| 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.
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?