This paper contributes to the framework of probabilistic modeling of uncertainty. Two probabilistic models for the evaluation of rainfall-induced landslide susceptibility are compared: one based on the Monte Carlo method and the other on the Point Estimate Method (PEM), accounting for the correlation between soil strength properties and using the TRIGRS model (Baum et al., 2002) to assess the Factor of Safety and the distribution of pore pressure. The results are compared in terms of: total amount of time required by the analyses, mean values of the Factor of Safety, probability distribution functions, and Probability of Failure, showing that the PEM is an efficient alternative to the Monte Carlo method, allowing to save time. This is very important, especially when the susceptibility maps are provided for regional scale analysis.
A comparison between probabilistic approaches for the evaluation of rainfall-induced landslide susceptibility at regional scale
FANELLI, GIULIA
;SALCIARINI, DIANA;TAMAGNINI, Claudio
2016
Abstract
This paper contributes to the framework of probabilistic modeling of uncertainty. Two probabilistic models for the evaluation of rainfall-induced landslide susceptibility are compared: one based on the Monte Carlo method and the other on the Point Estimate Method (PEM), accounting for the correlation between soil strength properties and using the TRIGRS model (Baum et al., 2002) to assess the Factor of Safety and the distribution of pore pressure. The results are compared in terms of: total amount of time required by the analyses, mean values of the Factor of Safety, probability distribution functions, and Probability of Failure, showing that the PEM is an efficient alternative to the Monte Carlo method, allowing to save time. This is very important, especially when the susceptibility maps are provided for regional scale analysis.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
