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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Assessing shallow landslide hazards using the TRIGRS and SHALSTAB models, Serra do Mar, Brazil

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Author(s):
Vieira, Bianca Carvalho [1] ; Fernandes, Nelson Ferreira [2] ; Augusto Filho, Oswaldo [3] ; Martins, Tiago Damas [4] ; Montgomery, David R. [5]
Total Authors: 5
Affiliation:
[1] Univ Sao Paulo, Dept Geog, Ave Prof Lineu Prestes 338 Cidade Univ, BR-05508080 Sao Paulo - Brazil
[2] Univ Fed Rio de Janeiro, Dept Geog, Ilha Fundao, BR-21945970 Rio De Janeiro, RJ - Brazil
[3] Univ Sao Paulo, Sao Carlos Sch Engn, Ave Trabalhador Sao Carlense 400, BR-13556590 Sao Paulo, SP - Brazil
[4] Univ Fed Sao Paulo, Cities Inst, Ave Jacu Pessego 2630, BR-08260001 Sao Paulo, SP - Brazil
[5] Univ Washington, Dept Earth & Space Sci, Johnson Hall, Box 351310, Seattle, WA 98195 - USA
Total Affiliations: 5
Document type: Journal article
Source: ENVIRONMENTAL EARTH SCIENCES; v. 77, n. 6 MAR 2018.
Web of Science Citations: 6
Abstract

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. (AU)

FAPESP's process: 14/10109-2 - Assessment of shallow landslide susceptibility using mathematical models: support on real-time hydrologic monitoring
Grantee:Bianca Carvalho Vieira
Support Opportunities: Scholarships abroad - Research