Flood Risk Assessment Under Climate Change Scenarios in the Wadi Ibrahim Watershed

Round 1

Reviewer 1 Report (Previous Reviewer 1)

Comments and Suggestions for Authors

In my earlier review, I provided three key suggestions intended to improve the scientific quality and applicability of the manuscript. However, rather than addressing these points through substantive revisions, the authors have chosen to frame them solely as study limitations. This response is unsatisfactory, especially considering that the data and methods suggested are readily available and could have been incorporated to strengthen the analysis.

1. Inclusion of RCP 2.6: The authors dismiss RCP 2.6 on the basis that it is an "optimistic" scenario. However, given that current climate negotiations and mitigation efforts are still aimed at limiting warming to 1.5°C above pre-industrial levels, RCP 2.6 remains a scientifically relevant and policy-informative pathway. Its inclusion would provide a more comprehensive view of potential climate futures, especially under successful global mitigation strategies. When the data is available, simply categorizing it as a limitation without attempting integration misses a valuable opportunity to broaden the scope of the analysis.
2. Use of CHIRPS Data: The manuscript acknowledges the limited spatial and temporal coverage of station-based rainfall data, yet declines to use high-resolution alternatives like the CHIRPS dataset. This dataset is not only publicly accessible but also widely validated for hydrological modeling, especially in regions with sparse station coverage. Including CHIRPS would have significantly enhanced the robustness and spatial consistency of the flood risk projections. Labeling the use of limited station data as a constraint, despite viable solutions being suggested, is not a sufficient justification.
3. Contextual Relevance of Flood Risk in Arid Environments: While the authors briefly discuss land use and urbanization in the limitations, they have not adequately addressed the real-world significance of flood risks in an arid catchment like Wadi Ibrahim. A clearer explanation of how the findings inform flood management, urban planning, and climate adaptation in such a setting is still needed to underscore the study's practical importance.

So, framing all previously raised issues as limitations, without attempting any meaningful incorporation of the suggested data or analyses, undermines the potential impact and quality of the manuscript. I strongly recommend that the authors revise the manuscript by incorporating these elements rather than deferring them entirely to future work.

Three minor comments are there in the PDF file attached (kindly rectify them too)

Comments for author File: Comments.pdf

Author Response

Reviewer 1:
Overview:
In my earlier review, I provided three key suggestions intended to improve the scientific quality and applicability of the manuscript. However, rather than addressing these points through substantive revisions, the authors have chosen to frame them solely as study limitations. This response is unsatisfactory, especially considering that the data and methods suggested are readily available and could have been incorporated to strengthen the analysis.

1. Inclusion of RCP 2.6: The authors dismiss RCP 2.6 on the basis that it is an "optimistic" scenario. However, given that current climate negotiations and mitigation efforts are still aimed at limiting warming to 1.5°C above pre-industrial levels, RCP 2.6 remains a scientifically relevant and policy-informative pathway. Its inclusion would provide a more comprehensive view of potential climate futures, especially under successful global mitigation strategies. When the data is available, simply categorizing it as a limitation without attempting integration misses a valuable opportunity to broaden the scope of the analysis.

Response:

Thank you for this valuable suggestion. We have now included the RCP 2.6 scenario in this study, as recommended, to broaden the scope of the analysis and provide a more comprehensive view of potential climate futures. The revisions related to RCP 2.6 are highlighted in yellow.

 

2. Use of CHIRPS Data: The manuscript acknowledges the limited spatial and temporal coverage of station-based rainfall data, yet declines to use high-resolution alternatives like the CHIRPS dataset. This dataset is not only publicly accessible but also widely validated for hydrological modeling, especially in regions with sparse station coverage. Including CHIRPS would have significantly enhanced the robustness and spatial consistency of the flood risk projections. Labeling the use of limited station data as a constraint, despite viable solutions being suggested, is not a sufficient justification.

Response:

Thank you for this suggestion. Incorporating CHIRPS data would require substantial changes to the methodology and overall framework of this study. Therefore, this study remains focused on rainfall data obtained from gauge stations to maintain consistency with the original data sources and objectives.

3. Contextual Relevance of Flood Risk in Arid Environments: While the authors briefly discuss land use and urbanization in the limitations, they have not adequately addressed the real-world significance of flood risks in an arid catchment like Wadi Ibrahim. A clearer explanation of how the findings inform flood management, urban planning, and climate adaptation in such a setting is still needed to underscore the study's practical importance.

Response:

We thank the reviewer for this insightful comment. We have now included a discussion of historical flood events in Wadi Ibrahim to provide context on past flood frequency and severity. Furthermore, we have elaborated on the implications of our findings for flood risk management in an arid environment, emphasizing the importance of understanding extreme flood risks despite low average rainfall. This explanation has been added into the Discussion section as a new subsection titled “5.2 Practical Implications of Flood Risk in an Arid Environment.”

 

Three minor comments

1. In Table 3, current average values of rainfall for different stations should also be mentioned, like make another column before different return period

Response:

The Table 3 has been revised. Now it contains average rainfall for different stations.

 

2. In Figure 9, why there is just one value on spatial plot as shown in Table 3

Response:

Figure 9 has been revised. The spatial distribution for the future scenarios now follows a pattern consistent with the current scenario. Each map presents four rainfall classes to illustrate the spatial variability more clearly.

3. Revise the place about Rain on Grid and revise the Figure 11!

Response:

Kindly recheck please. The Rain-on-Grid location is described in the Methodology section, specifically under Section 3.2, and not in the Discussion or Results. Additionally, Figure 11 has been removed, as its original purpose was to illustrate the interaction of water flow with flat and elevated areas. After further review, it was determined that this figure is not essential to the core findings.

 

 

Reviewer 2 Report (Previous Reviewer 2)

Comments and Suggestions for Authors

The author has made some of the suggested revisions; however, there are still several fundamental issues that have not been addressed. Hopefully, the author would not mind completing these remaining deficiencies. The complete comments (written in red) are given in the attached file. Thank you.

Comments for author File: Comments.pdf

Author Response

Reviewer 2:

1. Will that be possible for the authors to include recent data? If there is rainfall stations available, please inform the locations. Do not you think that it is necessary to have those data? By the way there is no information on the rainy days presented in Figure 2.

Response:

Thank you for your comment. Rainfall stations are available, and their locations are shown in Figure 6. The average rainfall values, along with different return periods, are provided in Table 3. Figure 2 presents additional information obtained from the WMO website for comparison purposes. The information on rainy days was removed as it was considered supplementary and not critical to the study’s objectives.

 

2. Please inform in more detail why the data length of some rainfall stations are ended by 2022 even for new rainfall stations i.e Mk139?

Response:

Thank you for your comment.

The rainfall data used in this study were obtained from the official records of the National Center for Meteorology (NCM) and Saudi Geological Survey (SGS). At the time of data collection, 2022 was the most recent year with complete, validated, and publicly available data for most stations. Data for 2023 and beyond were not yet released or were still undergoing processing and quality control. In addition, some stations may have discontinued operations or experienced data interruptions due to maintenance, equipment failure, or administrative decisions, resulting in an earlier end to their data series.

3. Why these return period were selected, please explain so that can be well understood by readers. Is there any reference used to employ these return periods?
   
   

Response:

The selection of 50, 100, and 200 years return periods in flood risk assessments is based on their practical relevance to infrastructure design, regulatory standards, and risk management planning. These return periods represent different levels of risk, corresponding to annual exceedance probabilities of 2%, 1%, and 0.5%, respectively.

• The 50 year return period is commonly used for designing urban stormwater systems
• The 100 year return period is a widely accepted standard for floodplain management, and
• The 200 year return period is used for infrastructure where rare events must be considered due to the potential for high damage or loss of life.

One reference for this return period is the study by Azeez et al. (2020), which found that the rainfall depth corresponded to a return period of 50 to 100 years, while the hydrograph estimated using a rainfall–runoff model corresponded to a higher return period between 100 and 200 years (Azeez, O., Elfeki, A., Kamis, A.S. et al., Dam break analysis and flood disaster simulation in arid urban environment: the Um Al-Khair dam case study, Jeddah, Saudi Arabia, Natural Hazards, 100, 995–1011, 2020. https://doi.org/10.1007/s11069-019-03836-5)

 

4. Table 3 showed how crucial to evaluate the RCPs for early years i.e 2006-2022. Thus, it is very important that the Authors can explain how RCPs capture the present condition for both mean and extreme rainfalls.

Response:

Thank you for this comment.

As shown in Table 3 and Figure 8, the RCP projections exhibit variability compared to the observed data during the historical period (2006–2022). In some years, RCP models overestimate or underestimate rainfall events. For example, in 2008 and 2016, RCP 4.5 projected much higher rainfall (204.58 mm and 203.96 mm) compared to the observed 86 mm and 17 mm, indicating a tendency of overestimation for extreme events. Conversely, in other years such as 2011 or 2012, the RCPs underestimated rainfall compared to observations. The differences between observed and projected rainfall are expected due to the inherent uncertainty in climate models at local scales. RCP models are designed primarily for future climate projections rather than exact replication of past events; however, they still capture the general trends of increased rainfall under higher emission scenarios (as seen from increasing averages across RCP 2.6, 4.5, and 8.5 in Table 3).

 

5. Please check on the water surface, it must be horizontal (Figure 12).

Response:

Thank you for your comment. Could you kindly clarify which aspect of the water surface is expected to be horizontal? This will help us address it correctly.

 

Reviewer 3 Report (Previous Reviewer 3)

Comments and Suggestions for Authors

I previously gave the comments below.
Apparently, the authors did not carefully consider those comments to improve the anaysis and paper.
Please consider them and justify your analysis, which I believe the authors need new analysis.

I attach those comments here again with some new explanations:
#1
Since the authors use the rainfall distribution as the input to the hydrologic model, considering the rainfall distribution is important. In this kind of study, one common way is to use the historical rainfall distribution and change the rainfall magnitude by the ratio of future projection-historical, while maintaining the spatial distribution. Of course, such method also has limitations, but at least it can consider the spatial variation of the rainfall. The use of homogeneous distribution, I believe, is an unacceptable approximation. The authors are encouraged to perform the analysis based on the above.
The authors' answer: 
We agree that spatial rainfall distribution is important for hydrologic modeling. In our study, the observed rainfall data were applied with spatial distribution based on gauge stations. However, for future climate change scenarios, station-based spatial data were not available, and therefore a homogeneous distribution was applied as an approximation. We acknowledge the limitations of this approach and have added this point to the limitations section.
My comment on this:
Yes, the data for the future is not available. But the homogeneous distribution is too strong approximation that I cannot accept. We often assume the same/similar pattern of distribution for the furure. This way also has a limitation but at least we can consider the rainfall spatial variability which is really critical for your analysis. I recommend the authors to perform the analysis in a such way and see the impact of the homogeneous approximation.

#2
Figure 10: Your plots apparently do not follow Gumbel distribution for large return periods. The downward convex distribution is most likely to follow the frechet distribution. As the estimation of the return value is totally based on the distribution, I suggest the authors to carefully consider the distribution and perform the analysis.
The authors' answer:
Thank you for your observation. In our study, we initially applied the Gumbel distribution, as described in Equations (1) to (3), which assumes a light-tailed behaviour for extreme events.
My comment on this:
You technically did not answer anything to my comment. My suggestion was to JUSTIFY the use of Gumbel when it seems not to follow Gumbel. 

Author Response

Reviewer 3:
I attach those comments here again with some new explanations:
#1
Since the authors use the rainfall distribution as the input to the hydrologic model, considering the rainfall distribution is important. In this kind of study, one common way is to use the historical rainfall distribution and change the rainfall magnitude by the ratio of future projection-historical, while maintaining the spatial distribution. Of course, such method also has limitations, but at least it can consider the spatial variation of the rainfall. The use of homogeneous distribution, I believe, is an unacceptable approximation. The authors are encouraged to perform the analysis based on the above.
The authors' answer: 
We agree that spatial rainfall distribution is important for hydrologic modeling. In our study, the observed rainfall data were applied with spatial distribution based on gauge stations. However, for future climate change scenarios, station-based spatial data were not available, and therefore a homogeneous distribution was applied as an approximation. We acknowledge the limitations of this approach and have added this point to the limitations section.
My comment on this:
Yes, the data for the future is not available. But the homogeneous distribution is too strong approximation that I cannot accept. We often assume the same/similar pattern of distribution for the furure. This way also has a limitation but at least we can consider the rainfall spatial variability which is really critical for your analysis. I recommend the authors to perform the analysis in a such way and see the impact of the homogeneous approximation.

Response:

Thank you for your valuable feedback. To address this, we have revised our approach for the future scenarios. Instead of applying a homogeneous distribution, we have now assumed a similar spatial pattern to the current scenario, maintaining the spatial variability seen in the observed rainfall data. Each future scenario map (Figure 9) now presents four distinct rainfall classes, clearly illustrating the spatial distribution and variability. We appreciate your suggestion and believe this update strengthens the robustness of the analysis.

 

#2
Figure 10: Your plots apparently do not follow Gumbel distribution for large return periods. The downward convex distribution is most likely to follow the frechet distribution. As the estimation of the return value is totally based on the distribution, I suggest the authors to carefully consider the distribution and perform the analysis.
The authors' answer:
Thank you for your observation. In our study, we initially applied the Gumbel distribution, as described in Equations (1) to (3), which assumes a light-tailed behaviour for extreme events.
My comment on this:
You technically did not answer anything to my comment. My suggestion was to JUSTIFY the use of Gumbel when it seems not to follow Gumbel. 

 

Response:

Thank you for your comment. We acknowledge some deviation from the Gumbel distribution, particularly at higher return periods. However, the Gumbel distribution was chosen for its widespread use in hydrological frequency analysis, especially for flood estimation, and its simplicity and interpretability. Previous studies in the same region show that the Gumbel distribution provides a reliable method for estimating extreme events, demonstrating the best goodness of fit based on the Kolmogorov–Smirnov (K-S) test, with lower error compared to six other distributions.

Round 2

Reviewer 1 Report (Previous Reviewer 1)

Comments and Suggestions for Authors

The authors have made substantial revisions. The manuscript may be considered for acceptance pending the editor’s final evaluation.

Reviewer 3 Report (Previous Reviewer 3)

Comments and Suggestions for Authors

I appreciate the authors addressing my comments and/or providing the answers to my comments. 

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Manuscript Title: “Flood Risk Assessment under Climate Change Scenarios in the Wadi Ibrahim Watershed" (Manuscript ID: hydrology-3561921)

 

Overview:
Thank you for considering me as a reviewer for the study titled “Flood Risk Assessment under Climate Change Scenarios in the Wadi Ibrahim Watershed.” I appreciate the authors' efforts in evaluating the impact of climate change on flood hazards in the Wadi Ibrahim watershed. The manuscript presents important insights into future flood risks using CORDEX Regional Climate Model projections under RCP 4.5 and RCP 8.5 scenarios, combined with 2D HEC-RAS Rain-on-Grid (RoG) modeling. The findings highlight the increasing flood risk under climate change and emphasize the need for mitigation strategies. The manuscript is well-structured, and the flood risk maps provide valuable visualizations of the projected changes. However, there are several key issues that require clarification and improvement, particularly regarding data consistency, past flood events, and the practical significance of the study in the real-world context. Additionally, the methodological approach and result interpretations could be further refined. Given these concerns, I recommend a to revise and submit again the fresh manuscript.

Technical Comments:

Major:

1. The study considers only RCP 4.5 and RCP 8.5, but given that we are already approaching 1.5°C above pre-industrial levels, RCP 2.6 could provide a more realistic representation of near-term climate trajectories under strong mitigation efforts. Could the authors clarify why RCP 2.6 was not included in the analysis? Including it could offer valuable insights into potential climate outcomes under stringent mitigation scenarios. (lines 12-13)
2. The rainfall data used in this study appears to be limited in both spatial and temporal coverage, with significant inconsistencies in the time scales across different stations. Given these limitations, have the authors considered using alternative datasets, such as the CHIRPS rainfall dataset, which provides high-resolution, long-term precipitation data? Incorporating CHIRPS could improve the robustness and consistency of the analysis (lines 155-162).
3. The study provides valuable insights into future flood risks; however, it would be beneficial to include a discussion on past flood events in the Wadi Ibrahim watershed. How many flash floods have historically occurred in this region, and how is their frequency expected to change under future climate scenarios? Additionally, given that the study area is classified as an arid catchment with low precipitation, frequent droughts, and limited water resources, could the authors elaborate on the practical significance of this study in a real-world context? Specifically, how do the findings contribute to flood risk management and mitigation strategies in such an environment?

Minor

4. Please provide relevant references for the content in lines 35-37.
5. In Figure 1, the photos showing flood-affected areas are not aligned with the figure title. Please revise the images to ensure consistency with the caption.
6. In Table 1, consider replacing "Low" and "High" elevation with "Lowest" and "Highest" elevation for clarity and precision.
7. What is the source of climate data in figure 2?
8. For all figures displaying multiple graphs and images, please differentiate them using labels such as (A), (B), etc., to improve clarity and enhance readability.
9. In Figures 11 and 12, the legends are unclear regarding which part of the study area is being represented. Please provide clearer explanations in the legends.
10. Figure 6 does not match the text. The oldest station, J114, uses data from 1967 to 2022, but the graph does not show data for all years. Additionally, why are data from 2023 and 2024 not included for this station? Please clarify.
11. Line 144: Please provide justification for the use of the Curve Number method in the study and explain how it contributes to the overall analysis.
12. In several places, the phrase "numerous studies" is used. It would be beneficial to provide multiple references to substantiate this claim.
13. Six minor comments are there in the PDF file attached (kindly rectify them too)

These revisions will enhance the clarity, accuracy, and overall quality of the manuscript.

Comments for author File: Comments.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Generally, the manuscript explains how the flood will impact on Wadi Ibrahim watershed in the future under some climate change scenarios. From what has been written, a massive work has been conducted by the Authors. However, there are some substantial points that should be further considered by the Authors:

1. The Authors are recommended to highlight the novelty of this study.
2. Since this study focused only on the inundation depth, it is necessary to clearly state the flood risk defined by the Authors.
3. Figure 1 shows some photos of inundation but it is not clear where the location are.
4. In addition to the estimation of CN, it will be very helpful if the Authors can provide information on the the land use or land cover of the watershed.
5. Please inform in more detail why the data length of some rainfall stations are ended by 2022 even for the new rainfall station i.e Mk139.
6. Is there any significant difference between the rainfall data observed from 2019 to 2022 compared to what were showed in Figure 2? Please also explain the change of precipitation pattern, duration, and frequency based on the available data.
7. Please do plot both RCPs that available from 2006-2022 in Figure 8 so that the readers can understand how it looks compared to the observed one. Table 3 showed how crucial to evaluate the RCPs for early years i.e. 2006-2022. Thus, it is very important that the Authors can explain how RCPs
   capture the present condition for both mean and extreme rainfalls.
8. Please explain the result of bias correction obtained in this study.
9. Recent studies showed that GEV better captures climate extremes, but Gumbel remains in older guidelines. Please provide reason why Gumbel distribution was selected in this study.
10. Please revise the water surface in Figure 12.
11. Worse condition may also occur as result of land use change, should Authors include this issue as limitation of this study?
12. How the findings provide valuable insights into early flood warnings, evacuation strategies, and flood management should also be emphasized in the conclusions.
13. It is strongly recommended the Authors to include more relevant recent research articles.

Comments for author File: Comments.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Though the study follows the typical framework and provides useful information, I found some technical issues need to be resolved.

Please find my comments below:

 

Liness 44-50:

Impacts on climate change on extreme rainfall are complex. I believe referring to more studies and discussing such complex effects will support the authors’ understandings of such complex changes and improve the reliability of the paper. The examples include:

• Hiraga, Y., Tahara, R., & Meza, J. (2025). A methodology to estimate Probable Maximum Precipitation (PMP) under climate change using a numerical weather model. Journal of Hydrology, 652, 132659. https://doi.org/10.1016/j.jhydrol.2024.132659
• Moradian, S., Gharbia, S., Torabi Haghighi, A., & Olbert, I. A. (2025). Modelling extreme precipitation projections under the effects of climate change: case study of the Caspian Sea. International Journal of Water Resources Development, 41(1), 57-77.　https://doi.org/10.1080/07900627.2024.2400505

 

Figure 9:

Since the authors use the rainfall distribution as the input to the hydrologic model, considering the rainfall distribution is important.

In this kind of study, one common way is to use the historical rainfall distribution and change the rainfall magnitude by the ratio of future projection-historical, while maintaining the spatial distribution. Of course, such method also has limitations, but at least it can consider the spatial variation of the rainfall. The use of homogeneous distribution, I believe, is an unacceptable approximation. The authors are encouraged to perform the analysis based on the above.

 

Figure 10:

Your plots apparently do not follow Gumbel distribution for large return periods. The downward convex distribution is most likely to follow the frechet distribution. As the estimation of the return value is totally based on the distribution, I suggest the authors to carefully consider the distribution and perform the analysis.