In the last years, many hydrogeological emergencies, induced by persistent and widespread rainfall events, concerned Calabria region (southern Italy), in particular during the winter season. Flood and landslide events undermined the safety of tens of thousands of people. These events, related to the period 2008-2010, are comparable, or even worse, with those occurred in the 50’s and in the early 70’s. The proposed study regards the analysis of triggering conditions for landslides induced by rainfall. For this topic, many models are reported in the technical literature, which allow the definition of instability conditions for a slope, through an accurate investigation. (MONTGOMERY & DIETRICH, 1994; IVERSON, 2000; GUZZETTI, 2008; CEPEDA et al., 2010). In particular, this work describes an hydrological approach for the trigger modeling of landslides, and the applications related to the provinces of Catanzaro, Vibo Valentia and Crotone. For each investigated province, a lot of landslide events have been documented, characterized by different kinematic, lithological and morphological conditions, but the same triggering factor, the rainfall. The analysis was carried out by using the hydrological model named FLaIR (Forecasting of Landslides Induced by Rainfalls, SIRANGELO & VERSACE, 1992), for which some improvements were realized in the last years. Each landslide area was investigated, and then regionalization techniques were developed, aimed at the definition of transfer functions, parameters and rainfall thresholds representative of each province. The obtained results allow to apply the FLaIR model also in areas characterized by a lack of information for the past mobilization events.

Development of an hydrological landslide model at regional scale. Applications in the central part of Calabria region (southern Italy) / Capparelli, G; DE LUCA, DAVIDE LUCIANO; Versace, P.. - In: RENDICONTI ONLINE DELLA SOCIETÀ GEOLOGICA ITALIANA. - ISSN 2035-8008. - 21:1(2012), pp. 567-568.

Development of an hydrological landslide model at regional scale. Applications in the central part of Calabria region (southern Italy)

Capparelli G;DE LUCA, DAVIDE LUCIANO;Versace P.
2012

Abstract

In the last years, many hydrogeological emergencies, induced by persistent and widespread rainfall events, concerned Calabria region (southern Italy), in particular during the winter season. Flood and landslide events undermined the safety of tens of thousands of people. These events, related to the period 2008-2010, are comparable, or even worse, with those occurred in the 50’s and in the early 70’s. The proposed study regards the analysis of triggering conditions for landslides induced by rainfall. For this topic, many models are reported in the technical literature, which allow the definition of instability conditions for a slope, through an accurate investigation. (MONTGOMERY & DIETRICH, 1994; IVERSON, 2000; GUZZETTI, 2008; CEPEDA et al., 2010). In particular, this work describes an hydrological approach for the trigger modeling of landslides, and the applications related to the provinces of Catanzaro, Vibo Valentia and Crotone. For each investigated province, a lot of landslide events have been documented, characterized by different kinematic, lithological and morphological conditions, but the same triggering factor, the rainfall. The analysis was carried out by using the hydrological model named FLaIR (Forecasting of Landslides Induced by Rainfalls, SIRANGELO & VERSACE, 1992), for which some improvements were realized in the last years. Each landslide area was investigated, and then regionalization techniques were developed, aimed at the definition of transfer functions, parameters and rainfall thresholds representative of each province. The obtained results allow to apply the FLaIR model also in areas characterized by a lack of information for the past mobilization events.
Empirical regional modeling; Forecasting of landslides; Rainfall
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/167524
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