Evaluation of Landslide Risk Using the WoE and IV Methods: A Case Study in the Zipaquirá–Pacho Road Corridor

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

1. A study area map is needed in Introduction section.
2. Figure 1 presents a methodology that considers only two causal factors, data sources and geoenvironmental factors, for generating the landslide susceptibility zoning map. However, a crucial factor, hydro-meteorological conditions, is missing. Given that rainfall and other climatic elements are major triggers of landslides globally, their inclusion is essential for a more comprehensive and accurate assessment.
3. The study relies on a single snapshot of data. This static approach may not account for temporal changes in causal factors that can influence landslide occurrences. Further, the study splits the data 70/30 for modelling and validation, the spatial representativeness of the selected points for training versus validation could be questioned, potentially impacting the model’s generalizability. Such limitations of the study must be acknowledged.
4. WoE and IV methods, though useful, may not fully capture complex non-linear interactions among causal factors, where machine learning could enhance prediction. Relying solely on the AUC metric for validation may overlook spatial autocorrelation and overfitting risks, limiting a comprehensive performance assessment. Such limitations of the study must be acknowledged.
5. Detailed description of Figure 4 is needed, especially the similarity % of area between Very low to very high susceptibility areas.

Author Response

Please see the attached response file.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

Dear Editor and Authors,

I have revised the manuscript entitled: Evaluation of Landslide Risk Using the WoE and IV Methods: A Case Study in the Zipaquirá–Pacho road Corridor.  The aims of the study are the assessment of a landslide susceptibility zoning map for the Zipaquirá-Pacho road corridor in Cundinamarca, an area prone to frequent landslides. Two statistical methods—Weight of Evidence (WoE) and Information Value (IV)—were applied alongside various causal factors to generate the map using GIS software. The topic of the manuscript is certainly suitable for the journal and of potential international interest, but unfortunately, the paper has several critical points that hamper the publication in the present form and a major revision is request. The main problem of the paper is that the approach used is not novel, furthermore, the contribution appears confused and low fluid and in many part the methodology applied should be better described. No interesting details about the data specification and study area that show the uniqueness of the problem statement with the hypothesis and findings no in depth discussion, only presenting the results in general manner and often unclear. Many data are presented, which is either not clear how was obtained and/or discussed in depth. The discussion failed to present a clear story but rather includes several issues, which were discussed in a superficial way.

In the following, the authors can find several comments and suggestions.

 

1) In the introduction section, it is challenging to see the justification for this research. The literature review is insufficient. The paper needs to clearly state the problems with existing works and specify what problem(s) this paper addresses. Also, the research background about the proposed subject and methods has not been appropriately mentioned, especially about the applied suggested models in previous studies. Furthermore, the main goal of the current research should clearly and concisely explain the main scientific contributions of this work.

 

2) Today's more advanced machine learning models have proven to be more effective in landslide susceptibility assessment, therefore, the Authors should explain why in the your their have used the WoE and IV methods for mapping landslide susceptibility?

 

3) I suggest to add some information, related to geological, geomorphological and climatic setting of the study area.

 

4) I suggest also to add in the text a brief description of the landslide type. The authors should be add in the text some information about landslide movement, according to their types (for more see: Cruden DM, Varnes DJ (1996) Landslide types and processes. In: Turner AK, Schuster RL (eds) Landslides investigation and mitigation. Transportation research board, US National Council, Special Report 247, Washington, DC, Chapter 3:36-75, and Hungr O, Leroueil S, Picarelli L (2014) The Varnes classification of landslide types, an update. Landslides 11:167-194).

 

5) The Sections 2.2, 2.3 and 2.4 can be coupled. Several sentences are repetition.

 

6) The authors should be evaluate the relative importance of each causal factor used for mapping the landslide susceptibility analysis, applying the Jack-knife test. This analyses it is important to identify the causal factors and their contribute to perform a landslide susceptibility map. Not all causal factors have an equal importance on landslide occurrences; thus, the most and least important factors must be identified and the least effective factors should be removed from modelling, as they can reduce the prediction capability of the susceptibility model.

For major details regards to application and useful of the Jack-knife test I recommend the following Research articles:

-Convertino M, Troccoli A, Catani F. 2013. Detecting fingerprints of landslide drivers: a MaxEnt model. J Geophys Res Earth Surf. 118(3):1367–1386.

-Gullà G., Conforti M., Borrelli L. 2021. A refinement analysis of the shallow landslides susceptibility at regional scale supported by GIS-aided geo-database. Geomatics, Natural Hazards and Risk, 12 (1), 2500–2543. https://doi.org/10.1080/19475705.2021.1967204

-Tien Bui D, Tuan TA, Klempe H, Pradhan B, Revhaug I. 2016. Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree. Landslides. 13(2):361–378.

7) No critical analysis of results has been reported in the paper. The result section is so poor in writing and obtaining results. Also, the written results do not have homogeneous due to no logical relationship between applied methods results.

8) The discussion failed to present a clear story but rather includes several issues which were discussed in a superficial way.  Therefore, these aspect should be better focussed in the discussion section. Also, the Authors should better highlight the novelty of the applied methodology and their points of force. The authors must emphasize that their work can be successfully used in other regions and settings, because this justify the publication in an international journal.

9) I did not see any note about the comparison between the obtained results of the current research and previous research.

Applying all the corrections to your manuscript, it will be significantly improved and should be able to get published in the next step.

Author Response

Please see the attached response file.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

The paper describes the development of a landslide susceptibility map along a road corridor in Colombia which has been subject to impactful landslides. 

The paper is well written and the research is clearly laid out. The weaknesses lie in not fully explaining the landslide processes and linking these to the factors chosen as well as the similarity in the approaches being compared. There is a lack of novelty in the manuscript, although it is a good case study. 

However I am curious as to why two bivariate statistical approaches were chosen to be compared? This could have been more interesting to the reader to compare two more contrasting methodologies. The end results give very similar success rates which is not unsurprising.  What are the benefits of each method compared to the other. 

It would add more context for the reader to know what type of landslides are occurring in the study area, this would then help the reader understand what drove some of the decision making around inclusion of certain factors in the methodology. 

No explanation of the Sen2P slope factor. 

More discussion and justification in general about the factors included. in Section 2.5- this was lacking and links to the missing information on landslide type. I would like to see how the factors chosen link to the actual landslide process. 

The inventory contains 101 landslides which are concentrated along the road section but there appears to be a large area included within the study area away from the road. Are there any landslides in these areas? Doe the inclusion of a wider study area away from the road with a limited inventory along the road cause any bias in the method? 

Are all the landslides natural? With their proximity to the road section are the landslides occurring due to factors not able to be included within the assessment such as construction technique or cut slopes being oversteepened. 

There seems to be some repetition throughout of the inventory/its creation, this could be cut down (Line 50-56, 66-75, 186-189.)

 

Author Response

Please see the attached response file.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Dear Editor and Authors,

I have revised the new version of manuscript entitled: : Evaluation of Landslide Risk Using the WoE and IV Methods: A Case Study in the Zipaquirá–Pacho road Corridor. My opinion is that the quality of the manuscript respect to first version, has been improved considering most of the suggestions of the reviewers. The Authors have discussed with great attention and wealth of details the items of the research. The paper appears well constructed, documented and the results have been widely discussed. Hence, it is recommended that the manuscript now can be accepted for publication in its present form.

Author Response

Please refer to the attached response letter for a detailed reply.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

Thank you for the improvements and clarifications that have been made.

I have a few follow up comments that need addressing. 

I am still unclear about Sen2P slope factor- how is this different to slope (degree)? The explanation does not clarify how the two slopes factors are different and the text in line 291 does not match the values in the Table 2 (0-15, 15-25). Does the Sen2P factor represent a different topographic attribute?

Line 295-300: The link between rotational landslides and distance to faults is a bit weak and flow accumulation seems better suited to debris flows. this paragraph feels a bit like its been added  without fully being thought through. 

Author Response

Please refer to the attached response letter for a detailed reply.

Author Response File: Author Response.docx