Landslide susceptibility mapping based on rainfall scenarios: a case study from Sao Paulo in Brazil

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dc.contributor.authorRamos, Leila Maria [UNESP]
dc.contributor.authorBazzan, Thiago
dc.contributor.authorMotta, Mariana Ferreira Benessiuti [UNESP]
dc.contributor.authorBernardes, George de Paula [UNESP]
dc.contributor.authorGiacheti, Heraldo Luiz [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionNatl Inst Space Res
dc.date.accessioned2022-11-30T13:45:04Z
dc.date.available2022-11-30T13:45:04Z
dc.date.issued2022-01-01
dc.description.abstractMass movement susceptibility mapping from rainfall data and in situ site characterization constitute an important approach for preventing geological-geotechnical accidents on railroads and highways. A comprehensive site characterization program was conducted to identify slopes with mass movements along the 44 km of SP-171 road in the state of Sao Paulo, Brazil. Ninety-two slopes with some degree of instability were found along this section of the road, including rupture scars, active erosive processes and the presence of unstable rock blocks. Two scenarios for mass movement susceptibility (100 mm and 500 mm of accumulated rainfall) were defined by overlaying thematic maps of relief, soil type, geology, accumulated rainfall and declivity using geographic information system-based techniques. The results for both scenarios identified the regions with high and medium susceptibility to mass movements; for the scenario of 100 mm of accumulated rainfall; we found that 27% and 73% of the land area of SP-171 is respectively highly and moderately susceptible to landslide events. For the scenario of 500 mm, we found 58% and 40% to be highly and moderately susceptible areas. This study also allowed us to identify the main geotechnical problems along the 44 km of this road, and thus can be used to guide actions and decisions to avoid or minimize such problems.en
dc.description.affiliationUNESP, Dept Civil Engn, Guaratingueta, SP, Brazil
dc.description.affiliationNatl Inst Space Res, Earth Observat & Geoinformat Div, Sao Jose Dos Campos, SP, Brazil
dc.description.affiliationUNESP, Dept Civil & Environm Engn, Bauru, SP, Brazil
dc.description.affiliationUnespUNESP, Dept Civil Engn, Guaratingueta, SP, Brazil
dc.description.affiliationUnespUNESP, Dept Civil & Environm Engn, Bauru, SP, Brazil
dc.format.extent438-451
dc.identifierhttp://dx.doi.org/10.3934/geosci.2022024
dc.identifier.citationAims Geosciences. Springfield: Amer Inst Mathematical Sciences-aims, v. 8, n. 3, p. 438-451, 2022.
dc.identifier.doi10.3934/geosci.2022024
dc.identifier.issn2471-2132
dc.identifier.urihttp://hdl.handle.net/11449/237791
dc.identifier.wosWOS:000829674000001
dc.language.isoeng
dc.publisherAmer Inst Mathematical Sciences-aims
dc.relation.ispartofAims Geosciences
dc.sourceWeb of Science
dc.subjectGeotechnical cartography
dc.subjectGIS
dc.subjectLandslide studies
dc.subjectSusceptibility
dc.subjectRainfall
dc.titleLandslide susceptibility mapping based on rainfall scenarios: a case study from Sao Paulo in Brazilen
dc.typeArtigo
dcterms.rightsHolderAmer Inst Mathematical Sciences-aims

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Artigos - Engenharia Civil - FEG
Artigos - Engenharia Civil e Ambiental - FEB