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Probabilistic Analysis of the Landslide Hazard in Cold Regions: Considering Multiple Triggering Factors and Their Interdependence

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Abstract

This study reports a quantitative pattern of landslide hazard in cold regions, triggered by multiple climatic factors. Different machine learning models were first employed to analyze the stability of the disaster-pregnant environment of landslides. Subsequently, the temperature difference and precipitation weakening the geotechnical body were regarded as the triggering factors of landslides in cold regions, and their marginal distribution and interdependence were determined based on the copula theory to develop the joint distribution from the perspective of exceedance probability. Landslide hazard under different return periods (T = 5, 10, 20, and 50 years) was then identified in terms of the product of the permanent environment and the triggering factor. Results show that decision tree (DT)-boosting maintains high prediction for the disaster-pregnant environment, with AUC of 0.978 and 0.859, respectively, in the training and test phases, and the high susceptibility is concentrated in the central and southeastern parts of the study area. Further, the Gumbel copula keeps the smallest distance to the empirical copula, better portraying the interdependence of triggering factors. Specifically, the probability of landslide hazard decreases as the return period increases, while the intensity increases. This study provides a window to accurately capture the landslide hazard caused by fluctuations in multiple climate factors in cold regions.

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Acknowledgements

This research is supported and funded by the National Key Research and Development Program of China (2018YFC0809605). The authors are grateful for this support, and would like to thank the professors for providing the dates used in this study as well.

Funding

Funding was provided by the National Key Research and Development Program of China (Grant no. 2018YFC0809605).

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Authors and Affiliations

  1. School of Civil Engineering, Harbin Institute of Technology, No. 73 Huanghe Rd., Nangang Dist., Harbin, 150001, China

    Qiang Liu, Aiping Tang & Xiaxin Tao

  2. Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, Harbin Institute of Technology, 150090, Harbin, China

    Aiping Tang

  3. Institute of Engineering Mechanics, China Earthquake Administration, Harbin, 150090, China

    Xiaxin Tao

  4. School of Civil and Ocean Engineering, Jiangsu Ocean University, Lianyungang, 222005, China

    Delong Huang

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Correspondence to Aiping Tang.

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Liu, Q., Tang, A., Tao, X. et al. Probabilistic Analysis of the Landslide Hazard in Cold Regions: Considering Multiple Triggering Factors and Their Interdependence. Pure Appl. Geophys. 179, 4063–4077 (2022). https://doi.org/10.1007/s00024-022-03152-3

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