Articles | Volume 25, issue 11
https://doi.org/10.5194/hess-25-5937-2021
https://doi.org/10.5194/hess-25-5937-2021
Research article
 | 
15 Nov 2021
Research article |  | 15 Nov 2021

Rainfall-induced shallow landslides and soil wetness: comparison of physically based and probabilistic predictions

Elena Leonarduzzi, Brian W. McArdell, and Peter Molnar

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Cited articles

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Anagnostopoulos, G. G., Fatichi, S., and Burlando, P.: An advanced process-based distributed model for the investigation of rainfall-induced landslides: The effect of process representation and boundary conditions, Water Resour. Research, 51, 7501–7523, https://doi.org/10.1002/2015WR016909, 2015. a, b
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Ayalew, L. and Yamagishi, H.: The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan, Geomorphology, 65, 15–31, 2005. a
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Short summary
Landslides are a dangerous natural hazard affecting alpine regions, calling for effective warning systems. Here we consider different approaches for the prediction of rainfall-induced shallow landslides at the regional scale, based on open-access datasets and operational hydrological forecasting systems. We find antecedent wetness useful to improve upon the classical rainfall thresholds and the resolution of the hydrological model used for its estimate to be a critical aspect.