caa a22 4500 60545485X CHVBK 20210128100209.0 cr unu---uuuuu 210128e20150501xx s 000 0 eng 10.1007/s10064-014-0622-8 doi (NATIONALLICENCE)springer-10.1007/s10064-014-0622-8 Susceptibility to shallow landslides in a drainage basin in the Serra do Mar, São Paulo, Brazil, predicted using the SINMAP mathematical model [Elektronische Daten] [Tulius Nery, Bianca Vieira] 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. Springer-Verlag Berlin Heidelberg, 2014 Serra do Mar nationallicence Shallow landslides nationallicence Digital terrain model nationallicence SINMAP nationallicence Nery Tulius National Early Warning and Monitoring Center for Natural Disasters, Cachoeira Paulista, Brazil aut Vieira Bianca Department of Geography, University of São Paulo, Prof. Lineu Prestes Avenue, 338, Cidade Universitária, São Paulo, Brazil aut Bulletin of Engineering Geology and the Environment Springer Berlin Heidelberg 74/2(2015-05-01), 369-378 1435-9529 74:2<369 2015 74 10064 https://doi.org/10.1007/s10064-014-0622-8 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10064-014-0622-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Nery Tulius National Early Warning and Monitoring Center for Natural Disasters, Cachoeira Paulista, Brazil aut NATIONALLICENCE 700 1- Vieira Bianca Department of Geography, University of São Paulo, Prof. Lineu Prestes Avenue, 338, Cidade Universitária, São Paulo, Brazil aut NATIONALLICENCE 773 0- Bulletin of Engineering Geology and the Environment Springer Berlin Heidelberg 74/2(2015-05-01), 369-378 1435-9529 74:2<369 2015 74 10064