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Monitoring and risk analysis of surface subsidence in the Jiaozuo Goaf along the middle route of the South-to-North Water Diversion Project based on the DS-InSAR method

  • role： First author第一作者
  • Affiliation：

    MNR Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China

  • Email：ts21160055a31ld@cumt.edu.cn
  • Introduction：张子彦，研究方向为InSAR技术应用。E-mail： ts21160055a31ld@cumt.edu.cn
ZHANG Ziyan1,  
  • Affiliation：

    Henan No.5 Institute of Resources and Environment Investigation, Zhengzhou 450053, China

ZHANG Jingkai2,  
  • Affiliation：

    MNR Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China

ZHANG Haolei1,  
  • Affiliation：

    MNR Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China

DU Yuling1,  
  • role： Corresponding author通信作者
  • Affiliation：

    MNR Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China

  • Email：yanshiyong@cumt.edu.cn
  • Introduction：闫世勇，研究方向为InSAR形变监测与环境灾害遥感。E-mail： yanshiyong@cumt.edu.cn
YAN Shiyong1*

résumé

As a national strategic project, the middle route of the South-to-North Water Diversion Project (SNWDP) is important for optimizing water resource allocation and promoting regional coordinated development in China. Unfortunately, the main canal of the middle route traverses a mining area in Jiaozuo. The massive surface subsidence caused by goafs left by coal mining has destroyed surrounding infrastructure and led to national economic losses. Deformation monitoring of the Jiaozuo section along the middle route of the SNWDP must be performed, and the threat of mining subsidence to the main channel should be assessed.The land surface of the Jiaozao Goaf is mostly covered with farmland and bare soil. Thus, obtaining a sufficient number of high coherence measurement points via traditional time series InSAR (TS-InSAR) is difficult. Consequently, TS-InSAR, which integrates PS and DS data (DS-InSAR), was used in this study. The TS-InSAR method benefits from homogeneous identification given its two-sample T-hypotheses and interferometric phase optimization based on an “eigen-decomposition-based maximum likelihood estimator” (EMI). The integration can efficiently improve the gathering of the spatial distribution density of measurement points with the help of a large number of scattered points. Particularly for this research, the spatiotemporal distribution of surface deformation in the Jiaozuo Goaf region from 2019 to 2020 was obtained from 54 Sentinel-1A images. Then, on the basis of the deformation monitoring results, a risk assessment indicator of deformation along the SNWDP that considers deformation and distance factors was developed. The index calculation results indicate that the study area can be divided into four grades according to the threat level of surface deformation to the main channel of the middle route of the SNWDP.The results further revealed several subsidence basins in the Jiaozuo Goaf that are distributed along the main canal of the middle route of the SNWDP. The maximum subsidence is 180 mm, and the maximum deformation rate is approximately -125 mm/a. The deformation of most subsidence centers has a continuous subsidence trend, but no evidence can prove that the boundaries of the subsidence basins would expand to the main channel of the SNWDP. The results of risk grading based on risk assessment indicators also revealed the presence of no-risk and low-risk areas along the main canal of the SNWDP, accompanied by a small number of medium- to high-risk areas.Overall, DS-InSAR can obtain sufficient observation points and realize fine deformation monitoring of mining areas within the SNWDP and Jiaozuo. The Jiaozuo section of the middle route of the SNWDP is less affected by mining subsidence, while high-deformation risk areas exist in the northwestern mines in Zhangtun, Baizhuang, and Zhongmacun. High-risk areas need to be continuously monitored to prevent potential subsidence hazards. The spatial distribution of medium- to high-risk areas is in good agreement with the results of the deformation analysis. Therefore, the risk indicator based on deformation and distance factors proposed in this study has good research value and can provide a scientific basis for disaster risk assessment of the SNWDP. Future research may include exploring hydrogeological factors and optimizing risk assessment indicators to improve the accuracy of deformation risk evaluation results under complex geological conditions.

mots-clés

remote sensing;goaf;DS-InSAR;Surface deformation monitoring;middle route of South-North Water Diversion Project;risk indicator

References

  1. 1.
    Ansari H, De Zan F and Bamler R. 2018. Efficient phase estimation for interferogram stacks. IEEE Transactions on Geoscience and Remote Sensing, 56(7): 4109-4125
  2. 2.
    Berardino P, Fornaro G, Lanari R and Sansosti E. 2002. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Transactions on Geoscience and Remote Sensing, 40(11): 2375-2383
  3. 3.
    Dong J, Lai S J, Wang N, Wang Y A, Zhang L and Liao M S. 2021. Multi-scale deformation monitoring with Sentinel-1 InSAR analyses along the Middle Route of the South-North Water Diversion Project in China. International Journal of Applied Earth Observation and Geoinformation, 100: 102324
  4. 4.
    Dong J J, Li X, Mei Y and Liu S Y. 2022. D-InSAR monitoring of site stability for surface substation above old mine goaf. Journal of Mining and Safety Engineering, 39(1): 62-71
  5. 5.
    Du Z Y, Ge L L, Ng A H M, Lian X G, Zhu Q G Z, Horgan F G and Zhang Q. 2021. Analysis of the impact of the South-to-North water diversion project on water balance and land subsidence in Beijing, China between 2007 and 2020. Journal of Hydrology, 603: 126990
  6. 6.
    Fan H D, Gu W, Qin Y, Xue J Q and Chen B Q. 2014. A model for extracting large deformation mining subsidence using D-InSAR technique and probability integral method. Transactions of Nonferrous Metals Society of China, 24(4): 1242-1247
  7. 7.
    Ferretti A, Prati C and Rocca F. 2001. Permanent scatterers in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 39(1): 8-20
  8. 8.
    Jiang J X, Du Y L, Chen Y, Liu G and Yan S Y. 2021. Monitoring and analysis of surface deformation in Peibei mining region based on DS-InSAR technique. Bulletin of Surveying and Mapping, (2): 117-121
  9. 9.
    Li Y. 2019. Long Time-Series InSAR Surface Deformation Monitoring with Distributed Scatterers in Mining Area. Xuzhou: China University of Mining and Technology
  10. 10.
    Li Y X. 2016. Cause and activity analysis of the Baizhuang ground fissure for the South-to-North Water Transfer Project. South-to-North Water Transfers and Water Science Technology, 14(4): 173-178
  11. 11.
    Lu L. 2020. Study on DS-InSAR Method for Monitoring Time-Series Surface Deformation in Mining Area. Xuzhou: China University of Mining and Technology
  12. 12.
    Ma C, Qu C Y and Meng X J. 2014. Embankment stability of the north Henan section of Middle Route Project (MRP) of South-to-North Water Diversion based on InSAR time series analysis. Seismology and Geology, 36(3): 749-762
  13. 13.
    Ma L, Wu J, Liu Z Y, Bi Y L, Peng S P and Xue F. 2022. Slope stability analysis of external dump in Hongshaquan Open-pit Coal Mine. Coal Engineering, 54(3): 12-16
  14. 14.
    Osmanoğlu B, Sunar F, Wdowinski S and Cabral-Cano E. 2016. Time series analysis of InSAR data: methods and trends. ISPRs Journal of Photogrammetry and Remote Sensing, 115: 90-102
  15. 15.
    Shamshiri R, Nahavandchi H, Motagh M and Hooper A. 2018. Efficient ground surface displacement monitoring using Sentinel-1 data: integrating distributed scatterers (DS) identified using two-sample t-test with persistent scatterers (PS). Remote Sensing, 10(5): 794
  16. 16.
    Tian F. 2020. Application Research of Time Series InSAR Technology in Deformation Monitoring of Central Line Project of South-to-North Water Diversion. Xi’an: Xi’an University of Science and Technology (田凡. 2020. 时序InSAR技术在南水北调中线形变监测中的应用研究. 西安: 西安科技大学) [DOI: 10.27397/d.cnki.gxaku.2020.000278]
  17. 17.
    Wang G J, Xie M W, Qiu C and Esaki T. 2010. Application of D-INSAR technique to landslide monitoring. Rock and Soil Mechanics, 31(4): 1337-1344
  18. 18.
    Wang H J. 2021-07-22(006). A total of 40 billion cubic meters of water has been transferred from the middle route of the South-to-North Water Diversion Project. CPPCC Daily
  19. 19.
    Wang Y S and Yang Y Y. 2005. South-to-North Water Transfer project of China. Yangtze River, 36(7): 2-5
  20. 20.
    Xie M W, Wang Z F, Hu M and Huang J H. 2012. The characteristic analysis of D-InSAR data for landslides monitoring in alpine and canyon region. Bulletin of Surveying and Mapping, 4: 18-21, 40
  21. 21.
    Xu D B, Feng H and Yan S Y. 2020. Deformation monitoring for structural health of Xiaolangdi Dam with Sentinel-1A based on DS-InSAR. China Rural Water and Hydropower, (6): 165-170
  22. 22.
    Yang J W, Tan Z X and Deng K Z. 2021. Deformation monitoring and law analysis of railway in mining area based on DS-InSAR. Coal Engineering, 53(9): 143-148
  23. 23.
    Yang L Y, Zhao C Y and Yang C S. 2020. Three-dimensional time series movement analysis of the Cuolangma glacier with PO-SBAS technique. Progress in Geophysics, 35(6): 2116-2123
  24. 24.
    Zhang Y G, Tian F, Li Y C and Liu H J. 2021. Application of time series InSAR to deformation monitoring in central line Project of South-to-North Water Transfer. Journal of Yangtze River Scientific Research Institute, 38(8): 72-77
  25. 25.
    Zhao M, Cai Y J, Guo W, Zhu Y J, Li F and Zhao F L. 2007. Land surface deformation characteristics in Jiaozuo cool mining area on middle route of S-N water transfer. Yangtze River, 38(9): 52-54, 71

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