Landslide movements triggered by rainfall can be foreseen in real-time by modelling the relationship between rainfall amount and landslide occurrence. This paper deals with the problem of the reliability of the FLAIR (Forecasting of Landslides induced by Rainfalls) model when applied to forecasting landslide movements in the usual condition of poor historical information availability. In this case, the identification of the admissibility field for the model parameters, instead of a point estimation, leads to an improvement of the forecasting reliability. Moreover, this approach makes the model capable of taking into account information embodied in periods of heavy rain but without movement. The concepts of informative content and foreseeability of landslide movements are introduced and their duality is analyzed. The effectiveness of the estimation procedure described has been tested by application on two landslides located in southern Italy. Landslide movements triggered by rainfall can be foreseen in real-time by modelling the relationship between rainfall amount and landslide occurrence. This paper deals with the problem of the reliability of the FLaIR (Forecasting of Landslides Induced by Rainfalls) model when applied to forecasting landslide movements in the usual condition of poor historical information availability. In this case, the identification of the admissibility field for the model parameters, instead of a point estimation, leads to an improvement of the forecasting reliability. Moreover, this approach makes the model capable of taking into account information embodied in periods of heavy rain but without movement. The concepts of informative content and foreseeability of landslide movements are introduced and their duality is analyzed. The effectiveness of the estimation procedure described has been tested by application on two landslides located in southern Italy.

Real-time estimation of hazard for landslides triggered by rainfall

SIRANGELO, BENIAMINO
1998-01-01

Abstract

Landslide movements triggered by rainfall can be foreseen in real-time by modelling the relationship between rainfall amount and landslide occurrence. This paper deals with the problem of the reliability of the FLAIR (Forecasting of Landslides induced by Rainfalls) model when applied to forecasting landslide movements in the usual condition of poor historical information availability. In this case, the identification of the admissibility field for the model parameters, instead of a point estimation, leads to an improvement of the forecasting reliability. Moreover, this approach makes the model capable of taking into account information embodied in periods of heavy rain but without movement. The concepts of informative content and foreseeability of landslide movements are introduced and their duality is analyzed. The effectiveness of the estimation procedure described has been tested by application on two landslides located in southern Italy. Landslide movements triggered by rainfall can be foreseen in real-time by modelling the relationship between rainfall amount and landslide occurrence. This paper deals with the problem of the reliability of the FLaIR (Forecasting of Landslides Induced by Rainfalls) model when applied to forecasting landslide movements in the usual condition of poor historical information availability. In this case, the identification of the admissibility field for the model parameters, instead of a point estimation, leads to an improvement of the forecasting reliability. Moreover, this approach makes the model capable of taking into account information embodied in periods of heavy rain but without movement. The concepts of informative content and foreseeability of landslide movements are introduced and their duality is analyzed. The effectiveness of the estimation procedure described has been tested by application on two landslides located in southern Italy.
1998
Hydrological models; Landslides forecasting; Rainfall
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/135708
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