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Rainfall-induced landslides assessment in the Fengjie County, Three-Gorge reservoir area, China

Author

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  • Kai Wang

    (Northwest University
    Zhongyuan University of Technology)

  • Shaojie Zhang

    (Chinese Academy of Sciences)

Abstract

It is critical to accurately assess the location and evolution of impending landslide hazards, especially when influenced by the effects of climate change. However, most existing landslide models only analyze the stability of individual grid cells without considering soil interaction between adjacent cells. This means that the stability of individual grid cells is not necessarily representative of actual slope stability at a given location, in turn affecting the accuracy of landslide stability assessments. In this paper, slope units are defined using the morphological image analysis and homogeneous slope unit method to represent the actual slope conditions and to extract the profile of each slope unit. The critical slip surface of the soil mass is investigated to account for the interaction between adjacent grid cells within the slope unit. A probabilistic analytical landslide model is established and the response mechanism of the hydrological processes is proposed. This model is applied to landslide hazard assessment in the Three-Gorges Reservoir Area, Fengjie County, China. Using historical rainfall data, the distribution of landslide hazards is analyzed for different antecedent precipitation levels and rainfall return periods. The results show that the amount of antecedent precipitation, and rainfall return period, have different effects on landslide triggering in the area. Importantly, the model reveals that extreme rainfall events induced by climate change will lead to a large number of new landslides in areas where they are not anticipated. Further investigation and monitoring (e.g., early-warning systems, long-term assessment) of rainfall-induced landslides in the Three-Gorges Reservoir Area is recommended.

Suggested Citation

  • Kai Wang & Shaojie Zhang, 2021. "Rainfall-induced landslides assessment in the Fengjie County, Three-Gorge reservoir area, 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. 108(1), pages 451-478, August.
    • Handle: RePEc:spr:nathaz:v:108:y:2021:i:1:d:10.1007_s11069-021-04691-z
    DOI: 10.1007/s11069-021-04691-z
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    References listed on IDEAS

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    Cited by:

    1. Zhengyang Su & Guizhi Wang & Yakun Wang & Xiang Luo & Hao Zhang, 2022. "Numerical simulation of dynamic catastrophe of slope instability in three Gorges reservoir area based on FEM and SPH 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(1), pages 709-724, March.
    2. Tanmoy Das & Vansittee Dilli Rao & Deepankar Choudhury, 2022. "Numerical investigation of the stability of landslide-affected slopes in Kerala, India, under extreme rainfall event," 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. 114(1), pages 751-785, October.
    3. Junbiao Yan & Zongxing Zou & Rui Mu & Xinli Hu & Jincheng Zhang & Wen Zhang & Aijun Su & Jinge Wang & Tao Luo, 2022. "Evaluating the stability of Outang landslide in the Three Gorges Reservoir area considering the mechanical behavior with large deformation of the slip zone," 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. 112(3), pages 2523-2547, July.
    4. Tingchen Wu & Xiao Xie & Haoyu Wu & Haowei Zeng & Xiaoya Zhu, 2022. "A Quantitative Analysis Method of Regional Rainfall-Induced Landslide Deformation Response Variation Based on a Time-Domain Correlation Model," Land, MDPI, vol. 11(5), pages 1-19, May.

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