Time-Series Analysis of Mining-Induced Subsidence in the Arid Region of Mongolia Based on SBAS-InSAR

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

-            Can you provide more details about the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique?

-            How does it work, and what are its main advantages in monitoring surface subsidence compared to other methods?

-            How were the Sentinel-1A datasets collected and processed for this study? What specific steps were involved in the processing of the SAR data to generate time-series surface subsidence maps using the SBAS-InSAR technique?

-            Could you elaborate on the time frame covered by the analysis from 2018 to 2022? How did the researchers handle and analyse the temporal variability of surface subsidence over this period?

-            Were there any notable trends or patterns observed in the subsidence behaviour during this time?

-            What were the spatial distribution patterns of subsidence identified in the Oyu Tolgoi mining area? Were there specific regions within the mine site that experienced more pronounced subsidence compared to others? What factors may have contributed to these spatial variations?

-            You mentioned that the maximum cumulative subsidence reached -742.01 mm, with the highest annual average subsidence rate at -158.11 mm/year. Can you provide more context on these values?

-            How significant are they in terms of their potential impact on mining operations and environmental risks?

-            What were the main drivers or factors identified for the subsidence observed at the Oyu Tolgoi mining area?

-            How did variations in groundwater levels, active mining operations, and changes in surface stress contribute to the observed subsidence patterns?

-            Based on the findings of the study, what are the potential implications for mining safety and environmental conservation in the region?

-            Are there any specific recommendations or mitigation measures that could be implemented to address the ongoing subsidence issue at the Oyu Tolgoi mining area?

Author Response

Comments from Reviewer 1

Comment 1.1: Can you provide more details about the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique?

Reply: Thank you for taking the time to review this paper. We greatly appreciate your thoughtful comments that helped improve the manuscript. To explain in more detail about the SBAS-InSAR technique, the sentence in Section 3.2 has been updated in the revised manuscript as: “The SBAS-InSAR technology proposed by Berardino is a time-series InSAR method that can be used to monitor the temporal evolution of surface deformations [33].” (Page 4 Line 124-125), and “Although it can be simply understood as a combination of multiple DInSAR, SBAS-InSAR effectively minimizes spatial and temporal correlation and atmospheric disturbances, enhancing measurement accuracy and enabling time-series analysis. Compared to labor-intensive traditional geodetic surveys like leveling and GPS, which struggle with large-area surface deformation monitoring, SBAS-InSAR offers efficient, all-weather and wide-coverage deformation monitoring [34].” (Page 4 Line 125-131). Please also see response to Comment 1.2 for details.

 

Comment 1.2: How does it work, and what are its main advantages in monitoring surface subsidence compared to other methods?

Reply: Thank you for your suggestion. We greatly appreciate your valuable comments that helped improve the manuscript. To make it easier for readers to clearly understand these issues, we have updated the text and added references in Section 3.2 as: “Although it can be simply understood as a combination of multiple DInSAR, SBAS-InSAR effectively minimizes spatial and temporal correlation and atmospheric disturbances, enhancing measurement accuracy and enabling time-series analysis. Compared to labor-intensive traditional geodetic surveys like leveling and GPS, which struggle with large-area surface deformation monitoring, SBAS-InSAR offers efficient, all-weather and wide-coverage deformation monitoring [34].” (Page 4 Line 125-131).

We also revised the text of how SBAS-InSAR works: “It obtains a series of short spatial baseline interferometric pairs by setting specific temporal and spatial baseline thresholds. Then it performs differential interferometric processing on these interferometric pairs, and utilize the high-pass filtering of the temporal thresholds and the low-pass filtering of the spatial thresholds to remove atmospheric interferences, so as to get the correct unwrapped phase information. Finally, the singular value decomposition (SVD) method is employed to invert the time series deformation results based on the flexible combination of interferograms within a subset.” (Page 4 Line 132-138), and “In such situations, the SVD method can be employed to perform the singular value decomposition of coefficient matrix B, allowing for the joint solution of multiple small baseline sets.” (Page 5 Line 166-168).

 

Comment 1.3: How were the Sentinel-1A datasets collected and processed for this study? What specific steps were involved in the processing of the SAR data to generate time-series surface subsidence maps using the SBAS-InSAR technique?

Reply: Thank you for noting these. To clarify these issues, we have revised the text and added more details in Section 2.2 and Section 3.3.

We revised the text in Section 2.2: “Based on the vector files of the study area, Sentinel-1A datasets were collected from the Alaska Satellite Facility (ASF) (https://search.asf.alaska.edu/), selecting 120 well-coherent single look complex (SLC) scenes from Path 84, Frame 135 recorded in an ascending orbit, covering the entire year from 2018 to 2022. (Page 2 Line 83 - Page 3 Line 87), “… from ASF (https://scihub.copernicus.eu/gnss/#/home) …” (see details On Page 5 Line 91-93) and “… (http://gdex.cr.usgs.gov/gdex/) ...” (see details On Page 5 Line 93-95).

We have added more details in Section 3.3: “Initially, the 120 collected SAR images were imported, aligned with precise orbit files, and clipped to precisely fit the study area. After that, SBAS-InSAR processing was per-formed. Finally, the results can be visualized. The primary steps of SBAS-InSAR processing include: …” (see details on page 5 Line 174-177).

To clarify the specific step involved in the processing of the SAR data to generate time-series surface subsidence maps We have added more details in Section 3.3: “In this step, the SVD method is utilized to invert the time series deformation results and the time-series surface subsidence maps were generated in the SAR coordinate system.” (Page 5 Line 194 – Page 6 Line 196).

 

Comment 1.4: Could you elaborate on the time frame covered by the analysis from 2018 to 2022? How did the researchers handle and analyse the temporal variability of surface subsidence over this period?

Reply: Thanks. To clarify the time frame, we have revised the text in Section 2.2: “…, selecting 120 well-coherent single look complex (SLC) scenes from Path 84, Frame 135 recorded in an ascending orbit, covering the entire year from 2018 to 2022” (see details on Page 2 Line 83 - Page 3 Line 87).

To facilitate understanding of the subsidence changes over this period for readers, we have revised the text in Section 4.2: “To analyze the temporal variability of surface subsidence at the OT mine site over this period, we mapped and compared accumulated surface deformation data from January 11, 2018, to December 28, 2022 (Figure 6).” (On page 8 Line 256-258).

 

Comment 1.5: Were there any notable trends or patterns observed in the subsidence behaviour during this time?

Reply: We greatly appreciate the detailed comments towards improving the manuscript. To clarify this issue, we have further added more text of the patterns and trends of surface subsidence at the OT mine site during this period in Section 4.1: “This means the OT mine workings predominantly underwent significant subsidence with notably high rates, while a minor section of the region exhibited slight uplift during this time.” (On Page 8 Line 243-245), and “…, which means that the subsidence velocity varied among the different areas. Moreover, the subsidence velocity decreases gradually from the center outwards.” (see details on Page 8 Line 245-249).

 

Comment 1.6: What were the spatial distribution patterns of subsidence identified in the Oyu Tolgoi mining area? Were there specific regions within the mine site that experienced more pronounced subsidence compared to others? What factors may have contributed to these spatial variations?

Reply: We appreciate the comments. To clarify these issues, we have corrected and updated the text in Section 4.3: “This stratification helps in understanding the varying velocities of surface deformation and its spatial distribution patterns across different regions of the OT mine.” (Page 9 Line 290-292), “Specifically, Zone C transitions from orange at the center through yellow, green, and light blue, corresponding to Class II through Class V subsidence rates, respectively. Zones B, D, and E exhibit gradients from yellow through light blue, indicating Classes III to V.” (Page 9 Line 306-309).

We have also updated the text in Section 4.3: “Zone A, which includes the mine’s water storage and adjacent wetland areas, experiences more pronounced subsidence compared to other regions.” (Page 11 Line 338-339), and “The above factors could contribute to the spatial variations of subsidence.” (Page 9 Line 347-348).

 

Comment 1.7: You mentioned that the maximum cumulative subsidence reached -742.01 mm, with the highest annual average subsidence rate at -158.11 mm/year. Can you provide more context on these values?

Reply: Thanks for your suggestion. As suggested, we have rephrased parts of the text and added more context on these values in Section 4.1 and Section 4.2. For example, we revised the text in Section 4.1: “The satellite Line-of-Sight (LOS) velocity map (Figure 5) illustrates that red and yellow areas, which indicate negative deformation rates, signify subsidence—i.e., the ground surface moving away from the satellite.” (Page 7 Line 239-241), and “Notably, the darkest red square area on the right exhibits the highest subsidence velocity, with parts of the area experiencing an annual average subsidence velocity of -158.11 mm/year.” (Page 7 Line 249-251). We have also revised the text in Section 4.2: “…, with parts of the areas experience the cumulative subsidence of -741.01 mm over 2018 to 2022.” (see details On Page 8 Line 266-268).

 

Comment 1.8: How significant are they in terms of their potential impact on mining operations and environmental risks?

Reply: We appreciate your insightful and constructive comments and suggestions. To give a clearer understanding of this issue for readers, we have revised in Section 4.1: “Such a high rate of subsidence annually may have serious implications for infrastructure stability, mining safety and environment.” (Page 7 Line 251-252). Please also see our response to Comments 1.11.

 

Comment 1.9: What were the main drivers or factors identified for the subsidence observed at the Oyu Tolgoi mining area?

Reply: Thank you for noting this. To clarify this issue, we have revised the text in Section 5: “…, suggesting that ongoing mining activities significantly contributes to the observed sur-face subsidence.” (see details on Page 13 Line 352 – 355), “…, as mining operations likely alter surface stress and induce rock mass deformations, such as collapses and fractures [44, 45].” (see details on Page 11 Line 359-362), and “These consistent studies and reports indicate the decline in groundwater levels is also a contributing factor to surface subsidence at the mine site, as it causes subsurface rocks to expand and contract [48].” (Page 13 Line 390 – 392).

 

Comment 1.10: How did variations in groundwater levels, active mining operations, and changes in surface stress contribute to the observed subsidence patterns?

Reply: We appreciate this comment. To clarify this issue, we have revised the text in Section 5: “Supplementary Data: The study's validation and analysis of subsidence is limited by the unavailable or inconsistent availability and accuracy of measured data, GNSS data, groundwater data and mining volumes.” (Page 13 Line 415 – 417) and “…, refined mining volumes, ….” (see details on Page 13 Line 424-427).

 

Comment 1.11: Based on the findings of the study, what are the potential implications for mining safety and environmental conservation in the region?

Reply: We greatly appreciate the detailed comments towards improving the manuscript. To give the reader a clearer understanding of the potential implications for mining safety and environmental conservation in the region, we have rephrased parts of the text and added references in Section 5 as: “To mitigate the potential threats of subsidence to infrastructure stability, mining safety, water resources, and the environment, it is necessary for OT mines to adopt the following measures to reduce ongoing subsidence: continuous on-site monitoring, reinforcement of infrastructure, improved management of water resources, and reduction in groundwater extraction [50-52].” (Page n Line 427-431). Please also see our response to Comments 1.8.

 

Comment 1.12: Are there any specific recommendations or mitigation measures that could be implemented to address the ongoing subsidence issue at the Oyu Tolgoi mining area?

Reply: We appreciate your insightful and constructive comments and suggestions. To clarify this issue, we have revised the text in Section 5: “To mitigate the potential threats of subsidence to infrastructure stability, mining safety, water resources, and the environment, it is necessary for OT mines to adopt the following measures to reduce ongoing subsidence: continuous on-site monitoring, reinforcement of infrastructure, improved management of water resources, and reduction in groundwater extraction [50-52].” (see details on Page 13 Line 427-431).

 

 

Reviewer 2 Report

Comments and Suggestions for Authors

Based on 120 Sentinel-1A datasets, this study conducted surface subsidence monitoring using SBAS-InSAR technology from 2018 to 2020. It is meaningful for mining safety 23 and environmental conservation. 

However, there are some aspects that should be improved:

(1) The accuracy verification should be strengthen.  In addition PS-InSAR, other materials, such as GNSS monitoring points can be bused.

(2) The correlation between subsidence and other factors should be improved. Especially, the correlation between subsidence and groundwater levels can be improved.

(3) Now that Figure 7 exists, Figure 5 can be removed. It is a duplication.

(4) In table 1, all the Path is 84 for different scene number. This column can be deleted.

(5) The periods are 12 days for most cases, whereas there are 24 days for a few cases. Please give the reasons.

Author Response

Comments from Reviewer 2

Based on 120 Sentinel-1A datasets, this study conducted surface subsidence monitoring using SBAS-InSAR technology from 2018 to 2020. It is meaningful for mining safety 23 and environmental conservation. However, there are some aspects that should be improved:

 

Comment 2.1: The accuracy verification should be strengthen. In addition, PS-InSAR, other materials, such as GNSS monitoring points can be bused.

Reply: Thank you for taking the time to review this paper and for your positive feedback regarding our manuscript. To clarify this issue, we have revised the text in Section 4.4 and Section 5. For example, we have updated the text in Section 4.4: “Conducting field-level surveys for data validation at the OT site and obtaining usable GNSS data are extremely challenging due to stringent policies and regulations as well as lack of instrumentation deployment such as GNSS.” (Page 10 Line 319-321). We have revised in the sentence in Section 5 as: “…, measured data, available GNSS data, ...” (see details in Page 13 Line 424-427).

 

Comment 2.2: The correlation between subsidence and other factors should be improved. Especially, the correlation between subsidence and groundwater levels can be improved.

Reply: We appreciate your insightful and constructive comments and suggestions. To clarify this specific issue, the sentence in Section 5 has been updated in the revised manuscript as: “Correlating subsidence with groundwater levels is also challenged by the sporadic availability and variable accuracy of groundwater data, complicating the establishment of a direct causative relationship.” (Page 13 Line 417 – 420). Please also see our response to Comments 1.10 for more information.

 

Comment 2.3: Now that Figure 7 exists, Figure 5 can be removed. It is a duplication.

Reply: Thanks, it is a good suggestion. We have removed the original Figure 5 and repositioned Figure 7 to enhance readability in Results on Page 7.

 

Comment 2.4: In table 1, all the Path is 84 for different scene number. This column can be deleted.

Reply: Thank you for your advice. We have taken it into consideration and have deleted the column "Path" in Table 1 on Page 3.

 

Comment 2.5: The periods are 12 days for most cases, whereas there are 24 days for a few cases. Please give the reasons.

Reply: Thank you for your advice. Although Sentinel-1A has a revisit period of 12 days, not all data provide good interferometric results, resulting in some intervals being 24 days. To clarify this issue, we have updated the text in Section 2.2 as follows: “…, selecting 120 well-coherent single look complex (SLC) scenes from Path 84, Frame 135 recorded in an ascending orbit, covering the entire year from 2018 to 2022.” (see details Page 2 Line 83 - Page 3 Line 87).

 

In summary, these 4 references have been added:

[34] Li, S.; Xu, W.; Li, Z. Review of the SBAS InSAR Time-series algorithms, applications, and challenges. Geod. Geodyn. 2022, 13, 114-126. https://doi.org/10.1016/j.geog.2021.09.007.

 

[50] Sahu, P.; Lokhande, R.D. An Investigation of Sinkhole Subsidence and its Preventive Measures in Underground Coal Mining. Procedia Earth Planet. Sci. 2015, 11, 63–75. https://doi.org/10.1016/j.proeps.2015.06.009.

 

[51] Kondolf, G.M.; Schmitt, R.J.P.; Carling, P.; Darby, S.; Arias, M.; Bizzi, S.; Castelletti, A.; Cochrane, T.A.; Gibson, S.; Kummu, M.; et al. Changing sediment budget of the Mekong: Cumulative threats and management strategies for a large river basin. Sci. Total Environ. 2018, 625, 114–134. https://doi.org/10.1016/j.scitotenv.2017.11.361.

 

[51] Tang, W.; Zhao, X.; Motagh, M.; Bi, G.; Li, J.; Chen, M.; Chen, H.; Liao, M. Land Subsidence and Rebound in the Taiyuan Basin, Northern China, in the Context of Inter-Basin Water Transfer and Groundwater Management. Remote Sens. Environ. 2022, 269, 112792. https://doi.org/10.1016/j.rse.2021.112792.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have adequately addressed my comments. I recommend the publication of the revised manuscript. 

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have made corresponding revisions. If it is possible, the language, text, figures and references can be checked before acceptance.