An empirical method to forecast the effect of storm intensity on shallow landslide abundance

Jonathan D. Stock; Dino Bellugi

doi:10.4408/ijege.2011-03.b-110

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An empirical method to forecast the effect of storm intensity on shallow landslide abundance

Jonathan D. Stock·Dino Bellugi

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Abstract

We hypothesize that the number of shallow landslides a storm triggers in a landscape increases with rainfall intensity, duration and the number of unstable model cells for a given shallow landslide susceptibility model of that landscape. For selected areas in California, USA, we use digital maps of historic shallow landslides with adjacent rainfall records to construct a relation between rainfall intensity and the fraction of unstable model cells that actually failed in historic storms. We find that this fraction increases as a power law with the 6-hour rainfall intensity for sites in southern California. We use this relation to forecast shallow landslide abundance for a dynamic numerical simulation storm for California, representing the most extreme historic storms known to have impacted the state.

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Italian Journal of Engineering Geology and Environment Article

Source-reported bounding extent: 32.534156° to 42.009247° latitude; -124.409591° to -114.134768° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

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BibTeX RIS

Jonathan D. Stock, Dino Bellugi. 2011. An empirical method to forecast the effect of storm intensity on shallow landslide abundance. https://doi.org/10.4408/ijege.2011-03.b-110

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