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The RUSLE erosion index as a proxy indicator for debris flow susceptibility

TitoloThe RUSLE erosion index as a proxy indicator for debris flow susceptibility
Tipo di pubblicazioneArticolo su Rivista peer-reviewed
Anno di Pubblicazione2015
AutoriZini, A., Grauso S., Verrubbi Vladimiro, Falconi Luca, Leoni G., and Puglisi Claudio
RivistaLandslides
Volume12
Paginazione847-859
ISSN1612510X
Parole chiaveabiotic factor, Debris, debris flow, Debris flows, Debris-flow susceptibilities, Erosion, hazard assessment, human activity, Hydraulic models, hydraulics, index method, Inherent characteristics, Italy, Landslide, Logistic regression analysis, Logistic regressions, Model validation, parameterization, Rain, Regression analysis, Revised Universal Soil Loss Equation, Revised universal soil loss equations, RUSLE, Sediment transport, Sicily, Soil erosion, Soils, Statistical mechanics, vulnerability
Abstract

Debris flows represent dangerous occurrences in many parts of the world. Several disasters are documented due to this type of fast-moving landslides; therefore, natural-hazard assessment of debris flows is crucial for safety of life and property. To this aim, much current work is being directed toward developing geotechnical-hydraulic models for the evaluation of debris flow susceptibility. A common base for such current models is parameterization of background predisposing and triggering factors such as inherent characteristics of geo-materials, topography, landscape and vegetation cover, rainfall regime, human activities, etc. which influence the occurrence of these processes on slopes. The same factors are also taken into account in soil erosion prediction models. Consequently, it seems worth investigating the effectiveness of the soil erosion index as debris flows susceptibility indicator. To this aim, a logistic regression analysis was carried out between the erosion index assessed by means of the Revised Universal Soil Loss Equation (RUSLE) model and the inventory of debris flows that have occurred in an area in Sicily (Southern Italy). Model assumptions were verified and validated by means of a series of statistical tools. Different possible scenarios were also evaluated by considering hypothetical changes in soil erosion rate under different rain erosivity conditions. Notwithstanding the rough approximations in model data collection, the outcomes appear encouraging. © 2014, Springer-Verlag Berlin Heidelberg.

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URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84942876612&doi=10.1007%2fs10346-014-0515-8&partnerID=40&md5=06bb7290c7c2ae2660c0c9cbdd7a0799
DOI10.1007/s10346-014-0515-8
Citation KeyZini2015847