In this paper, we present preliminary results of the IPL project No. 198 “Multi-scale rainfall triggering models for Early Warning of Landslides (MUSE).” In particular, we perform an assessment of the geotechnical and hydrological parameters affecting the occurrence of landslides. The aim of this study is to improve the reliability of a physically based model high resolution slope stability simulator (HIRESSS) for the forecasting of shallow landslides. The model and the soil characterization have been tested in Northern Tuscany (Italy), along the Apennine chain, an area that is historically affected by shallow landslides. In this area, the main geotechnical and hydrological parameters controlling the shear strength and permeability of soils have been determined by in situ measurements integrated by laboratory analyses. Soil properties have been statistically characterized to provide more refined input data for the slope stability model. Finally, we have tested the ability of the model to predict the occurrence of shallow landslides in response to an intense meteoric precipitation.

Soil characterization for shallow landslides modeling: a case study in the Northern Apennines (Central Italy)

Catani F.
Funding Acquisition
2017

Abstract

In this paper, we present preliminary results of the IPL project No. 198 “Multi-scale rainfall triggering models for Early Warning of Landslides (MUSE).” In particular, we perform an assessment of the geotechnical and hydrological parameters affecting the occurrence of landslides. The aim of this study is to improve the reliability of a physically based model high resolution slope stability simulator (HIRESSS) for the forecasting of shallow landslides. The model and the soil characterization have been tested in Northern Tuscany (Italy), along the Apennine chain, an area that is historically affected by shallow landslides. In this area, the main geotechnical and hydrological parameters controlling the shear strength and permeability of soils have been determined by in situ measurements integrated by laboratory analyses. Soil properties have been statistically characterized to provide more refined input data for the slope stability model. Finally, we have tested the ability of the model to predict the occurrence of shallow landslides in response to an intense meteoric precipitation.
2017
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3384557
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