Mapping Geospatial AI Flood Risk in National Road Networks

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

I suggest moderate revisions. In the following my comments:

1. I think the introduction is difficult to read. I suggest to summarize the text to main improtant concepts. The introduction should briefly focuses on backgrounds and on the limits of past literature studies but also describe the gaps that the proposed manuscript would like to fill. A minor note: the figures taken from Scopus are not clear and the methodological procedure that  can bring an appropriate selection of the manuscripts is not defined.

2. The methodological section needs more details or if it is taken from past studies needs citation. All the details about procedures, parameters and input data (source, resolution, time frame and so on) needs to be discussed.

3. Why you have not compared the obtained flood maps with the point of the flooded events? The flood points of the past events need more info about type, return time, timing of the events and so on.

4. I suggest to add in figure 5 and 6 the total number of analyzed roads to understand the better the percentage values (e.g. the 10% of 1000 roads at risk is different from the 10% of 10 or 50% of 10 for flood management issues).

5.The validation should be done in qualitative terms. A summarized table fo the results should be added.

 

Author Response

Reviewer 1:

Comments 1: I think the introduction is difficult to read. I suggest to summarize the text to main improtant concepts. The introduction should briefly focuses on backgrounds and on the limits of past literature studies but also describe the gaps that the proposed manuscript would like to fill. A minor note: the figures taken from Scopus are not clear and the methodological procedure that can bring an appropriate selection of the manuscripts is not defined.

Response 1: Thank you for this feedback. The introduction revised that to be more concise and consistent having mention the gaps and the Figure 1 is completely revised to be more readable and simple.

Comments 2: The methodological section needs more details or if it is taken from past studies needs citation. All the details about procedures, parameters and input data (source, resolution, time frame and so on) needs to be discussed.

Response 2: We appreciate this observation and have expanded the methodology section to provide more detailed information about the procedures, parameters, and input data from previous study.

Comments 3: Why you have not compared the obtained flood maps with the point of the flooded events? The flood points of the past events need more info about type, return time, timing of the events and so on.

Response 3: Thank you for raising this important point. These maps are provided in previous study which is submitted on Sustainable Cities and Society and its in second reviewing procedure that the figures cannot be exposed on another publication. I have provide some of the figures below for your reference.

Comments 4: I suggest to add in figure 5 and 6 the total number of analyzed roads to understand the better the percentage values (e.g. the 10% of 1000 roads at risk is different from the 10% of 10 or 50% of 10 for flood management issues).

Response 4: Thanks for your comment, its actually interesting to add the number of road, however due to the OSM data restriction the roads sections had various length and they are not following the same pattern and the best approach on these occasion is better to have length (km) which represent the better and clearer picture of the road analysis as presented on Figure 5, and the percentages are separately presented on Figure 6.

Comments 5: The validation should be done in qualitative terms. A summarized table fo the results should be added.

Response 5: Thank you for this suggestion. We have now included a full table and explanation on this matter to address your concerns.

“””

 

The validation of the flood probability model was conducted using a qualitative approach (see Table 1). We categorized the model's predictions into two groups: above 50% probability and below 50% probability. These predictions were then compared to the actual flood occurrences, where 1 indicates a flood event and 0 indicates no flood.

The results show that the model correctly predicted 167,386 cases out of a total of 182,616 instances. This translates to an accuracy of 92%, which indicates a high level of predictive performance. The model demonstrates strong capability in distinguishing between flood and non-flood events based on the 50% probability threshold.

It's important to note that while the overall accuracy is high, there may be variations in performance across different probability ranges. Further analysis of specific probability brackets could provide more detailed insights into the model's strengths and potential areas for improvement.

Table 1. Summary of Flood Prediction Model Performance Using 50% Probability Threshold

Prediction Category	Correct Predictions	Incorrect Predictions	Total
Above 50% probability	14,732	9,607	24,339
Below 50% probability	152,654	5,723	158,377
Total	167,386	15,330	182,616
Accuracy	92%

Table provides a clear overview of the model's performance, showing the distribution of correct and incorrect predictions for both high and low probability categories. The high number of correct predictions in both categories contributes to the model's impressive overall accuracy of 92%.

 

 

”””

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Weaknesses

While the study is comprehensive within the Portuguese context, the generalizability of the findings to other regions with different topographic and climatic conditions might be limited. Further studies could extend the methodology to diverse geographical areas to validate its applicability.

The study abstracts from temporal variables such as weather or precipitation patterns, focusing solely on land characteristics. Incorporating these temporal factors could provide a more dynamic and holistic understanding of flood risks.

The application of the model in real-time flood monitoring and response is not extensively discussed. Future research could explore how the GeoAI model can be integrated into real-time flood management systems for immediate response and mitigation.

Recommendations

Extend the methodology to different geographical regions to validate the model's applicability and robustness across various topographic and climatic conditions.

Integrate temporal environmental factors such as real-time weather data and precipitation patterns to enhance the predictive capability of the model.

Investigate the integration of the GeoAI model into real-time flood monitoring and response systems to enhance immediate flood management capabilities.

 

Comments on the Quality of English Language

Areas for Improvement:

1. Complex Sentences:

   • Some sentences are complex and lengthy, which may affect readability. Breaking these into shorter sentences could enhance clarity.

2. Redundancy:

   • There are occasional redundancies where the same idea is repeated in different sections. Streamlining these sections could improve conciseness.

3. Passive Voice:

   • The article frequently uses the passive voice, which can make the text less engaging. Using active voice where appropriate could make the writing more dynamic.

4. Minor Grammatical Errors:

   • There are a few minor grammatical errors and typos that need correction. For example, ensuring subject-verb agreement and proper punctuation in complex sentences.

Author Response

Reviewer 2:

Comments 1: While the study is comprehensive within the Portuguese context, the generalizability of the findings to other regions with different topographic and climatic conditions might be limited. Further studies could extend the methodology to diverse geographical areas to validate its applicability.

Response 1: Thanks for your comments, due to data-collection procedure, and the sequence of the studies that we are performing it is not feasible to apply this for other regions. And in future studies we will apply the model to other European regions. This is also explained further in the discussion and conclusion sections.

 

Comments 2: The study abstracts from temporal variables such as weather or precipitation patterns, focusing solely on land characteristics. Incorporating these temporal factors could provide a more dynamic and holistic understanding of flood risks.

Response 2: Thanks for your comments, the uniqueness of this study lies in this area that using the fixed land characteristic and topography information that create a fix layer for using in the future studies that then can be use to have adding weather or precipitation patterns in future studies. A discussion added explaining this in the article clearly.

 

Comments 3: The application of the model in real-time flood monitoring and response is not extensively discussed. Future research could explore how the GeoAI model can be integrated into real-time flood management systems for immediate response and mitigation.

Response 3: Thank you for this insightful comment. We have also write at future study and limitation this great point you have mentioned.

 

Comments 4: Areas for Improvement: Complex Sentences, Redundancy, Passive Voice, Minor Grammatical Errors.

Response 4: We appreciate these suggestions and have carefully revised the manuscript to address the concerns regarding complex sentences, redundancy, passive voice, and minor grammatical errors. We have aimed for clearer, more concise, and engaging language throughout the text.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This paper presents an innovative integration of Geospatial Artificial Intelligence for hazard mapping to assess flood risks on road networks, incorporating OpenStreetMap's road network data to study vulnerability, and emphasizing the importance of integrating geospatial analysis tools with open data to enhance the resilience of critical infrastructure against natural hazards.

Manuscript is quite long; authors should reconsider restructuring and optimization of the manuscript.

I believe that the title should be rephrased; it is too general and it doesn't fully represent the research focus of this paper.

Authors should pay attention to citation style used in the manuscript, it is inconsistent, making it hard to follow the relevance of particular references.

Literature review section is unnecessarily long, in this form it does not contribute to quality of the manuscript. Quite opposite actually, due to length of the manuscript authors should pay more attention considering potential readers and their overall interest. Reviewing a broad number of references generally related to flood risk, authors do not support their innovative methodology presented in this paper. My recommendation is to merge first and second chapter into a single straightforward chapter, where authors will provide their review on state-of-the-art references that are strictly related to their research.

Methodological part is too general. I understand that the authors are familiar with AI techniques, but since this paper could be read by scientists and experts  in the field of flood risk but with little or no background to AI and Machine Learning, authors should explain particular steps of the methodology more thoroughly. Authors do not explain how actually the model is developed and based on the presented methodology, this approach could hardly be reproduced on some other site. Authors have underestimated the importance of actual natural conditions leading to flood occurrence (either fluvial or coastal). If their intention was to include other factors in flood hazard assessment other than just natural (for example precipitation), this must be better communicated and explained.

Considering the results, my recommendation to authors is to avoid using expression "road flood probability", especially of you rate it 0-100. As I recall, authors are rating flood risk on a scale 0-100, "during heavy rainfall or similar extreme weather events". Representing flood risk as "road flood probability" is not in accordance with common flood risk assessment practice and it is misleading.

 

Comments on the Quality of English Language

Authors use a large amount of words and complex phrases that are not common in everyday use, especially for non-English readers. Many of these phrases are really general and do not contribute to the paper at all. Please use simple English and focus only on what actually matters. Removing unnecessary and complex phrases will shorten your manuscript and make it more appealing to potential readers.

Author Response

Reviewer 3:

Comments 1: Manuscript is quite long; authors should reconsider restructuring and optimization of the manuscript.

Response 1: Thank you for this feedback. We have reviewed the manuscript and made efforts to streamline and shorten the text where possible, particularly in the literature review section.

Comments 2: I believe that the title should be rephrased; it is too general and it doesn't fully represent the research focus of this paper.

Response 2: We appreciate this suggestion and have revised the title. Please be informed that this study focus is simply and practically map the predicted flood on the road network and do not offer any other insights/solution.

Comments 3: Authors should pay attention to citation style used in the manuscript, it is inconsistent, making it hard to follow the relevance of particular references.

Response 3: We apologize for this oversight. We have carefully reviewed and corrected the citation style throughout the manuscript to ensure consistency.

Comments 4: Literature review section is unnecessarily long... My recommendation is to merge first and second chapter into a single straightforward chapter, where authors will provide their review on state-of-the-art references that are strictly related to their research.

Response 4: Thank you for this valuable suggestion. We have significantly shortened and restructured the literature review, focusing on the most relevant references directly related to our research.

Comments 5: Methodological part is too general... Authors do not explain how actually the model is developed and based on the presented methodology, this approach could hardly be reproduced on some other site...

Response 5: We understand the need for greater clarity in the methodological section. We have expanded this section to provide more detailed information on the model development process which is explained the previous study evolution and how the previous study obtain the flood maps, including specific parameters and steps involved. We believe this revised description will facilitate reproducibility of the approach.

Comments 6: Considering the results, my recommendation to authors is to avoid using expression "road flood probability", especially of you rate it 0-100. As I recall, authors are rating flood risk on a scale 0-100, "during heavy rainfall or similar extreme weather events". Representing flood risk as "road flood probability" is not in accordance with common flood risk assessment practice and it is misleading.

Response 6: We appreciate this feedback and agree that the term "road flood probability" could be misleading. We have revised the text to use the more accurate term "flood risk score" throughout the manuscript, clarifying that it represents the relative likelihood of flooding on a scale of 0-100 based on the model's assessment.

Comments 7: Authors use a large amount of words and complex phrases that are not common in everyday use, especially for non-English readers. Many of these phrases are really general and do not contribute to the paper at all. Please use simple English and focus only on what actually matters. Removing unnecessary and complex phrases will shorten your manuscript and make it more appealing to potential readers.

Response 7: We appreciate this feedback and we have taken this feedback seriously and have revised the manuscript to use simpler and more direct language. We have eliminated unnecessary jargon and complex phrases to improve clarity and readability for a wider audience.

 

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

All suggestion were implemented.

Author Response

 Thank you for your thorough review and valuable feedback. I appreciate your positive assessment and am glad that the revisions have addressed your suggestions.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

Dear Authors,

although you've invested large efforts in improving your manuscript, there are still some issues to be discussed before publishing.

Although literature review covers a large amount of similar papers, I still believe that it should be improved. Literature review should contain a critical review of previously published paper similar to your topic. Summarizing each paper in few lines doesn't give us an appropriate overview on advantages and disadvantages of each paper. By improving this part, you can further support your research methodology and demonstrate the necessity for development of a new approach.

Furthermore, methodological part should be generally better explained. In its current shape, it is customized for your site and explanation how it can be applied to other sites is missing.

Please remove expression "road flood probability" from all figures; it has been removed from Figure 3 only while in Figures 9.-16. still remains.

Comments on the Quality of English Language

English has improved but it could be once again revised by a native speaker.

Author Response

Comments and Responses

Comment 1: Although literature review covers a large amount of similar papers, I still believe that it should be improved. Literature review should contain a critical review of previously published paper similar to your topic. Summarizing each paper in few lines doesn't give us an appropriate overview on advantages and disadvantages of each paper. By improving this part, you can further support your research methodology and demonstrate the necessity for development of a new approach.

Response 1: Thank you for your feedback. We have revised portions of the literature review to emphasize a more focused topic. However, it's important to note that this paper primarily focuses on mapping the developed flood model onto the road network asset system. As such, the paper is specifically aimed at presenting a data wrangling technique that refines and visualizes the flood risk score on roads, using the probability generated by the consensus mechanism of the predictor forest. Following a bibliometric analysis, the literature review highlights the critical importance of studying the impact of floods on transportation systems. Some adjustments are done and extra explanation added to the end of the literature review as : “This literature review provides a well-rounded understanding of the strengths and limitations found in various flood risk management approaches, especially concerning road networks. By evaluating different methodologies, it reveals effective strategies, such as the use of advanced technologies and socio-economic considerations, while also pointing out areas that need further attention, like the resilience of infrastructure in vulnerable regions. This analysis supports the development of a new research methodology by illustrating the need for innovative solutions that address current shortcomings and enhance the protection of transportation networks against flood risks. It also underscores the importance of integrating a Geospatial-AI approach to more precisely evaluate and mitigate the impacts of floods on critical infrastructure.”

 

Comment 2: Furthermore, methodological part should be generally better explained. In its current shape, it is customized for your site and explanation how it can be applied to other sites is missing.

Response 2: Thank you for your valuable feedback. You've raised an important point, and we've addressed it by adding two paragraphs at the end of the methodology section. These new paragraphs explain how our approach can be applied to other sites, ensuring that the methodology is adaptable and not limited to the specific context of our study.

 

Comment 3: Please remove expression "road flood probability" from all figures; it has been removed from Figure 3 only while in Figures 9.-16. still remains.

Response 3: Thank you for your feedback. We have removed the expression "road flood probability" and replaced it with "Flood risk score" across all relevant figures. While this change has already been applied to Figure 3, we have now updated Figures 9-16 as well.