IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v87y2017i1d10.1007_s11069-017-2773-y.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-017-2773-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-017-2773-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yinping Nie & Xiuzhen Li & Wendy Zhou & Ruichi Xu, 2021. "Dynamic hazard assessment of group-occurring debris flows based on a coupled model," 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. 106(3), pages 2635-2661, April.
    2. Kyungjin An & Suyeon Kim & Taebyeong Chae & Daeryong Park, 2018. "Developing an Accessible Landslide Susceptibility Model Using Open-Source Resources," Sustainability, MDPI, vol. 10(2), pages 1-13, January.
    3. Lorella Montrasio & Roberto Valentino & Angela Corina & Lauro Rossi & Roberto Rudari, 2014. "A prototype system for space–time assessment of rainfall-induced shallow landslides in Italy," 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. 74(2), pages 1263-1290, November.
    4. D. W. Park & S. R. Lee & N. N. Vasu & S. H. Kang & J. Y. Park, 2016. "Coupled model for simulation of landslides and debris flows at local scale," 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. 81(3), pages 1653-1682, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:87:y:2017:i:1:d:10.1007_s11069-017-2773-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.