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

被引:0
|
作者
Zhang Z. [1 ]
Zhang J. [2 ]
Zhang H. [1 ]
Du Y. [1 ]
Yan S. [1 ]
机构
[1] MNR Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou
[2] Henan No.5 Institute of Resources and Environment Investigation, Zhengzhou
基金
中国国家自然科学基金;
关键词
DS-InSAR; goaf; middle route of South-North Water Diversion Project; remote sensing; risk indicator; surface deformation monitoring;
D O I
10.11834/jrs.20242229
中图分类号
学科分类号
摘要
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. © 2024 Science Press. All rights reserved.
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页码:900 / 910
页数:10
相关论文
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