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Deformation characteristics and stability of the Sifangbei landslide based on the shape renewal of longitudinal profile

Author

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  • Lan Xiao

    (China University of Geosciences)

  • Liang Yang

    (China University of Geosciences)

  • Yang Wang

    (China University of Geosciences)

Abstract

It is beneficial for disaster prevention and mitigation to use a numerical model to evaluate landslide stability. The Sifangbei landslide, located in the Three Gorges Reservoir Area (TGRA), is sliding slowly under the action of reservoir water. Due to the lack of early technology and funds, the depiction of the longitudinal profile and stability analysis of the landslide are very limited. In this study, the longitudinal profile of the main sliding direction was corrected from the original version of the ground model using field investigation, drilling, in situ monitoring, and geophysical observation. Then, through the establishment of numerical models, the landslide model based on the original profile is used as a reference to re-study its deformation characteristics and stability analysis. The results are as follows: The displacement response of the new model is closer to the real deformation record of the landslide. The deformation of the landslide body in the rear section and front edge is significant, even during periods of low rainfall in the reservoir storage season. According to the hydraulic mechanism, the stability changes of the two models under the influence of RWL show that there is a stronger buoyancy force of the soil mass in the front resisting section after the profile of the model is modified. The above conclusions indicate that the Sifangbei landslide is not a typical seepage-driven landslide, and its prevention and control should be updated in time. This study also provides a case for the same type of landslide and the relationship between the landslide deformation and the sliding surface shape.

Suggested Citation

  • Lan Xiao & Liang Yang & Yang Wang, 2024. "Deformation characteristics and stability of the Sifangbei landslide based on the shape renewal of longitudinal profile," 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. 120(4), pages 3677-3697, March.
    • Handle: RePEc:spr:nathaz:v:120:y:2024:i:4:d:10.1007_s11069-023-06345-8
    DOI: 10.1007/s11069-023-06345-8
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    References listed on IDEAS

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    1. Changjun Huang & Qingshan Zhou & Lv Zhou & Yuanzhi Cao, 2021. "Ancient landslide in Wanzhou District analysis from 2015 to 2018 based on ALOS-2 data by QPS-InSAR," 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. 109(2), pages 1777-1800, November.
    2. Ruchika Sharma Tandon & Vikram Gupta & Bhimala Venkateshwarlu & Pradeep Joshi, 2022. "An assessment of Dungale landslide using remotely piloted aircraft system (RPAS), ground penetration radar (GPR), and Slide & RS2 Softwares," 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. 113(2), pages 1017-1042, September.
    3. Renato Macciotta & Michael Hendry & C. Martin, 2016. "Developing an early warning system for a very slow landslide based on displacement monitoring," 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(2), pages 887-907, March.
    4. Junhui Shen & Yihang Gao & Liwang Wen & Xiaohao Jin, 2018. "Deformation response regularity of Liujiaba landslide under fluctuating reservoir water level 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. 94(1), pages 151-166, October.
    5. Renato Macciotta & Michael Hendry & C. Derek Martin, 2016. "Developing an early warning system for a very slow landslide based on displacement monitoring," 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(2), pages 887-907, March.
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