that nature is not causing disasters, while is the presence of humans plays the major role.
Detailed comment #2 reply: We would like to thank the reviewer for this comment, we completely agree with reviewer’s notion. We will replace the term “natural disaster” with “natural hazard” throughout the manuscript.
- line 27: how can mapping reduce hazard? The link is not fully clear, as, usually, mapping is a good way to reduce risks. Please rephrase this paragraph.
Detailed comment #3 reply: Thank you for noting this. We will rephrase the sentence.
- lines 40-43: please double-check the language. I guess it should read “This…”. But also in this case, the language could be improved
Detailed comment #4 reply: Thank you for noting this. We will rephrase the sentences to improve the language.
- line 54: what critical scenarios and selected how? It would be good to have more details already in the Introduction, also to better catch the transferability of results/approach
Detailed comment #5 reply: Thank you for the comment. We will extend the description of the “scenario ensembles” to ensure a clearer link between the “Introduction” and “Methods” sections.
- line 59: additional information on how this roughness is calculated would help in understanding the novelty of the study. For example, have you considered time-changing roughness during the simulation or just values depending on the land use? Even if addressed later in the study, adding some comments in the Introduction would help readers better follow you.
Detailed comment #6 reply: Thank you for the comment. We will rephrase this paragraph to include the points raised by the reviewer, specifically potential changes in river channel roughness and land use-related roughness conditions. We have not considered time-changing roughness during the simulation but just values depending on the land use.
Methods
- please change the title to a more general “Materials and Methods”, as you are also presenting the input data
Detailed comment #7 reply: Thank you for the comment. As suggested by the reviewer, we will change the title to “Materials and Methods”.
- line 77-78: where can readers see the flood inundation extent? Can you provide some additional references?
Detailed comment #8 reply: We will improve Figure 1 by adding the flood inundation extent. The inundation extent polygon is based on the observed flood extent during few past flood events. The shown flood extent will provide a general representation of a flood event in the range of a 100-year return period.
- Figure 1: what is the source of the buildings polygons? I suggest acknowledging data sources more properly.
Detailed comment #9 reply: Thank you for pointing this out. By including simplified building polygons in Figure 1, we aimed to represent the locations of larger built-up clusters. The simplified built-up cluster polygons was based on the detailed land-use classification provided by the Slovenian Ministry of Agriculture, Forestry and Food (MKGP). Details on the data source are provided in Table 2.
We have decided to remove the building polygons from new Figure 1, since we encountered the problem with readability of figure when adding inundation polygons to Figure 1. Also, the build-up areas are shown also in Figure 3 (lower map) where a clear acknowledgement of land use data will be provided.
- please add more references to past flooding events, as the second part of Sec. 2.1 remains a bit too vague in the present version
Detailed comment #10 reply: We will add references to second part of section 2.1 to improve the presentation of past flood events in the study area.
- would it be good to also have reference years in Table 1, to better understand what the baseline of the model is
Detailed comment #11 reply: Thank you for this comment. We will add reference years of the national datasets considered in the hydrodynamical model development.
- what is the source of Figure 3, and how was the clustering made? In my opinion, lines 120-130 should be expanded, providing more details that ensure the reproducibility of the study
Detailed comment #12 reply: We will add a reference to the national land-use database (MKGP, 2026), from which the land-use classes shown in Figure 3 were obtained. We will provide additional information on the clustering of the land-use classes. The main aim of preparing Figure 3 (lower map) with clustered land-use classes was to more clearly represent the fragmented patterns of built-up areas and the general extent of agricultural land-use classes along the studied Vipava River section. We will rewrite the section in which the land-use characteristics of the study area are presented.
- given that you used HecRas (Sec. 2.2.2), this model should be described in the Introduction, pointing out its pros and cons with respect to the specific case study. HecRas has some limitations that should be acknowledged, and the fact that it was already used in the study area does not suffice to confirm that it is a good choice
Detailed comment #13 reply: We will follow the reviewer’s suggestion and introduce the HEC-RAS hydrodynamic model already in the Introduction. We agree that HEC-RAS has some limitations; however, it is widely used software that has been relatively successfully applied in many studies. We would also like to point out that other hydrodynamic models have been used in the past to study flood conditions along the studied Vipava River section (e.g. FLO-2D, MIKE FLOOD). Based on different applications, we find it extremely difficult to clearly identify one hydrodynamic model as superior to others. However, we will extend the description of the HEC-RAS hydrodynamic model settings to more clearly present the potential limitations of the performed hydrodynamic simulations.
- line 144: here you said that roughness was calibrated against water levels. Would it be possible to see such a calibration, and eventually a validation against flooding events? I understand you provided some references, but readers should also be able to follow you without looking at past studies. You can add calibration/validation details as supplementary material.
Detailed comment #14 reply: Thank you for this comment. Following the reviewer’s suggestion, we will provide the observed combined flood extent during the more recent flood events in 2010 and 2012 as supplementary material. The observed flood extent was used for calibration of the hydrodynamic model simulation. Considerable differences in the flood peak return periods were reported for specific water stations along Vipava River. The peak discharge return periods of the observed flood events along the studied Vipava River reach were assessed to locally range between 50 and 100 years. For few other flood events with lower return periods, only water levels at specific locations are available. These events were used to calibrate and validate the channel roughness characteristics of the Vipava River.
- line 158: with the current development of IT infrastructures, the computational effort is not a limitation anymore. I suggest deleting this sentence. In addition, there are other free and/or commercial models that perform better than HecRas in terms of computational speed and efficiency (and this comment connects to the need of explaining why HecRas was used).
Detailed comment #15 reply: We agree with the reviewer that recent developments in IT infrastructure have considerably reduced computational limitations when performing numerous hydrodynamic simulations. However, we believe that performing numerous simulations with changing hydrodynamic settings remains a considerable challenge in many cases. We will rewrite this section to better address the points raised by the reviewer. As stated in the reply to Detailed comment #12, in our view, it is extremely difficult to clearly identify one hydrodynamic model as superior to others based on different criteria, such as computational speed, efficiency, numerical stability etc.
- from the description reported in Section 2.2.2, I can understand that simulations were done with clear water. Could you please confirm that no morphological changes were considered, and that this reflects the conditions of the study reach?
Detailed comment #16 reply: The reviewer is correct; the simulations were performed without considering sediment transport processes, and no potential hydromorphological changes were considered. We consider this assumption suitable for the studied Vipava River section, as only relatively limited and spatially constrained hydromorphological changes have been observed during the last few flood events.
- line 201: why a threshold of 0.01 m water depth? What’s the rationale behind it?
Detailed comment #17 reply: Thank you for this comment. Since several floodplain sections along the studied Vipava River section are wide and flat, we selected a relatively low threshold (0.01 m) to obtain a more detailed overview of the potential changes in inundation extent driven by the selected scenario ensembles. We are aware that selecting such a low threshold might raise questions about hydrodynamic model sensitivity. However, the general idea behind selecting the scenario ensembles was to better cover different uncertainty and sensitivity aspects that are reflected in changes in inundation extent.
Results and Discussion
- line 210: please add a reference to the first sentence.
Detailed comment #18 reply: Thank you for noting this, we will add relevant references.
- Figure 4: how where the flood hazard classes defined? I might have missed it.
Detailed comment #19 reply: Flood hazard classes were defined following the criteria presented in Table 4.
- line 230: this raises a question about the actual need of using statistical methods. I agree with your point of view, but I suggest deepening the discussion on this aspect, eventually looking at other studies.
Detailed comment #20 reply: Thank you for pointing this out. We will extend this section to better address the problem of assessing the design discharges in view of the observed flood peaks.
- Sections 3.2 and 3.3 need more comments, as roughness plays a major role in water levels rather than in spatial extent, as you also noticed. Do water levels play a role in the study area (e.g., evacuation routes, buildings)
Detailed comment #21 reply: Thank you for this comment. We will extend the comments in Sections 3.2 and 3.3 to better address the influence of roughness on water levels and the spatial extent of inundation. Following the reviewer’s suggestions, we will also extend the comments in Section 3.4 related to the impact of water levels on inundation characteristics in built-up areas.
- line 295: Louise Slater (she, so should be “her results”) looked at the contribution of a changing morphology on flood risk, while your model considers clear water, if I understood correctly. Could you please provide more comments on that? Moreover, there is ample recent literature on the influence of sediments and active bed on flood risk, and I suggest deepening the literature review if you wish to address this topic.
Detailed comment #22 reply: Thank you for noting our mistake; we apologize for that. As noted by the reviewer, we did not consider the impact of changed channel hydromorphology, but rather the impact of changed river channel hydraulic roughness, which was also one of the drivers of changed hydraulic capacity identified by Slater (2016). Following the reviewer’s suggestion, we will extend the discussion by adding references to support our discussion of the impact of successional changes in river channel roughness on inundation extent and inundation depth.
- would it be possible to have a clearer Figure 10, eventually using the same colour scale to help compare results?
Detailed comment #23 reply: We will make a new version of Figure 10 in order to make the presentation clearer. We will unify the colors scale of both graphs and increased text fonts.
- line 348-361: this remains a rather vague discussion. I suggest adding some clear, actionable steps to take advantage of flood mapping, also considering the potential use of the affected areas. Appropriate spatial planning should go beyond abandoning areas, and I would like to see more comments on this, also considering the current state of the art.
Detailed comment #24 reply: Thank you for these suggestions. We will enhance the discussion by following the reviewer’s suggestions to more clearly present the potential advantages of the flood maps shown in Figures 11 and 12. We will also add references to support the discussion of state-of-the-art approaches to spatial planning and the potential uses of the information provided by the weighted exceedance probability of inundation.
Conclusions
- line 382: I would use “changes” (or a similar word) instead of “deterioration”, as some changes in roughness could eventually reduce local flood hazard.
Detailed comment #25 reply: Thank you for this attentive comment. We will implement the suggested corrections (“deterioration” to “changes”).
- line 388: again, I do not see computational time as a limitation nowadays. It’s possible to address it using adequate models and IT infrastructures.
Detailed comment #26 reply: Generally, we agree with the reviewer’s opinion. However, as mentioned earlier (Detailed comment #14 reply), we believe that performing numerous simulations is, in many cases, still a considerable challenge. We decided to rewrite the sentence in the direction indicated by the reviewer.
Data availability
- I was not able to find the Zenodo dataset. As this could be my mistake, could you please help me with this?
Detailed comment #27 reply: We will check the link to the datased uploadad to Zenodo, it worked for us. We will do additional check of the link with the journal office.
Citation: https://doi.org/10.5194/egusphere-2026-2602-AC1 -
RC2: 'Comment on egusphere-2026-2602', Antonio Annis, 26 Jun 2026
reply
I have read the manuscript together with the RC1 report and the authors' reply. My concerns below are mainly about the stated novelty and about the specification of some methodological steps that are central to the conclusions but cannot, as written, be reproduced or fully interpreted.
Major comments
The RC1 has already asked for a clearer statement of novelty; I would make the request more specific. The comparison of hydrological versus hydraulic uncertainty in inundation mapping is well established (e.g. Merz & Thieken, 2005; Apel et al., 2008; Mosquera-Machado & Ahmad, 2007; Dimitriadis et al., 2016; Annis et al., 2020). As written, the manuscript reads as a careful site-specific application rather than a methodological advance. Please state explicitly in the Introduction what is new relative to this literature — e.g. the "boundary scenario ensemble" construction, the weighted exceedance-probability aggregation, or the joint treatment of FFA confidence intervals and climate scenarios.
Table 1 reports the flood-frequency analysis at "daily" resolution, and the text (l. 109) refers to "annual discharge peaks". For a catchment with the torrential tributary behaviour and karst response you describe, and at this reach scale, the time of concentration is plausibly of the order of hours, so annual maxima of daily-mean discharge can substantially underestimate the instantaneous flood peak. Please clarify whether the FFA target variable is the instantaneous annual maximum or the daily-mean annual maximum and, if only daily data were available, whether a peak/daily-mean adjustment was applied.
Three candidate distributions are mentioned (Pearson III, Log-Pearson III, GEV; l. 109), but the manuscript does not state which distribution was adopted for the design values and the confidence intervals, nor does it report any goodness-of-fit assessment. Since the S1 rests entirely on the 10% and 90% confidence intervals, which distribution was selected and on what basis? Have you done the goodness-of-fit evidence, and how the confidence intervals were estimated (parameter/sampling uncertainty, bootstrap, etc.)? At present this is delegated to a thesis written in Slovenian (Piry, 2020), which is not sufficient for reproducibility. Please include the essential FFA results in the manuscript or as supplementary material — at minimum the selected distribution, fitted parameters, design quantiles with confidence intervals, and a fit diagnostic.
Section 2.2.3 mentions the Morris screening method, but the manuscript does not report the information needed to interpret or reproduce it: the number of trajectories, the number of levels, the parameter ranges sampled, and the resulting total number of model runs. This matters because Table 3 describes only eight boundary scenarios constructed in a one-factor-at-a-time manner, whereas a Morris analysis requires randomized trajectories of runs each across the parameter space. It is therefore unclear whether the Morris indices in Fig. 10 were computed from the eight listed runs (in which case they are not a proper Morris sample) or from an additional, undocumented set of simulations. Please clarify it.
The "weighted exceedance probability of inundation" is one of the manusript's central outputs, but it is not defined precisely enough to be reproduced or interpreted. As described, it combines binary inundation indicators from simulations that span different return periods and different epistemic choices (FFA confidence intervals, floodplain roughness, channel roughness), each weighted by an "annual exceedance probability". Please provide the governing equation: which simulations enter the aggregation, the weight assigned to each, and the normalization. Moreover, the return period is an aleatory (frequency) quantity, whereas the roughness scenarios and the FFA confidence-interval bounds represent epistemic uncertainty. I 'd ask the authors either to separate the weighting across return periods from the epistemic spread across scenario members)or to justify the chosen aggregation and state clearly what the resulting map represents.
The RCP-driven peak-increase scenarios are currently treated somewhat separately from the main sensitivity framework: they appear in the narrative comparison with the FFA confidence intervals (Sect. 3.1) and in Fig. 12, but not in the comparative sensitivity analysis of Fig. 10. Since the climate signal is a scaling of the peak-discharge factor, it could be incorporated directly into the same comparative framework — for example as an additional level/axis in Fig. 10, or in a single figure that ranks FFA confidence-interval width, channel-roughness change, floodplain roughness, and the RCP-driven increase on the same footing. This would let the reader judge how much the climate-change contribution weighs relative to the other sources, and it would directly support the paper's claim that the FFA uncertainty already "covers" the RCP 2.6/4.5 ranges.
Specific comments
- Figure 1. The elevation colour scale used in the left (overview) panel does not match the colour bar/legend shown for the right panel. Please harmonize the two.
- The floodplain-roughness effect on inundation extent (≈4–6%) is of the same order as the reported validation uncertainty (mean 6%, s.d. 3%; l. 154–156), which you partly acknowledge at l. 265. Please state this explicitly where the S2 results are first presented.
- Scenario ensemble S3 compares the 1970s design channel roughness (n = 0.035) with the current calibrated This is a comparison between two temporal states of the channel (a change scenario) rather than a parameter "sensitivity" in the usual sense. Consider adjusting the terminology so that the distinction between epistemic sensitivity (S2) and physical/temporal change (S3) is clear to the reader.
References
Apel, H., Merz, B., & Thieken, A. H. (2008). Quantification of uncertainties in flood risk assessments. International Journal of River Basin Management, 6(2), 149-162.
Merz, B., & Thieken, A. H. (2005). Separating natural and epistemic uncertainty in flood frequency analysis. Journal of Hydrology, 309(1-4), 114-132.
Mosquera-Machado, S., & Ahmad, S. (2007). Flood hazard assessment of Atrato River in Colombia. Water resources management, 21(3), 591-609.
Dimitriadis, P., Tegos, A., Oikonomou, A., Pagana, V., Koukouvinos, A., Mamassis, N., ... & Efstratiadis, A. (2016). Comparative evaluation of 1D and quasi-2D hydraulic models based on benchmark and real-world applications for uncertainty assessment in flood mapping. Journal of Hydrology, 534, 478-492.
Citation: https://doi.org/10.5194/egusphere-2026-2602-RC2
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- 1
General comments:
The work presents an interesting approach on flood mapping, which includes the analysis of hydrological uncertainty and model sensitivity while developing flood hazard maps. The case study is a reach of the Vipava River, a transboundary river flowing from Slovenia to Italy.
The goal of the study is proper and timely, but, in my opinion, the manuscript should be significantly better developed before publication, starting from a more explicit stressing of the novelty, and how this specific work goes beyond the current state of the art. Indeed, the need for considering uncertainty in flood mapping is not a new topic, and there are examples in the literature, which should be addressed in the Introduction to point out knowledge gaps.
The methodological part could be further expanded, also following my detailed comments below, to better guide readers through all the steps needed to produce the maps you show, and also what is needed to evaluate them from a quantitative point of view.
I strongly advise separating the Results from the Discussion, expanding the latter section to better highlight the novelty of the study and what other scholars and stakeholders can learn from your application. Likely in the Introduction, a more in-depth review of the state of the art would support your statements in a more thorough manner, moving from reporting results to actually discussing them from a critical point of view.
Detailed comments:
Introduction
- please avoid excessive use of AI-generated text. The first line of the Introduction could be found in many other similar studies, always with the same phrasing.
- there are no such things as “natural disasters”. As pointed out by UNDRR (https://www.undrr.org/our-impact/campaigns/no-natural-disasters), we have to change the way we communicate, and acknowledge that nature is not causing disasters, while is the presence of humans plays the major role.
- line 27: how can mapping reduce hazard? The link is not fully clear, as, usually, mapping is a good way to reduce risks. Please rephrase this paragraph.
- lines 40-43: please double-check the language. I guess it should read “This…”. But also in this case, the language could be improved
- line 54: what critical scenarios and selected how? It would be good to have more details already in the Introduction, also to better catch the transferability of results/approach
- line 59: additional information on how this roughness is calculated would help in understanding the novelty of the study. For example, have you considered time-changing roughness during the simulation or just values depending on the land use? Even if addressed later in the study, adding some comments in the Introduction would help readers better follow you.
Methods
- please change the title to a more general “Materials and Methods”, as you are also presenting the input data
- line 77-78: where can readers see the flood inundation extent? Can you provide some additional references?
- Figure 1: what is the source of the buildings polygons? I suggest acknowledging data sources more properly.
- please add more references to past flooding events, as the second part of Sec. 2.1 remains a bit too vague in the present version
- would it be good to also have reference years in Table 1, to better understand what the baseline of the model is
- what is the source of Figure 3, and how was the clustering made? In my opinion, lines 120-130 should be expanded, providing more details that ensure the reproducibility of the study
- given that you used HecRas (Sec. 2.2.2), this model should be described in the Introduction, pointing out its pros and cons with respect to the specific case study. HecRas has some limitations that should be acknowledged, and the fact that it was already used in the study area does not suffice to confirm that it is a good choice
- line 144: here you said that roughness was calibrated against water levels. Would it be possible to see such a calibration, and eventually a validation against flooding events? I understand you provided some references, but readers should also be able to follow you without looking at past studies. You can add calibration/validation details as supplementary material.
- line 158: with the current development of IT infrastructures, the computational effort is not a limitation anymore. I suggest deleting this sentence. In addition, there are other free and/or commercial models that perform better than HecRas in terms of computational speed and efficiency (and this comment connects to the need of explaining why HecRas was used).
- from the description reported in Section 2.2.2, I can understand that simulations were done with clear water. Could you please confirm that no morphological changes were considered, and that this reflects the conditions of the study reach?
- line 201: why a threshold of 0.01 m water depth? What’s the rationale behind it?
Results and Discussion
- line 210: please add a reference to the first sentence.
- Figure 4: how where the flood hazard classes defined? I might have missed it.
- line 230: this raises a question about the actual need of using statistical methods. I agree with your point of view, but I suggest deepening the discussion on this aspect, eventually looking at other studies.
- Sections 3.2 and 3.3 need more comments, as roughness plays a major role in water levels rather than in spatial extent, as you also noticed. Do water levels play a role in the study area (e.g., evacuation routes, buildings)
- line 295: Louise Slater (she, so should be “her results”) looked at the contribution of a changing morphology on flood risk, while your model considers clear water, if I understood correctly. Could you please provide more comments on that? Moreover, there is ample recent literature on the influence of sediments and active bed on flood risk, and I suggest deepening the literature review if you wish to address this topic.
- would it be possible to have a clearer Figure 10, eventually using the same colour scale to help compare results?
- line 348-361: this remains a rather vague discussion. I suggest adding some clear, actionable steps to take advantage of flood mapping, also considering the potential use of the affected areas. Appropriate spatial planning should go beyond abandoning areas, and I would like to see more comments on this, also considering the current state of the art.
Conclusions
- line 382: I would use “changes” (or a similar word) instead of “deterioration”, as some changes in roughness could eventually reduce local flood hazard.
- line 388: again, I do not see computational time as a limitation nowadays. It’s possible to address it using adequate models and IT infrastructures.
Data availability
- I was not able to find the Zenodo dataset. As this could be my mistake, could you please help me with this?