Assessing shallow landslide hazards using the TRIGRS and SHALSTAB models, Serra do Mar, Brazil
| Autor: | Nelson Ferreira Fernandes, David R. Montgomery, Bianca Carvalho Vieira, Oswaldo Augusto Filho, Tiago Damas Martins |
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| Rok vydání: | 2018 |
| Předmět: |
010504 meteorology & atmospheric sciences
Field data 0211 other engineering and technologies Soil Science 02 engineering and technology Escarpment Structural basin Spatial distribution 01 natural sciences GEOTECNIA Environmental engineering science Environmental Chemistry Soil parameters 0105 earth and related environmental sciences Earth-Surface Processes Water Science and Technology Hydrology 021110 strategic defence & security studies Global and Planetary Change geography geography.geographical_feature_category Geology Landslide Landslide susceptibility Pollution |
| Zdroj: | Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual) Universidade de São Paulo (USP) instacron:USP |
| Popis: | The hillslopes of the Serra do Mar, a system of escarpments and mountains that extend more than 1500 km along the southern and southeastern Brazilian coast, are regularly affected by heavy rainfall that generates widespread mass movements, causing large numbers of casualties and economic losses. This paper evaluates the efficiency of susceptibility mapping for shallow translational landslides in one basin in the Serra do Mar, using the physically based landslide susceptibility models SHALSTAB and TRIGRS. Two groups of scenarios were simulated using different geotechnical and hydrological soil parameters, and for each group of scenarios (A and B), three subgroups were created using soil thickness values of 1, 2, and 3 m. Simulation results were compared to the locations of 356 landslide scars from the 1985 event. The susceptibility maps for scenarios A1, A2, and A3 were similar between the models regarding the spatial distribution of susceptibility classes. Changes in soil cohesion and specific weight parameters caused changes in the area of predicted instability in the B scenarios. Both models were effective in predicting areas susceptible to shallow landslides through comparison of areas predicted to be unstable and locations of mapped landslides. Such models can be used to reduce costs or to define potentially unstable areas in regions like the Serra do Mar where field data are costly and difficult to obtain. |
| Databáze: | OpenAIRE |
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