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

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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.

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Authors and Affiliations

  1. Universidad Nacional de Colombia, Manizales, Colombia

    Oscar Correa, Francisco García & Omar Darío Cardona

  2. Universidad Nacional de Colombia, Bogotá, Colombia

    Gabriel Bernal & Carlos Rodriguez

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  1. Oscar Correa
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  2. Francisco García
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  3. Gabriel Bernal
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  4. Omar Darío Cardona
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Correspondence to Omar Darío Cardona.

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Correa, O., García, F., Bernal, G. et al. Early warning system for rainfall-triggered landslides based on real-time probabilistic hazard assessment. Nat Hazards 100, 345–361 (2020). https://doi.org/10.1007/s11069-019-03815-w

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