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

Shiang Jen Wu*, Yi Hua Hsiao, Keh Chia Yeh, Sheng Hsueh Yang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

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.

Original languageEnglish
Pages (from-to)469-513
Number of pages45
JournalNatural Hazards
Volume87
Issue number1
DOIs
StatePublished - 1 May 2017

Keywords

  • Exceedance probability
  • Rainfall threshold
  • Shallow landslide
  • TRIGRS model
  • Uncertainty analysis

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