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A probabilistic model for evaluating the reliability of rainfall thresholds for shallow landslides based on uncertainties in rainfall characteristics and soil properties

Author

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  • Shiang-Jen Wu

    (National Center for High-Performance Computing)

  • Yi-Hua Hsiao

    (National Science and Technology Center for Disaster Reduction)

  • Keh-Chia Yeh

    (National Chiao Tung University)

  • Sheng-Hsueh Yang

    (National Chiao Tung University)

Abstract

This study aims to develop a probabilistic rainfall threshold estimation model for shallow landslides (PRTE_LS) in order to quantify its reliability while being affected by uncertainties in the rainfall characteristics and soil properties. The rainfall characteristics include the rainfall duration, depth and storm patterns in which their uncertainties result from temporal variation. The effective cohesion of soil, the unit weight of soil, the angle of internal friction, hydraulic conductivity and hydraulic diffusivity are the soil properties represented as the soil parameters in the TRIGRS model in which uncertainties are attributed to spatial variation. After analyzing the sensitivity of rainfall characteristics and TRIGRS parameters to the estimation of rainfall thresholds, the maximum rainfall intensity, storm pattern and soil parameters (soil cohesion, soil friction angle and total unit weight of soil) are retreated as uncertainty factors used in the model development. The proposed PRTE_LS model is used for the reliability assessment of the issued rainfall thresholds in the Jhoukou River watershed, southern Taiwan, to demonstrate its applicability. The results indicate that the corresponding exceedance probability (i.e., underestimated risk) approximates 0.1 on average. In other words, its reliability reaches 0.9. However, issued rainfall thresholds with high reliability might hardly achieve the goal of early warning because shallow landslides can possibly happen before the actual rainfall amount exceeds the threshold. Consequently, the proposed PRTE_LS model can modify issued rainfall thresholds with the specific occurrence probability under the critical safety factors and warning durations being considered. As a result, the proposed PRTE_LS can not only quantify the reliability of the issued rainfall thresholds, but its results can also be referred to in modifying the issued thresholds in order to enhance the early-warning performance.

Suggested Citation

  • Shiang-Jen Wu & Yi-Hua Hsiao & Keh-Chia Yeh & Sheng-Hsueh Yang, 2017. "A probabilistic model for evaluating the reliability of rainfall thresholds for shallow landslides based on uncertainties in rainfall characteristics and soil properties," 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. 87(1), pages 469-513, May.
  • Handle: RePEc:spr:nathaz:v:87:y:2017:i:1:d:10.1007_s11069-017-2773-y
    DOI: 10.1007/s11069-017-2773-y
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    References listed on IDEAS

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    1. Zonghu Liao & Yang Hong & Dalia Kirschbaum & Robert Adler & Jonathan Gourley & Rick Wooten, 2011. "Evaluation of TRIGRS (transient rainfall infiltration and grid-based regional slope-stability analysis)’s predictive skill for hurricane-triggered landslides: a case study in Macon County, North Carol," 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. 58(1), pages 325-339, July.
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    Cited by:

    1. Xing Zheng Wu & Chen Zhe Ma & Rui-kai Wang & Wei Chao Li, 2023. "Development of environmental contours from rainfall intensity and duration data for slopes," 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 1001-1027, March.

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