Retrospective monitoring of slope failure event of tailings dam using InSAR time-series observations

Huizhi Duan, Yongsheng Li (), Hongbo Jiang, Qiang Li, Wenliang Jiang, Yunfeng Tian and Jingfa Zhang
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Huizhi Duan: Ministry of Emergency Management of China
Yongsheng Li: Ministry of Emergency Management of China
Hongbo Jiang: Ministry of Emergency Management of China
Qiang Li: Ministry of Emergency Management of China
Wenliang Jiang: Ministry of Emergency Management of China
Yunfeng Tian: Ministry of Emergency Management of China
Jingfa Zhang: Ministry of Emergency Management of China

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 117, issue 3, No 11, 2375-2391

Abstract: Abstract Interferometric synthetic aperture radar (InSAR) has been effectively used to monitor surface deformation in a mining area with millimeter-level accuracy. On March 27, 2022, a tailings dam failure occurred in Shanxi Province, China, causing significant damage to surrounding houses, woodland, and roads below the tailings pond. We obtained the surface deformation map of the tailings dam before the catastrophic failure using the InSAR time-series method with a full resolution of Sentinel-1 A. This paper employed a GPU-assisted InSAR processing method for 91 Sentinel-1 images in Interferometric Wide Swath (IW) mode acquired from January 8, 2019, to March 17, 2022. The InSAR results show that during the 25 months preceding the tailings dam failure, Dam-II experienced an average cumulative LOS deformation of nearly 80 mm, while Dam-I experienced a significant deformation of more than 140 mm in the LOS direction. The analysis combining the deformation and rainfall results shows that rainfall significantly affects tailings pond deformation. In general, the deformation evolution has a high correlation with the rainfall annually, but the maximum deformation rate occurs with a delay of about one month compared to the peak rainfall. InSAR technology can significantly improve the monitoring capability of tailings dam failure and other landslide disasters, but it is limited by the observation frequency of the satellite. Thus, improving the temporal resolution of SAR data may assist in predicting tailings dam failure times more accurately.

Keywords: Time-series InSAR; Sentinel-1; Tailings dam; Deformation monitoring (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11069-023-05946-7

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