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

Duan, Huizhi; Li, Yongsheng; Jiang, Hongbo; Li, Qiang; Jiang, Wenliang; Tian, Yuan; Zhang, Jingfa

doi:10.1007/s11069-023-05946-7

Cited by 9 publications

(6 citation statements)

References 38 publications

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“…He discovered that the average deformational volume of the dams is related to the amount of rainfall, and that throughout the summer and fall, when rainfall is heavier and the tailings dam deforms more, the deformational volume of the dams rises. Changes in the water content of tailings ponds and tailings structures result in seasonal movements that have a substantial impact on slope stability [ 7 ]. Gama (2020) analyzed the deformation of the tailings ponds of the Córrego do Feijão mine in Brazil and the causes of the dam failure.…”

Section: Discussionmentioning

confidence: 99%

“…Lyu (2019) compiled information on tailings dam failures around the globe and found that the primary causes of tailings dam failures are seepage, foundation failure, roofing, and earthquakes, with rainfall being the primary cause of the first three [79]. Duan (2023) analyzed the causes of tailings dam failures at a total of Shanxi Daoer Aluminum tailings dams using Sentinel-1 data. He discovered that the average deformational volume of the dams is related to the amount of rainfall, and that throughout the summer and fall, when rainfall is heavier and the tailings dam deforms more, the deformational volume of the dams rises.…”

Section: Cause Analysis Of the Deformation In Dexing No4 Tailings Dammentioning

confidence: 99%

“…Shanxi Daoer Aluminum (Lvliang City, Shanxi Province) experienced a dam failure on 27 March 2022 due to the phenomenon of “melting and sinking” of the dam soil, caused by spring warming and rainfall, and a decrease in the dam’s load-bearing capacity. The accident caused the direct burial of a portion of a business’s facility, more than 200 m of seasonal ditches, and rural roadways directly beneath the tailings pond [ 7 ]. Globally, an average of two to five large tailings ponds fail annually, according to statistics [ 8 ], and the probability of tailings pond failure is approximately ten times that of reservoir dam failure [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, monitoring the stability of tailings dams is essential for the safety of tailings ponds and the long-term development of mines [10]. Agua Dulce, Potosí, Bolivia silver, zinc illegal mineshaft [13] 27 March 2022 Wenquan Township, Jiaokou County, Shanxi Province, China bauxite the rainfall reduced the stability of the dam and caused tailings dam failure [7] 20 January 2022…”

Section: Introductionmentioning

confidence: 99%

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SBAS-InSAR Based Deformation Monitoring of Tailings Dam: The Case Study of the Dexing Copper Mine No.4 Tailings Dam

Xie,

Wu,

Gao

et al. 2023

Sensors

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The No.4 tailings pond of the Dexing Copper Mine is the second largest in Asia. The tailing pond is a dangerous source of man-made debris flow with high potential energy. In view of the lack of effective and low-cost global safety monitoring means in this region, in this paper, the time-series InSAR technology is innovatively introduced to monitor the deformation of tailings dam and significant key findings are obtained. First, the surface deformation information of the tailings pond and its surrounding areas was extracted by using SBAS-InSAR technology and Sentinel-1A data. Second, the cause of deformation is explored by analyzing the deformation rate, deformation accumulation, and three typical deformation rate profiles of the representative observation points on the dam body. Finally, the power function model is used to predict the typical deformation observation points. The results of this paper indicated that: (1) the surface deformation of the tailings dam can be categorized into two directions: the upper portion of the dam moving away from the satellite along the Line of Sight (LOS) at a rate of −40 mm/yr, whereas the bottom portion approaching the satellite along the LOS at a rate of 8 mm/yr; (2) the deformation of the dam body is mainly affected by the inventory deposits and the construction materials of the dam body; (3) according to the current trend, deformation of two typical observation points in the LOS direction will reach the cumulative deformation of 80 mm and −360 mm respectively. The research results can provide data support for safety management of No.4 tailings dam in the Dexing Copper Mine, and provide a method reference for monitoring other similar tailings dams.

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Section: Discussionmentioning

confidence: 99%

Section: Cause Analysis Of the Deformation In Dexing No4 Tailings Dammentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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SBAS-InSAR Based Deformation Monitoring of Tailings Dam: The Case Study of the Dexing Copper Mine No.4 Tailings Dam

Xie,

Wu,

Gao

et al. 2023

Sensors

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“…Cloud computing can more effectively tackle these challenges by offering on-demand access to a shared pool of computing resources, allowing users to leverage the capabilities of distributed computing and storage without requiring substantial upfront investments in hardware and software infrastructure [16][17][18]. We employed the AI Earth cloud platform to develop an InSAR processing system, which integrated the platform's massive SAR remote sensing data and the advantages of cloud computing with our automated, high-performance InSAR processing algorithms [19], aiming at measuring surface deformation around glacial lakes efficiently.…”

Section: Introductionmentioning

confidence: 99%

Retrospective Analysis of Glacial Lake Outburst Flood (GLOF) Using AI Earth InSAR and Optical Images: A Case Study of South Lhonak Lake, Sikkim

Yu,

Li,

et al. 2024

Remote Sensing

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On 4 October 2023, a glacier lake outburst flood (GLOF) occurred at South Lhonak Lake in the northwest of Sikkim, India, posing a severe threat to downstream lives and property. Given the serious consequences of GLOFs, understanding their triggering factors is urgent. This paper conducts a comprehensive analysis of optical imagery and InSAR deformation results to study changes in the surrounding surface of the glacial lake before and after the GLOF event. To expedite the processing of massive InSAR data, an InSAR processing system based on the SBAS-InSAR data processing flow and the AI Earth cloud platform was developed. Sentinel-1 SAR images spanning from January 2021 to March 2024 were used to calculate surface deformation velocity. The evolution of the lake area and surface variations in the landslide area were observed using optical images. The results reveal a significant deformation area within the moraine encircling the lake before the GLOF, aligning with the area where the landslide ultimately occurred. Further research suggests a certain correlation between InSAR deformation results and multiple factors, such as rainfall, lake area, and slope. We speculate that heavy rainfall triggering landslides in the moraine may have contributed to breaching the moraine dam and causing the GLOF. Although the landslide region is relatively stable overall, the presence of a crack in the toparea of landslide raises concerns about potential secondary landslides. Our study may improve GLOF risk assessment and management, thereby mitigating or preventing their hazards.

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Application of Sentinel-1 InSAR to monitor tailings dams and predict geotechnical instability: practical considerations based on case study insights

Rana,

Delaney,

Evans

et al. 2024

Bull Eng Geol Environ

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Tailings storage facilities (TSFs) impound mining waste behind dams to ensure public safety, but failure incidents have prompted calls for more robust monitoring programs. Satellite-based interferometric synthetic aperture radar (InSAR) has grown in popularity due to its ability to remotely detect millimeter-scale displacements in most urban and some natural terrains. However, there remains a limited understanding of whether InSAR can be as accurate or representative as on-the-ground instruments, whether failures can be predicted in advance using InSAR, and what variables govern the quality and reliability of InSAR results. To address these gaps, we analyze open-source, medium-resolution Sentinel-1 data to undertake a ground-truth assessment at a test site and a forensic analysis of five failure cases. We use a commercial software with an automated Persistent Scatterer (PS) workflow (SARScape Analytics) for all case study sites except one and a proprietary algorithm (SqueeSAR) with a dual PS and Distributed Scatterer (DS) algorithm for the ground-truth site and one forensic case. The main goal is to deliver practical insights regarding the influence of algorithm/satellite selection, environmental conditions, site activity, coherence thresholds, satellite-dam geometry, and failure modes. We conclude that Sentinel-1 InSAR can serve as a hazard-screening tool to help guide where to undertake targeted investigations; however, most potential failure modes may not exhibit InSAR-detectable accelerations that could assist with time-of-failure prediction in real time. As such, long-term monitoring programs should ideally be integrated with a combination of remote sensing and field instrumentation to best support engineering practice and judgment.

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

Cited by 9 publications

References 38 publications

SBAS-InSAR Based Deformation Monitoring of Tailings Dam: The Case Study of the Dexing Copper Mine No.4 Tailings Dam

SBAS-InSAR Based Deformation Monitoring of Tailings Dam: The Case Study of the Dexing Copper Mine No.4 Tailings Dam

Retrospective Analysis of Glacial Lake Outburst Flood (GLOF) Using AI Earth InSAR and Optical Images: A Case Study of South Lhonak Lake, Sikkim

Application of Sentinel-1 InSAR to monitor tailings dams and predict geotechnical instability: practical considerations based on case study insights

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