The aim of this work is to define different triggering scenarios for shallow landslides through a physically-based approach. In particular, numerical simulations have been performed using TRIGRS model for the back-analysis of a reference landslide event, i.e. the disaster occurred in the Giampilieri area (located approximately SW of Messina in northeastern Sicily, Italy) on October 1st, 2009. The simulation results, expressed in terms of safety factor (FS), describe a temporal evolution of the slope instability substantially consistent with the real event. With regard to the spatial distribution of the slope failures, the model is able to identify quite well the 2009 landslide phenomena, since 48.5% of the source areas and 79.8% of the stable areas are correctly classified. After the calibration of the physically-based model, different triggering scenarios have been reconstructed by varying the rainfall input, on the basis of the hourly rainfall probability curves obtained through a statistical analysis of historical rainfall data. The results indicate that even rainfalls with low return period and short duration (i.e. one hour) can produce a considerable instability level, in agree with the high number of landslide/flood events recorded in the study area since the last century.

A deterministic approach for shallow landslide triggering scenarios in the southern Messina area (north-eastern Sicily, Italy)

Schilirò Luca;
2015

Abstract

The aim of this work is to define different triggering scenarios for shallow landslides through a physically-based approach. In particular, numerical simulations have been performed using TRIGRS model for the back-analysis of a reference landslide event, i.e. the disaster occurred in the Giampilieri area (located approximately SW of Messina in northeastern Sicily, Italy) on October 1st, 2009. The simulation results, expressed in terms of safety factor (FS), describe a temporal evolution of the slope instability substantially consistent with the real event. With regard to the spatial distribution of the slope failures, the model is able to identify quite well the 2009 landslide phenomena, since 48.5% of the source areas and 79.8% of the stable areas are correctly classified. After the calibration of the physically-based model, different triggering scenarios have been reconstructed by varying the rainfall input, on the basis of the hourly rainfall probability curves obtained through a statistical analysis of historical rainfall data. The results indicate that even rainfalls with low return period and short duration (i.e. one hour) can produce a considerable instability level, in agree with the high number of landslide/flood events recorded in the study area since the last century.
2015
Intense rainfall
North-eastern Sicily
Return period
Shallow landslides
Statistical analysis
TRIGRS
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/363678
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