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Early warning system for rainfall-triggered landslides based on real-time probabilistic hazard assessment

Author

Listed:
  • Oscar Correa

    (Universidad Nacional de Colombia)

  • Francisco García

    (Universidad Nacional de Colombia)

  • Gabriel Bernal

    (Universidad Nacional de Colombia)

  • Omar Darío Cardona

    (Universidad Nacional de Colombia)

  • Carlos Rodriguez

    (Universidad Nacional de Colombia)

Abstract

A methodology to define rainfall-landslide thresholds, using a probabilistic model in which the accumulated rainfall at any time is treated as a random variable, is proposed. The region under study is divided into areas of homogeneous rain hazard. For each homogeneous area, a probability model is fitted using state-of-the-art statistical methods, for each accumulation time considered. Thresholds are obtained by the definition of confidence intervals. Instantaneous accumulated rains, measured in real-time, are used to calculate the instantaneous probabilities of a landslide at each area and accumulation time. The maximum instantaneous probability determines the critical accumulated rain and sets the issued warning level. In addition, the model is tested, retrospectively, with the data for the disaster of April 19, 2017, in Manizales, Colombia, where 38 rainfall-triggered landslides killed 17 people and affected more than 3126 families.

Suggested Citation

  • Oscar Correa & Francisco García & Gabriel Bernal & Omar Darío Cardona & Carlos Rodriguez, 2020. "Early warning system for rainfall-triggered landslides based on real-time probabilistic hazard assessment," 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. 100(1), pages 345-361, January.
    • Handle: RePEc:spr:nathaz:v:100:y:2020:i:1:d:10.1007_s11069-019-03815-w
    DOI: 10.1007/s11069-019-03815-w
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    Cited by:

    1. David N. Nguyen & Yuichiro Usuda & Fumihiko Imamura, 2024. "Gaps in and Opportunities for Disaster Risk Reduction in Urban Areas Through International Standardization of Smart Community Infrastructure," Sustainability, MDPI, vol. 16(21), pages 1-13, November.
    2. Alfonso Gutierrez-Lopez, 2021. "A Robust Gaussian variogram estimator for cartography of hydrological extreme events," 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. 107(2), pages 1469-1488, June.

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