Identification of the affected areas by mass movement through a physically based model of landslide hazard combined with an empirical model of debris flow |
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Authors: | Roberto A T Gomes Renato F Guimarães Osmar A Carvalho Jr Nelson F Fernandes Eurípedes A Vargas Jr Éder S Martins |
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Institution: | (1) Departamento de Geografia, Instituto de Geociências, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil;(2) Departamento de Geografia, Instituto de Humanas, Universidade de Brasília, Campus Darcy Ribeiro, Asa Norte, Brasilia, CEP 70910-900, Brazil;(3) Departamento de Engenharia Civil, Pontifícia Universidade Católica, Rio de Janeiro, Brazil;(4) Pedologia, EMBRAPA Cerrados, Planaltina, Distrito Federal, Brazil |
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Abstract: | In tropical areas, mass movements are common phenomena, especially during periods of heavy rainfall, which frequently take
place in the summer season. These phenomena have caused loss of life and serious damage to infrastructure and properties.
The most prominent of these phenomena are landslides that can produce debris flows. Thus, this article aims at determining
affected areas using a model to predict landslide prone areas (SHALSTAB) combined with an empirical model designed to define
the debris flow travel distance and area of deposition. The methodology of this work consists of the following steps: (a)
elaboration of a digital elevation model (DEM), (b) application of the deterministic SHALSTAB model to locate the landslide
prone areas, (c) identification of the debris flow travel distance and area of deposition, and (d) mapping of the affected
areas (landslides and debris flows). This work was developed in an area in which many mass movements occurred after intense
rainfall during the summer season (February 1996) in the state of Rio de Janeiro, southeast Brazil. All of the scars produced
by that event were mapped, allowing for validation of the applied models. The model results show that the mapped landslide
locations can adequately be simulated by the model. |
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Keywords: | Landslide prediction Topographic DEM Debris flow GIS |
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