Flood Inundation Mapping Using the Google Earth Engine and HEC-RAS Under Land Use/Land Cover and Climate Changes in the Gumara Watershed, Upper Blue Nile Basin, Ethiopia

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have presented a manuscript on flood inundation mapping in the Gumara watershed using HEC-RAS, which was calibrated with the 2019 flood extent. Since ground data for the 2019 flood was not available, Sentinel-1 SAR data was used for flood extent estimation via Google Earth Engine (GEE). After calibration, the HEC-RAS model was applied to generate flood hazard maps and estimate flood inundation for both the near-future and far-future scenarios.

Major comments:

1. There is a lack of explanation regarding how the threshold for classifying the difference image into flooded and non-flooded pixels was determined.

2.  

   There is no clarity on what criteria were used to identify isolated pixels. Since this flood map serves as a reference for calibrating the HEC-RAS model, it should be as close as possible to actual ground conditions.

3.  

   Manning's "n" values were adjusted iteratively during the calibration phase, but the manuscript does not provide details on the step size used for each iteration. Additionally, three flood extents were used for model calibration, yet the methodology for selecting the best "n" values among them is unclear. Furthermore, a flow multiplier was applied without sufficient explanation. Given that model calibration is a central focus of this manuscript, this section should be explained in detail.

4.  

   The manuscript does not clarify why the calibrated "n" values for settlements are lower than those for the river channel. Is this due to extensive vegetation in the river channel, or is there another reason?

5. There is a serious lack of validation data. Since more than five years have passed since the 2019 flood, was any ground data available for comparison with both the original flood extent simulated by HEC-RAS and the calibrated flood extent using Sentinel-1 SAR data? However, if no ground validation data is available, the accuracy of the simulation could still be assessed using a simulated flood with a 5-year return period.
6. The conclusion should not merely be a summary, as it is in the current manuscript. Instead, it should highlight the key findings, their significance, and potential future research directions. Please rewrite it after adding the validation of your result and comparing the improvement of the pre-calibration against the after-calibration model. 

I have some other minor comments along with the above-mentioned comments and highlighted text in the attached manuscript pdf please follow them to submit the response.

Comments for author File: Comments.pdf

Comments on the Quality of English Language

Satisfactory!

Author Response

Thank you for reviewing our manuscript. We have carefully addressed all your suggestions, and the manuscript has been revised accordingly.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

The research presented in paper deals with the utilization of Google Earth Engine and HEC-RAS for flood inundation mapping under Land Use/Land Cover and Climate Changes – Case study in the Gumara Watershed, Upper Blue Nile Basin, Ethiopia.

The topic is very interesting because the very important phenomena have been investigated by utilizing free software which could be very useful for researchers all over the world. The importance of the topic is stressed by the fact that significant numbers of people are affected by increasing risks of flooding and that topic deserves any effort which could be made in order to predict, mitigate and/or prevent the devastating consequences of floods. What more authors state that “Floods are among the most frequent and devastating climate-related hazards, causing significant environmental and socioeconomic impacts.” This fact justifies the comprehensive approach in predicting the potentially flooded area and to taking proper and timely actions with goals to reduce risks for human lives and assets. Utilizing contemporary possibilities such as SAR and software tools are necessary conditions for forecasting the areas under the flood risk and, in that sense, the utilized methodology is acceptable.

Analyzing the structure of the paper it seems that the topic is explained and structured in an acceptable manner.

The overall methodological framework of the study is well explained by the figure 3.

The literature coverage is comprehensive including its contemporaneity. Also, this paper could be considered as a research continuation based on the paper [64] where the high flow extremes were analyzed.

Even though the applicability of proposed methodology authors stressed and some differences and potential challenges of proposed methodology.

In chapter 4.1.  it is stated: “The SAR-derived flood inundation maps in this study adequately delineated frequently affected areas, which is consistent with the findings of a previous study conducted by Melkamu et al. [42]. However, a slight difference in the magnitude of the overall extent of the flood was observed. This can be attributed to differences in the timing of the SAR image acquisition, the floodplain area considered, and the flood detection algorithm used.”

The differences in magnitude of the flood are explained by:

-          The timing of the SAR image acquisition

-          the floodplain area considered and

-          the flood detection algorithm used.

All mentioned sources of difference implicate that sensitivity analysis of the provided methodology should be provided which I could not find in the text. This fact implies that the proposed model has potential for further improvement, but I did not find the proposal for further research with aim for methodology improvement. Authors only propose further research in the direction “on the socioeconomic impacts of flooding and adaptive flood protection measures is also essential for enhancing resilience in flood-prone areas.”

In my opinion further research should be focused on the accuracy improvement of the model because models which are not at the adequate level of accuracy may cause wrong decisions and become the source of the additional risk.

Author Response

Thank you for reviewing our manuscript. We have carefully addressed all your suggestions, and the manuscript has been revised accordingly

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

see atttached file

Comments for author File: Comments.pdf

Comments on the Quality of English Language

No other comments

Author Response

Thank you for reviewing our manuscript. We have carefully addressed all your suggestions, and the manuscript has been revised accordingly

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Thank you very much for improving the manuscript according to our suggestions.

Comments on the Quality of English Language

I may not be adequately qualified to comment on the quality of the English language.

Reviewer 3 Report

Comments and Suggestions for Authors

Congratulations to the authors, as they have improved their manuscript and answered the raised questions. The paper is now ready to be published after solving the last remaining couple of formal issues:
1. at Row 455-456, you should write:
“An average bed slope of 0.0012 was used as the downstream boundary condition for the Gumara River, corresponding to uniform flow regime”.
2. at Row 457 you should replace "1785.5 m amsl was established" by "was set".

Author Response

Journal: remote sensing

Manuscript title: Flood Inundation Mapping Using the Google Earth Engine and HEC-RAS under Land Use/Land Cover and Climate Changes in the Gumara Watershed, Upper Blue Nile Basin, Ethiopia

Submission ID: remote sensing -3466093

Dear Editor,

Thank you for the opportunity to submit the revised version of our manuscript, “Flood Inundation Mapping Using the Google Earth Engine and HEC-RAS under Land Use/Land Cover and Climate Changes in the Gumara Watershed, Upper Blue Nile Basin, Ethiopia,” for publication in Remote Sensing Journal.

We sincerely appreciate the time and effort you have devoted to reviewing our work. We are also grateful for the insightful comments from the reviewers, which have been instrumental in improving the manuscript.

Below, please find a direct copy of the minor comments along with our response.

Minor comments

1. 1. at Row 455-456, you should write:

“An average bed slope of 0.0012 was used as the downstream boundary condition for the Gumara River, corresponding to uniform flow regime”.

Response #1: Thank you for your comment. We have revised the statement as per your suggestion (Rows 454-456).

2. at Row 457 you should replace "1785.5 m amsl was established" by "was set"..

Response #2: Thank you for your comment. The text has been corrected accordingly (row 457).