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Investigation of failure prediction of open-pit coal mine landslides containing complex geological structures using the inverse velocity method

Author

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  • Han Du

    (Tsinghua University)

  • Danqing Song

    (Tsinghua University)

Abstract

The prediction of time to slope failure (TOF) is one of the most pivotal concerns for both geological risk researchers and practitioners. Conventional inverse velocity method (IVM), based on the analysis of displacement monitoring data, has become an effective method to solve this problem because it is easy to perform and the prediction results are generally acceptable. Practically, some limitations like random instrumental noise, environmental noise, and measurement error are ubiquitous factors hampered the reliability of the prediction. In this work, traditional IVM method and modified IVM with three different filters are respectively detected on velocity time series from an landslide event in an open-pit coal mine with the propose of improving, in retrospect, the accuracy of failure predictions. Simultaneously, the effects of noise on the appraisal of IVM graphics are also assessed and explanation. The results demonstrate that the sliding process of landslides can be divided into three signature stages based on the IVM. Noteworthily, the slope failure critical point occurs at the end of the progressive stage and generally coincides with a major acceleration event in which almost integrity of the slope is lost, transitioning to a linear trend ever since. Additionally, the short-term smoothing filter (SSF) and long-term smoothing filter (LSF) models can provide more accuracy and useful information about the probable failure time. Finally, with the intention of enhancing the feasible use of the method and supporting pre-determined response plans, two-level alert procedures combing SSF and LSF are proposed. Graphical abstract

Suggested Citation

  • Han Du & Danqing Song, 2022. "Investigation of failure prediction of open-pit coal mine landslides containing complex geological structures using the inverse velocity method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(3), pages 2819-2854, April.
  • Handle: RePEc:spr:nathaz:v:111:y:2022:i:3:d:10.1007_s11069-021-05159-w
    DOI: 10.1007/s11069-021-05159-w
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    References listed on IDEAS

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    1. Kun He & Guotao Ma & Xiewen Hu, 2021. "Formation mechanisms and evolution model of the tectonic-related ancient giant basalt landslide in Yanyuan County, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(3), pages 2575-2597, April.
    2. Zhuo Chen & Danqing Song, 2021. "Numerical investigation of the recent Chenhecun landslide (Gansu, China) using the discrete element method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(1), pages 717-733, January.
    3. Haoran Li & Han Du & Runcai Bai & Guangwei Liu & Mingyuan Zhao & Rongzheng Liu, 2021. "The Failure Mechanism and Stability of the End Slope of Inclined Composite Coal Seam," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-22, October.
    4. Mostafa Dastorani & Mohammad Mirzavand & Mohammad Taghi Dastorani & Seyyed Javad Sadatinejad, 2016. "Comparative study among different time series models applied to monthly rainfall forecasting in semi-arid climate condition," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(3), pages 1811-1827, April.
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    Cited by:

    1. Yan Du & Lize Ning & Santos D . Chicas & Mowen Xie, 2023. "A new early warning Criterion for assessing landslide risk," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(1), pages 537-549, March.
    2. Danqing Song & Wanpeng Shi & Chengwen Wang & Lihu Dong & Xin He & Enge Wu & Jianjun Zhao & Runhu Lu, 2023. "Numerical Investigation of a Local Precise Reinforcement Method for Dynamic Stability of Rock Slope under Earthquakes Using Continuum–Discontinuum Element Method," Sustainability, MDPI, vol. 15(3), pages 1-24, January.

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