Susceptibility to shallow landslides in a drainage basin in the Serra do Mar, São Paulo, Brazil, predicted using the SINMAP mathematical model

  • Tulius Dias Nery
  • Bianca Carvalho VieiraEmail author
Original Paper


The Serra do Mar mountain range is a fault scarp with steep slopes that are often affected by shallow landslides triggered by extreme rainfall. Most of these events result in casualties and economic and environmental damage, especially in areas close to urban centers, major roadways and agricultural areas. The goal of this study was to evaluate the susceptibility to shallow landslides in the Serra do Mar, specifically within a drainage basin affected by such an event in January of 1985. For this purpose, the mathematical modeling technique of SINMAP was used by introducing the topographic values from a digital terrain model as well as geotechnical and hydrological values from previous studies performed in the Serra do Mar. In all, 32 susceptibility scenarios were generated, and three were analyzed for this study. These scenarios were validated using landslide scar maps produced using orthophotography; this technique was also used to analyze the functions of morphological parameters (e.g., slope angle, curvature and hypsometric features). The basin was classified as unstable, with landscape rates above 70 % for all three of the scenarios chosen. A higher landscape frequency was expected on straight slopes with angles between 30° and 50° under unsaturated soil conditions, as evidenced by low moisture rates, especially for N–S-facing slopes. The susceptibility maps generated using this model should prove useful for other critical parts of the Serra do Mar to understand better and, above all, predict these landslides, which annually cause significant damage in Brazil.


Serra do Mar Shallow landslides Digital terrain model SINMAP 



The authors acknowledge the support of the São Paulo Research Foundation (Fundação de Amparo à Pesquisa do Estado de São Paulo—FAPESP) for the development of this study and the granting of a Master’s thesis. The authors also thank Eymar Silva Sampaio Lopes, Paulina Setti Riedel, Antonio Carlos Colangelo, Emerson Galvani, and all of the members of the research group for their contributions and scientific discussions. This manuscript was significantly improved by the contributions made by anonymous reviewers.


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© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.National Early Warning and Monitoring Center for Natural DisastersCachoeira PaulistaBrazil
  2. 2.Graduate Program in Physical GeographyUniversity of São PauloSão PauloBrazil
  3. 3.Department of GeographyUniversity of São PauloSão PauloBrazil

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