Know to Predict, Forecast to Warn: A Review of Flood Risk Prediction Tools

Round 1

Reviewer 1 Report

The following minor comment must be considered for improvement:

# Abstract: At the end of the Abstract, please briefly specify what is the gaps for future studies

# Tables 1 and 2: Please provide the proper references

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

1.     The manuscript presents a bibliometric analysis of flood prediction tools based on Scopus data (2017 – 2022), which is interesting. The subject addressed is within the scope of the journal.

2.     However, the manuscript, in its present form, contains several weaknesses. Appropriate revisions to the following points should be undertaken in order to justify recommendation for publication.

3.     Full names should be shown for all abbreviations in their first occurrence in texts. For example, BN in p.1, GIS in p.1, etc.

4.     For readers to quickly catch your contribution, it would be better to highlight major difficulties and challenges, and your original achievements to overcome them, in a clearer way in abstract and introduction.

5.     p.1 - the bibliometric analysis is adopted on flood prediction tools. What are other feasible alternatives? What are the advantages of adopting this approach over others in this case? How will this affect the results? The authors should provide more details on this.

6.     p.1 - a review and meta-analysis are adopted on research articles. What are other feasible alternatives? What are the advantages of adopting this approach over others in this case? How will this affect the results? The authors should provide more details on this.

7.     p.3 - three research questions are adopted as the focus of this study. What are the other feasible alternatives? What are the advantages of adopting these research questions over others in this case? How will this affect the results? More details should be furnished.

8.     p.3 - the Scopus database is adopted in this study. What are other feasible alternatives? What are the advantages of adopting this database over others in this case? How will this affect the results? The authors should provide more details on this.

9.     p.4 - the search strategy as shown in Figure 1 is adopted for this review study. What are other feasible alternatives? What are the advantages of adopting this strategy over others in this case? How will this affect the results? The authors should provide more details on this.

10.  p.8 - multiple correspondence analysis is adopted to conduct the analysis. What are the advantages of adopting this approach over others in this case? How will this affect the results? More details should be furnished.

11.  p.8 - K-means clustering is adopted to group related concepts together. What are the other feasible alternatives? What are the advantages of adopting this approach over others in this case? How will this affect the results? More details should be furnished.

12.  This is a review paper regarding flood prediction tools. What are the novelties that can be brought out by reviewing this specific topic?

13.  What are the major differences between this review and other earlier review papers on this topic?

14.  More critical analysis should be made to different modelling methods, with both advantages and disadvantages of each method explicitly exhibited.

15.  Some assumptions are stated in various sections. Justifications should be provided on these assumptions. Evaluation on how they will affect the results should be made.

16.  The discussion section in the present form is relatively weak and should be strengthened with more details and justifications.

17.  Moreover, the manuscript could be substantially improved by relying and citing more on recent literature about contemporary real-life case studies of soft computing techniques on flood prediction such as the following. Discussions about result comparison and/or incorporation of those concepts in your works are encouraged:

●          Fu, M.L., et al., “Deep Learning Data-Intelligence Model Based on Adjusted Forecasting Window Scale: Application in Daily Streamflow Simulation IEEE ACCESS 8: 32632-32651 2020.

●          Kaya, C.M., et al., “Predicting flood plain inundation for natural channels having no upstream gauged stations,” Journal of Water and Climate Change 10 (2): 360-372 2019.

●          Mosavi, A., et al., “Flood Prediction Using Machine Learning Models: Literature Review,” Water 10 (11): article no. 1536 2018.

18.  Some inconsistencies and minor errors that needed attention are:

●          Replace “…the last five (5) years (2017 – 2019)…” with “…the last five (5) years (2017 – 2022)…” in line 19 of p.1

19.  In the conclusion section, some recommendations are made for further investigation. Why they are not performed in this study? More justifications should be furnished on this.

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Unfortunately, I cannot recommend the present paper for publication for several raisons.

 1.      This is a review paper as stated by the authors in the title of the manuscript; however, the content of this manuscript is largely left to the bibliometric description, which is not important for the readers.

2.      The scientific analysis of the published paper related to the flood prediction is completely missing.

3.      The scientific impact and the add value of the present paper should be certainly minor and negligible.

 

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

The revised paper has addressed all my previous comments, and I suggest to ACCEPT the paper as it is now.

Reviewer 3 Report

 

The authors have improved the paper by providing a reply to the comments, the paper is now accepted.