Analysis of Ground Subsidence Vulnerability in Urban Areas Using Spatial Regression Analysis

Round 1

Reviewer 1 Report

1            Authors are recommended to emphasis the novelty and significance of the study in more detail.

2            The manuscript contains some errors of the format of reference citation, when citing multiple references, “-” should be added between the first and the last one. For example, “[3][4][5][6][7][8]” should be “[3-8]”. When citing two articles, add “,”. “[12][13]” should be “[12,13]”.

3            Some of the references provided are old. It is suggested that a number of recent papers that are new and have been published in the last five years be used in the introduction and references list.

4            Authors are recommended that letters in equations should be italicized if they are variables, or regular font if they serve as explanatory notes. Please be consistent throughout.

5            Please explain the meaning of “*” in Table 2. It is suggested to add relevant explanation in the manuscript.

6            Authors are recommended to provide a more complete explanation in the “A Map of Ground Subsidence Vulnerability” section with literature.

 

Author Response

Review.1

 

1. Authors are recommended to emphasis the novelty and significance of the study in more detail.

 

• Current research on ground subsidence is focused on mechanism analysis through indoor model experiments and machine learning-based methodologies for predicting the risk of ground subsidence. Thus, this study conducted research on how the risk of ground subsidence could be predicted using spatial regression analysis, which takes spatial characteristics into account. In addition, it is expected that the findings of this study can be used to prevent ground subsidence accidents in high-risk areas using equipment such as ground penetrating radar. This content has been added to the Introduction. (line 61-84)

 

2. The manuscript contains some errors of the format of reference citation, when citing multiple references, “-” should be added between the first and the last one. For example, “[3][4][5][6][7][8]” should be “[3-8]”. When citing two articles, add “,”. “[12][13]” should be “[12,13]”.

 

• We corrected this in the manuscript.

 

3. Some of the references provided are old. It is suggested that a number of recent papers that are new and have been published in the last five years be used in the introduction and references list.

 

• We replaced outdated references with newer references.

 

4. Authors are recommended that letters in equations should be italicized if they are variables, or regular font if they serve as explanatory notes. Please be consistent throughout.

 

• We have italicized the variables in the equations in the manuscript.

 

5. Please explain the meaning of “*” in Table 2. It is suggested to add relevant explanation in the manuscript.

 

• We have summarized the contents of Table 2 focusing on the occurrence of ground subsidence, and have added an explanation for the asterisk (*). (Table.2)

 

6. Authors are recommended to provide a more complete explanation in the “A Map of Ground Subsidence Vulnerability” section with literature.

 

• We have added the relevant content in the section. The map of ground subsidence vulnerability presented in this study reflects the results of a model developed using only the attribute information of underground utilities. As mentioned in the Introduction, ground subsidence is caused by a variety of factors, so the ideal approach is to develop a model that reflects all of the data that affect the occurrence of ground subsidence. However, realistically, it is not feasible to obtain such a large amount of data. In this study, the model was developed primarily based on the available data that has been digitized and stored in databases by the responsible authorities. Thus, if a large amount of data is available in the future, we expect that a model with higher accuracy than the current model will be developed. (line 318-323)

Author Response File: Author Response.pdf

Reviewer 2 Report

Dear Author,

Please see the comments below.

1.     The introduction can be improved.

2.     Line 85: Please explain what you mean by missing data and outliers.

3.     Line 111: Can you please explain what you mean by density of pipe? What is the unit of density in Table 1?

4.     Use consistent symbols in equations 1 and 2.

5.     Do you have results for the combined effect (gap pipe, age, density….)?

6.     Did you verify the results from the regression analysis?

 

7.     Line 307: It is mentioned that the SLM model didn’t predict vulnerability well in the western part. How could you improve the model to predict it better? Did you check with the SEM model in those areas where SLM couldn’t predict well?

 

Thank you!

Dear Authors,

In my point of view, overall the language seems to be okay. However, it can be better. 

Author Response

Review.2

 

1 .The introduction can be improved.

 

• In the Introduction, we highlighted the novelty of this study and the expected effect of the research findings as follows. Current research on ground subsidence is focused on mechanism analysis through indoor model experiments and machine learning-based methodologies for predicting the risk of ground subsidence. Thus, this study conducted research on how the risk of ground subsidence could be predicted using spatial regression analysis, which takes spatial characteristics into account. In addition, it is expected that the findings of this study can be used to prevent ground subsidence accidents in high-risk areas using equipment such as ground penetrating radar. (line 61-84)

 

2. Line 85: Please explain what you mean by missing data and outliers.

 

• We added the meaning of missing data and outliers in that line. Missing values mean blank values in the database, and outliers mean values that are generally impossible. For example, it indicates values of the burial depth, pipe diameter, and age that are negative (-) or written as "0". (line 95-97)

 

3. Line 111: Can you please explain what you mean by density of pipe? What is the unit of density in Table 1?

 

• The density is a calculation of the length of the pipeline corresponding to a unit area (100m×100m), using a GIS program. A high density indicates that there are many buried pipes, and can also be interpreted as a high level of soil disturbance. The density of a pipe has no unit. (line 125-126)

 

4. Use consistent symbols in equations 1 and 2.

 

• We have unified the symbols in Equations 1 and 2.

 

5. Do you have results for the combined effect (gap pipe, age, density….)?

 

• In fact, ground subsidence is a complex phenomenon that can occur due to various and interconnected causes. Thus, it is desirable to prepare for ground subsidence accidents based on various factors. However, in reality, collecting accurate data can be challenging. Therefore, in this study, we collected the data, and developed a model, considering damage to underground utilities as the main cause of ground subsidence. Damage to underground utilities has been shown to occur due to age, pipe type, pipe diameter, length, soil quality, and corrosion from groundwater levels (Factors Influencing the Condition of Sewer Pipes: State-of-the-Art Review, 2020). The main purpose of this study is to develop a ground subsidence vulnerability model based on the available database. In this regard, we performed our analysis considering the damage to underground utilities to be caused by factors independent of the attribute information.

 

6. Did you verify the results from the regression analysis?

 

• The regression analysis results exhibited that the error term was non-normal and heteroscedastic, and the spatial autocorrelation of the residuals was verified. Accordingly, it is desirable to perform a spatial regression analysis that includes spatial effects. Because of this, analyzing the vulnerability of ground subsidence in the target area through OLS analysis results is not appropriate, and a map of ground subsidence vulnerability has not been presented.

 

7. Line 307: It is mentioned that the SLM model didn’t predict vulnerability well in the western part. How could you improve the model to predict it better? Did you check with the SEM model in those areas where SLM couldn’t predict well?

 

• The map of ground subsidence vulnerability in the target area was created through the results of the SEM model. We also compared the results. The comparison showed that the vulnerability prediction of the western part of the target area was not well done, as was the case with the SLM model. This suggests that the ground subsidence accident that occurred in the area may not have been caused by damage to underground utilities. Ground subsidence is caused by a variety of factors, so the ideal approach is to develop a model that reflects all of the data that affect the occurrence of ground subsidence. However, realistically, it is not feasible to obtain such a large amount of data. In this study, the model was developed primarily based on the available data that has been digitized and stored in databases by the responsible authorities. Thus, if a large amount of data becomes available in the future, we expect that a model with higher accuracy than the current model will be developed. This has been added to the manuscript.

Author Response File: Author Response.pdf

Reviewer 3 Report

Dear Authors

Scientific comments

The article would improve if you interpreted some concepts and variables, equations, parameters, units Figures and acronyms used, e.g.

Line 39 and following … Ground subsidence has been reported to be a risk for fluctuations in the coefficient of permeability due to the formation 40 of water channels in the presence of heterogeneous materials such as underground utili-41 ties and facilities [2]… it should be better explained  based on the Internal erosion principle, also known as piping, is one of the major causes of earth failures. Piping occurs when flowing water transport soil particles out of the structure of soil creating a hole within the soil.

Line 56 … the relative density of the ground, and stratigraphic conditions were sig-56 nificant factors influencing the ground subsidence … it is not scientifically correct, because the significant factors are dependent on the variation in the effective stress induced by the alteration of the water table (in case of the water pipe rupture) and/or the internal erosion (turbulent flow - cannot apply Darcy's Law) of particles. There are differences between the settlement and subsidence process. You must not mix concepts. The application of GIS in the elaboration of thematic maps is only a good decision tool if starting from solid and scientifically correct concepts in the evaluation of the parameters or physical phenomena that are intended to be represented.

It makes no sense to present Table 2 with 3 pages. They are long and difficult to interpret. What is intended is that it is possible to create a viable geographic information base for the elaboration of thematic cartography, using cartographic sources from open platforms or commercial programs, together with free software (this topic should be addressed). It must present the geographic basis, including scale and traditional cartographic sources. The diffusion of Geographic Information Systems (GIS), intensified in recent decades, provided a significant step in the development of thematic cartography using geographic databases and new analysis tools. The growing need for more complete and diverse information favors open-source software. It's important to become competitive with commercial software - It was central to focus on this topic.

Evaluate the generated thematic maps (Fig. 2) based on the treated data it’s necessary to evaluate critically.

bibliography is too long.

Editorial comments

Table 2 needs to be condensed.

Table 4 and Table (5?) line265 in same page.

Line 265; Legend of Table 5 (?).

Author Response

Review.3

 

1. The article would improve if you interpreted some concepts and variables, equations, parameters, units Figures and acronyms used, e.g.

 

• We have made efforts to improve our paper based on the reviews. Thank you for your various research-related suggestions to improve the content of this manuscript. (line 39-46)

 

2. Line 39 and following … Ground subsidence has been reported to be a risk for fluctuations in the coefficient of permeability due to the formation 40 of water channels in the presence of heterogeneous materials such as underground utili-41 ties and facilities [2]… it should be better explained based on the Internal erosion principle, also known as piping, is one of the major causes of earth failures. Piping occurs when flowing water transport soil particles out of the structure of soil creating a hole within the soil.

 

• We have revised the description of the ground subsidence occurrence mechanism in the introduction, and provided references. The mechanism of ground subsidence has been studied using numerical models, indoor model experiments, and other methods. Ground subsidence occurs when soil particles are lost or eroded from the area surrounding underground structures due to changes in groundwater (infiltration water, water table). This leads to the formation of holes in the ground, and the repeated expansion and contraction of these holes eventually results in the collapse of the upper layers of the ground. As you mentioned, this is similar to the phenomenon of piping, in which soil particles are eroded and transported by groundwater flow.

 

3. Line 56 … the relative density of the ground, and stratigraphic conditions were sig-56 nificant factors influencing the ground subsidence … it is not scientifically correct, because the significant factors are dependent on the variation in the effective stress induced by the alteration of the water table (in case of the water pipe rupture) and/or the internal erosion (turbulent flow - cannot apply Darcy's Law) of particles. There are differences between the settlement and subsidence process. You must not mix concepts. The application of GIS in the elaboration of thematic maps is only a good decision tool if starting from solid and scientifically correct concepts in the evaluation of the parameters or physical phenomena that are intended to be represented.

 

• Ground subsidence is a phenomenon caused by the development of cavities in the ground. As you mentioned, cavities in the ground have engineering-related causes, and it would be beneficial to clarify this and incorporate it into the ground subsidence vulnerability analysis. However, it is very difficult to collect data on ground conditions and engineering over an extensive area. Thus, in this study, we acquired the attribute data of underground utilities, which are the main causes of ground subsidence, for underground space management, and analyzed the vulnerability of ground subsidence based on the acquired data. In this process, we used GIS software to identify the locations of underground utilities and ground subsidence, and extract data. As you pointed out, the ideal approach would be to develop a reliable model that takes into account both ground conditions and engineering factors. In the future, we plan to conduct a study to collect data on the physical properties of the ground in the target area, and reflect it in the model. (Table.2)

 

4. It makes no sense to present Table 2 with 3 pages. They are long and difficult to interpret. What is intended is that it is possible to create a viable geographic information base for the elaboration of thematic cartography, using cartographic sources from open platforms or commercial programs, together with free software (this topic should be addressed). It must present the geographic basis, including scale and traditional cartographic sources. The diffusion of Geographic Information Systems (GIS), intensified in recent decades, provided a significant step in the development of thematic cartography using geographic databases and new analysis tools. The growing need for more complete and diverse information favors open-source software. It's important to become competitive with commercial software - It was central to focus on this topic.

 

• We have rearranged Table 2 to summarize the results of a correlation analysis between ground subsidence and underground utility attribute information, which is the main finding of this study. In addition, we used ArcGIS to extract data and create a map of ground subsidence vulnerability. This can be done by using QGIS, a free software program, to analyze and provide the results. The data used in ArcGIS (land registration map, ground subsidence history information, underground utility attribute information) were provided by the Korean government agency, which is the management body. Some of the data are subject to security restrictions. In particular, disclosing exact locations on the ground subsidence vulnerability map is very difficult in practice, as it can cause various social issues (The government also does not want to disclose detailed location information of underground utilities). Therefore, in this study, we believe that it is possible to develop a ground subsidence vulnerability prediction model by conducting a spatial regression analysis using underground utility attribute information and ground subsidence history information.

 

5. Evaluate the generated thematic maps (Fig. 2) based on the treated data it’s necessary to evaluate critically.

 

• The ground subsidence vulnerability prediction model developed in this study does not provide very high accuracy. This is due to the fact that, as mentioned earlier, ground subsidence is caused by a variety of different and complex causes (engineering, physical factors, etc.). However, in reality, it is not feasible to collect data that take all variables into account. Therefore, we have proposed a ground subsidence vulnerability prediction model based on the data that can be reasonably obtained. Furthermore, the data that were obtained (underground utility attribute information) have been reported as a direct major cause of ground subsidence. Therefore, by utilizing this, it was possible to present a model for predicting ground subsidence vulnerability, and a vulnerability map for ground subsidence in the target area was created. As you pointed out, if a study were conducted to verify the actual ground subsidence in the target area, it is expected that the accuracy and reliability of the model would increase. This is part of the future research plan, and we will also compare the ground subsidence vulnerability model using machine learning in addition to the spatial regression model.

 

6. bibliography is too long.

 

• It is difficult to reduce the references as they are all necessary for the reader’s understanding of this manuscript. However, some of the older references have been deleted and replaced with references from more recent studies.

 

7. Table 2 needs to be condensed.

 

• We have condensed Table 2.

 

8. Table 4 and Table (5?) line265 in same page.

 

• We have added the title for Table 5.

 

9.Line 265; Legend of Table 5 (?).

 

• We have added the title for Table 5.

 

Author Response File: Author Response.pdf