Volume 44 Issue 1
Jan.  2025
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WANG Canxing,ZHU Jieyong,YU Congjun,et al. Risk assessment of landslide geological hazards under different rainfall conditions based on the Pearson Ⅲ curves[J]. Bulletin of Geological Science and Technology,2025,44(1):194-204 doi: 10.19509/j.cnki.dzkq.tb20230472
Citation: WANG Canxing,ZHU Jieyong,YU Congjun,et al. Risk assessment of landslide geological hazards under different rainfall conditions based on the Pearson Ⅲ curves[J]. Bulletin of Geological Science and Technology,2025,44(1):194-204 doi: 10.19509/j.cnki.dzkq.tb20230472

Risk assessment of landslide geological hazards under different rainfall conditions based on the Pearson Ⅲ curves

doi: 10.19509/j.cnki.dzkq.tb20230472
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  • Author Bio:

    E-mail:793868972@qq.com

  • Corresponding author: E-mail:zhujieyong@kmust.edu.cn
  • Received Date: 16 Aug 2023
  • Accepted Date: 01 Dec 2023
  • Rev Recd Date: 30 Nov 2023
  • Available Online: 17 Dec 2023
  • Objective

    Rainfall is one of the important factors that induce geological disasters, such as landslides and collapses, posing a great threat to the safety of people's lives and property. Therefore, it is necessary to take effective prevention and control measures as well as to avoid and relocate.

    Methods

    This study takes Yezhi Town, Weixi County, Yunnan Province as the study area, and the grid unit is used as the evaluation unit. Nine evaluation factors, including elevation, land use type, slope, aspect, elevation, landform type, engineering geological rock group, land use type, distance from river, distance from fault, and curvature were selected. The random forest algorithm and weighted information method were used to analyze the weight of evaluation factors, and a susceptibility evaluation was also made. Based on this, rainfall was selected as the risk assessment factor. By calculating and predicting the rainfall in the study area with Pearson Ⅲ curve, rainfall in the study area was predicted for every 10 years, 20 years, 50 years, and 100 years, and a risk assessment was obtained.

    Results

    According to statistics, the susceptibility assessment results are divided into four levels using the natural discontinuity method: low, medium, high, and extremely high-susceptibility areas, which account for 32.80%, 34.02%, 21.96%, and 11.22% of the study area respectively. The ROC curves were used to verify the accuracy, and the AUC value was 89.2%.

    Conclusion

    By comparing the actual investigation situation, the landslide and collapse risk assessment results under different rainfall conditions are highly consistent with the actual situation. This study provides a basis for reasonable disaster prevention and mitigation, as well as risk avoidance and relocation.

     

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