Analysis of Debris Flow Damage Using High-Resolution Topographical Data

Round 1

Reviewer 1 Report

This manuscript is very impressive on both its writing format and technical contents. The analytical results are properly supported by its modeling techniques and simulation tools, e.g., the LiDAR scanning and unique data processing model, the FLO-2D numerical simulations. The numerical models, also correctly considered the realistic conditions of various geological and mechanical parameters of the debris flow. Therefore, I do not have adverse comments, and personally think this paper can provide insights about the susceptibility analysis to mountain slope instability and debris flow induced by heavy rainfall events in the studied region.

Overall, the authors have shown great advances in this tough topic, so I recommend the publication of this manuscript if the authors can address my concerns as detailed below.

At last, the authors are reminded that all landslides caused debris flow assessment should not be only limited to the deterministic imaginary approach. In the last decade, the probabilistic physically-based modelling approaches which can integrate the slope instability FoS with probability of failure prediction have seen fast development. For example, some recent publications on this topic can be found at: https://doi.org/10.1016/j.compgeo.2019.02.027; https://doi.org/10.1139/cgj-2020-0252; https://doi.org/10.1007/s10346-022-01885-9. The authors should consider this topic in their discussions for possible future study.

For the calculation of peak flow rate, what is the basis for using Eq. (1), please give reference or mention the details about the source data.

For all equations, the explain notes of symbols are not written in a professional way, please revise, and also check that all symbols are properly defined.

In Figure 9, please add more labelling words to explain the details.

Author Response

I have made the following revisions based on your feedback. The modified content in the paper is indicated in blue.

For the calculation of peak flow rate, what is the basis for using Eq. (1), please give reference or mention the details about the source data.

Reference to a report that provided a method for estimating discharge in small-scale watersheds. (Add Content)

For all equations, the explain notes of symbols are not written in a professional way, please revise, and also check that all symbols are properly defined.

The content in the main text regarding equations and symbol explanations has been revised.

In Figure 9, please add more labelling words to explain the details.

I have made revisions to the figure in Figure 9 and updated its content.

Reviewer 2 Report

The manuscript is about the debris flow damage analysis using GIS, LiDAR and FLO-2D. The problem is very pressing, significant and relevant to the journal. Followings are a few of my comments to improve the manuscript:

1.       Please ensure that all the keywords are mentioned within the abstract and are different from the title to enhance the visibility. For example, Debris Flow, need to be changed/replaced/

2.       A single long paragraph Introduction section, may be not a good idea. I would suggest to split the introduction using the following standard structure:

a.       Paragraph 1 about the problem description and significance of problem.

b.       Paragraph 2 about the existing solutions related to problems and research gaps.

c.       Paragraph 3 about the proposed solution and intuition behind the proposed solution. Please see, it is very important to clearly highlight why this research was performed and what motivated researchers to do this work.

d.       In the end, list the contributions of the work.

3.       The detailed literature review section is missing in manuscript and is one of the major lacking. I would suggest authors to critically analyse at least the benchmark research on this topic and draft a literature review section out of it.

4.       Quality of Figure 3 needs to be improved.

5.       What are the limitations of the research? Please clearly clarify.

Get the manuscript proofread by a native language editor

Author Response

I have made the following revisions based on your feedback. The modified content in the paper is indicated in blue.

1. Please ensure that all the keywords are mentioned within the abstract and are different from the title to enhance the visibility. For example, Debris Flow, need to be changed/replaced/

I have added the keywords "GIS data" and "Diffusion area" to the document.

2. A single long paragraph Introduction section, may be not a good idea. I would suggest to split the introduction using the following standard structure:

I have made efforts to enhance the Introduction section by adding content and making overall improvements.

3. I have edited it in a manner consistent with point 2.
4. Quality of Figure 3 needs to be improved.

I have improved the quality of Figure 3.

5. What are the limitations of the research? Please clearly clarify.

I have added content about the limitations of the research at the end of the Introduction section.

Reviewer 3 Report

This research is of some significance for geo-hazards early warning.             There are some errors/suggestions in the manuscript. Please see them in the attached PDF file and correct them throughout the whole manuscript. 

       For these above reasons, I suggest a major revision to this manuscript.  

   

Comments for author File: Comments.pdf

There are some grammar errors in the manuscript. Please see them in the attached PDF file and correct them throughout the whole manuscript. 

Author Response

I have made the following revisions based on your feedback. The modified content in the paper is indicated in blue.

1. It's been changed. (has -> have)
2. I have made revisions to Figure 4, including adding a legend and modifying the illustration.
3. I have improved the quality of Figure 5.
4. I have removed "since."
5. I have made modifications to Figure 8, including adding units of measurement.
6. I have changed "intensity" to "risk" in Table 6.
7. I have made revisions to Figure 9 and updated the relevant content accordingly.
8. I have added information about the functionality of LiDAR and related content to the Conclusion section.

Round 2

Reviewer 1 Report

I noticed the authors have overlooked some serious comments in last round. Please explain further. Compulsory revisions are needed to discuss the future works according to next comments:

 

Tthe authors are reminded that all landslides caused debris flow assessment should not be only limited to the deterministic imaginary approach. In the last decade, the probabilistic physically-based modelling approaches which can integrate the slope instability FoS with probability of failure prediction have seen fast development. For example, some recent publications on this topic can be found at: https://doi.org/10.1016/j.compgeo.2019.02.027; https://doi.org/10.1139/cgj-2020-0252; https://doi.org/10.1007/s10346-022-01885-9. The authors should consider this topic in their discussions for possible future study.

Author Response

comments

revisions

“The authors are reminded that all landslides caused debris flow assessment should not be only limited to the deterministic imaginary approach. In the last decade, the probabilistic physically-based modelling approaches which can integrate the slope instability FoS with probability of failure prediction have seen fast development. For example, some recent publications on this topic can be found at: https://doi.org/10.1016/j.compgeo.2019.02.027; https://doi.org/10.1139/cgj-2020-0252; https://doi.org/10.1007/s10346-022-01885-9. The authors should consider this topic in their discussions for possible future study”.

In response to the feedback, we have incorporated deterministic and probabilistic approaches into a dedicated literature review section.

Here are the major changes made:

Deterministic methodology has proven to be a valuable tool for disaster prediction when precise initial conditions and parameters are accurately known. This approach heavily relies on accurate initial topographic information and precipitation data to model the probability of landslides. Importantly, it employs statistical analysis and numerical model evaluation using field data as essential tools for a systematic response to mitigate the risks associated with debris flows. This methodology predicts the susceptibility of steep areas to landslides during rainfall [8-9], conducts GIS-based landslide risk assessments using deterministic modeling [10], and employs simulations like FLO-2D. It also introduced a numerical method to simulate the behavior of landslides and debris flows in a two-dimensional channel [11-14]. Furthermore, researchers have replicated the dynamic process of disasters and established landslide hazard zones through numerical simulation and risk assessment to more accurately identify landslide-prone areas [15-16]. Although these methodologies significantly contribute to landslide prediction, they inherently entail uncertainties due to simplifications and assumptions.

Probabilistic methodologies, on the other hand, priorities uncertainty in landslide and debris flow prediction. These approaches address uncertainty in initial conditions and parameters by modelling various variables, including topographic, meteorological, and geological variables, as probability distributions. Introduced the FORM (First Order Reliability Method) method, a probabilistic approach to geotechnical design, and assessed safety taking into account ground uncertainty. In addition, a probabilistic method for evaluating soil displacement on seismically loaded slopes was investigated. Emphasized the importance of carrying out GIS-based probabilistic analyses that can holistically consider the various factors contributing to landslide risk, using GIS-FORM to assess slope collapse risk [17-19]. Debris flow risk assessment and the identification of high-risk areas are vital components of disaster prevention and mitigation strategies in mountainous regions. In this context, a probabilistic assessment has been conducted to evaluate the potential risks associated with roads situated in close proximity to mountain slopes [20].

Author Response File: Author Response.pdf

Reviewer 2 Report

Authors failed to address the following comment, although it was mentioned as the major lacking of manuscript

The detailed literature review section is missing in manuscript and is one of the major lacking. I would suggest authors to critically analyse at least the benchmark research on this topic and draft a literature review section out of it.

Author Response

comments	revisions
“Authors failed to address the following comment, although it was mentioned as the major lacking of manuscript. The detailed literature review section is missing in manuscript and is one of the major lacking. I would suggest authors to critically analyse at least the benchmark research on this topic and draft a literature review section out of it”.	In response to the feedback, we have incorporated deterministic and probabilistic approaches into a dedicated literature review section. Additionally, the importance of the numerical model, the uncertainty inherent in the model, and the need for additional research were added and described. I’ve included the additional points you mentioned in the revised text. Here’s the updated version:

Here are the major changes made:

Deterministic methodology has proven to be a valuable tool for disaster prediction when precise initial conditions and parameters are accurately known. This approach heavily relies on accurate initial topographic information and precipitation data to model the probability of landslides. Importantly, it employs statistical analysis and numerical model evaluation using field data as essential tools for a systematic response to mitigate the risks associated with debris flows. This methodology predicts the susceptibility of steep areas to landslides during rainfall [8-9], conducts GIS-based landslide risk assessments using deterministic modeling [10], and employs simulations like FLO-2D. It also introduced a numerical method to simulate the behavior of landslides and debris flows in a two-dimensional channel [11-14]. Furthermore, researchers have replicated the dynamic process of disasters and established landslide hazard zones through numerical simulation and risk assessment to more accurately identify landslide-prone areas [15-16]. Although these methodologies significantly contribute to landslide prediction, they inherently entail uncertainties due to simplifications and assumptions.

Probabilistic methodologies, on the other hand, priorities uncertainty in landslide and debris flow prediction. These approaches address uncertainty in initial conditions and parameters by modelling various variables, including topographic, meteorological, and geological variables, as probability distributions. Introduced the FORM (First Order Reliability Method) method, a probabilistic approach to geotechnical design, and assessed safety taking into account ground uncertainty. In addition, a probabilistic method for evaluating soil displacement on seismically loaded slopes was investigated. Emphasized the importance of carrying out GIS-based probabilistic analyses that can holistically consider the various factors contributing to landslide risk, using GIS-FORM to assess slope collapse risk [17-19]. Debris flow risk assessment and the identification of high-risk areas are vital components of disaster prevention and mitigation strategies in mountainous regions. In this context, a probabilistic assessment has been conducted to evaluate the potential risks associated with roads situated in close proximity to mountain slopes [20].

In this study, we employ the FLO-2D numerical model for an analysis of debris flows, highlighting its crucial role in predicting debris flow disasters and assessing associated risks. Previous research has mainly focused on investigating the causal factors of debris flows and analyzing relevant models, often neglecting the use of accurate topographic data. Our study aims to bridge this gap. We have meticulously surveyed the areas affected by debris flows using LiDAR survey technology, enabling us to construct a high-resolution topographic dataset. The FLO-2D model was used to visualize debris flow characteristics and assess downstream risk, analyzing key parameters such as flow depth, velocity and diffusion area, and allowing a comprehensive comparison of spread areas at different flow rates. However, it's important to emphasize that our results and methodology are based on specific case studies and inherently involve modelling and associated uncertainties. Consequently, further research is warranted to validate their applicability in regions characterized by unique topographic and climatic conditions.

 

Author Response File: Author Response.pdf

Reviewer 3 Report

This research is of some significance for geo-hazards early warning.  

For authors have modified the manuscript according to the proposed comments, I suggest an acceptance for publication to this manuscript.

Author Response

We have revised the paper to reflect your comments, thank you. 

Author Response File: Author Response.pdf

Round 3

Reviewer 1 Report

The authors' fully addressed all previous comments.

Author Response

Thank you for your comments.

Reviewer 2 Report

Building the narrative on the bases of literature analysis within the introduction is fine and almost must. Its good that authors have that included in the introduction section. However, having a seperate detailed literature review section critically analysing the benchmark research in the domain and comparing the existing literature in various ways in what was asked. I would suggest the authors to add a new section 2. Literature Review in which they in detail present what has been done already and subjectively criticise the literature to identify the research gaps. I hope this makes it clear what is asked from the authors.

Author Response

comments

revisions

“Building the narrative on the bases of literature analysis within the introduction is fine and almost must. Its good that authors have that included in the introduction section. However, having a seperate detailed literature review section critically analysing the benchmark research in the domain and comparing the existing literature in various ways in what was asked. I would suggest the authors to add a new section 2. Literature Review in which they in detail present what has been done already and subjectively criticise the literature to identify the research gaps. I hope this makes it clear what is asked from the authors.”

In response to feedback, we've added a literature review section that critically analyses and compares benchmark research, as shown below. Thank you for your comments.

Here’s the updated version:

In this research, we use the FLO-2D numerical model to perform a debris flow analysis, emphasising the critical role of the model in predicting debris flow disasters and assessing associated risks. In a previous study, FLO-2D numerical simulations were performed for areas where debris flow disasters occurred, and the simulation results were compared with field data to verify the accuracy of the model predictions [11,15]. In order to understand the dynamics of debris flow material as influenced by rainfall, analyses have been carried out to assess the sensitivity of the models to parameter changes and to predict the extent of debris flow diffusion [12,14]. The simulations also highlight the importance of using LiDAR DEM to improve the accuracy and reliability of predictions of debris flow occurrence, movement and erosion [21]. In numerical modelling studies, achieving a close match with real-world phenomena is of paramount importance. While the above studies have shown consistency between debris flow patterns and model fit, quantitative data on the affected areas are still lacking. Consequently, uncertainties remain regarding the extent of debris flow diffusion. To comprehensively overcome these limitations, our study carefully integrates various data sources, including field data, parameters, LiDAR DEM and more. In addition, we conducted a topographic LiDAR survey to fill in the quantitative data gaps, thus enabling a quantitative representation and analysis of the debris flow affected areas.

Author Response File: Author Response.pdf