Towards a global database of rainfall-induced landslide inventories: first insights from past and new events

crossref(2018)

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摘要
Abstract. Rainfall-induced landslides are a common and significant source of damage and fatality worldwide. Still, we have very little understanding of the quantity and properties of landsliding that can be expected for a given storm and a given landscape, mostly because we have very few datasets of rainfall-induced landslides. Here we present six new comprehensive landslide inventories associated to well identified rainfall events. Combining these datasets, with two previously published datasets, we study their statistical properties and their relations to topographic slope distribution and storm properties. Landslide metrics (such as total landsliding, peak landslide density or landslide distribution area) vary across 2 to 3 order of magnitudes but strongly correlate with the storm total rainfall, varying over almost 2 orders of magnitude for these events. Correlation increases when we apply a normalization on the landslide runout distances. The non-linear scaling with total rainfall should be further constrained with additional cases and incorporation of landscape properties such as regolith depth, typical strength or permeability estimates. We also observe that, for storm with longer duration, landslides do not occur preferentially on the steepest slopes of the landscape, contrarily to observations from earthquake-induced landslides, suggesting preferential failures of larger drainage area patches with intermediate slopes. The database could be used for further comparison with spatially resolved rainfall estimates and with empirical or mechanistic landslide event modeling.
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