Combining spatial models for shallow landslides and debris-flows prediction

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Autor(es): dc.creatorGomes, Roberto Arnaldo Trancoso-
Autor(es): dc.creatorGuimarães, Renato Fontes-
Autor(es): dc.creatorCarvalho Júnior, Osmar Abílio de-
Autor(es): dc.creatorFernandes, Nelson Ferreira-
Autor(es): dc.creatorAmaral Júnior, Eurípedes Vargas do-
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Descrição: dc.descriptionMass movements in Brazil are common phenomena, especially during strong rainfall events that occur frequently in the summer season. These phenomena cause losses of lives and serious damage to roads, bridges, and properties. Moreover, the illegal occupation by slums on the slopes around the cities intensifies the effect of the mass movement. This study aimed to develop a methodology that combines models of shallow landslides and debris-flows in order to create a map with landslides initiation and debris-flows volume and runout distance. The study area comprised of two catchments in Rio de Janeiro city: Quitite and Papagaio that drained side by side the west flank of the Maciço da Tijuca, with an area of 5 km2. The method included the following steps: (a) location of the susceptible areas to landslides using SHALSTAB model; (b) determination of rheological parameters of debris-flow from the back-analysis technique; and (c) combination of SHALSTAB and FLO-2D models to delineate the areas more susceptible to mass movements. These scenarios were compared with the landslide and debris-flow event of February 1996. Many FLO-2D simulations were exhaustively made to estimate the rheological parameters from the back-analysis technique. Those rheological coefficients of single simulation were back-calculated by adjusting with area and depth of the debris-flow obtained from field data. The initial material volume in the FLO-2D simulations was estimated from SHALSTAB model. The combination of these two mathematical models, SHALSTAB and FLO-2D, was able to predict both landslides and debris-flow events. Such procedures can reduce the casualties and property damage, delineating hazard areas, to estimate hazard intensities for input into risk studies providing information for public policy and planning.-
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Publicador: dc.publisherMDPI - Multidisciplinar Digital Publishing-
Direitos: dc.rightsAcesso Aberto-
Direitos: dc.rightsRemote Sensing - © 2013 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (
Palavras-chave: dc.subjectMovimentos gravitacionais de massa-
Palavras-chave: dc.subjectModelos matemáticos-
Palavras-chave: dc.subjectDeslizamento (Geologia)-
Título: dc.titleCombining spatial models for shallow landslides and debris-flows prediction-
Tipo de arquivo: dc.typelivro digital-
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