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

Detalhes bibliográficos
Autor(a) principal: Ramos, Leila Maria [UNESP]
Data de Publicação: 2022
Outros Autores: Bazzan, Thiago, Motta, Mariana Ferreira Benessiuti [UNESP], Bernardes, George de Paula [UNESP], Giacheti, Heraldo Luiz [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.3934/geosci.2022024
http://hdl.handle.net/11449/237791
Resumo: Mass 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.
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spelling Landslide susceptibility mapping based on rainfall scenarios: a case study from Sao Paulo in BrazilGeotechnical cartographyGISLandslide studiesSusceptibilityRainfallMass 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.UNESP, Dept Civil Engn, Guaratingueta, SP, BrazilNatl Inst Space Res, Earth Observat & Geoinformat Div, Sao Jose Dos Campos, SP, BrazilUNESP, Dept Civil & Environm Engn, Bauru, SP, BrazilUNESP, Dept Civil Engn, Guaratingueta, SP, BrazilUNESP, Dept Civil & Environm Engn, Bauru, SP, BrazilAmer Inst Mathematical Sciences-aimsUniversidade Estadual Paulista (UNESP)Natl Inst Space ResRamos, Leila Maria [UNESP]Bazzan, ThiagoMotta, Mariana Ferreira Benessiuti [UNESP]Bernardes, George de Paula [UNESP]Giacheti, Heraldo Luiz [UNESP]2022-11-30T13:45:04Z2022-11-30T13:45:04Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article438-451http://dx.doi.org/10.3934/geosci.2022024Aims Geosciences. Springfield: Amer Inst Mathematical Sciences-aims, v. 8, n. 3, p. 438-451, 2022.2471-2132http://hdl.handle.net/11449/23779110.3934/geosci.2022024WOS:000829674000001Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAims Geosciencesinfo:eu-repo/semantics/openAccess2024-07-01T19:54:41Zoai:repositorio.unesp.br:11449/237791Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T13:36:07.475951Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Landslide susceptibility mapping based on rainfall scenarios: a case study from Sao Paulo in Brazil
title Landslide susceptibility mapping based on rainfall scenarios: a case study from Sao Paulo in Brazil
spellingShingle Landslide susceptibility mapping based on rainfall scenarios: a case study from Sao Paulo in Brazil
Ramos, Leila Maria [UNESP]
Geotechnical cartography
GIS
Landslide studies
Susceptibility
Rainfall
title_short Landslide susceptibility mapping based on rainfall scenarios: a case study from Sao Paulo in Brazil
title_full Landslide susceptibility mapping based on rainfall scenarios: a case study from Sao Paulo in Brazil
title_fullStr Landslide susceptibility mapping based on rainfall scenarios: a case study from Sao Paulo in Brazil
title_full_unstemmed Landslide susceptibility mapping based on rainfall scenarios: a case study from Sao Paulo in Brazil
title_sort Landslide susceptibility mapping based on rainfall scenarios: a case study from Sao Paulo in Brazil
author Ramos, Leila Maria [UNESP]
author_facet Ramos, Leila Maria [UNESP]
Bazzan, Thiago
Motta, Mariana Ferreira Benessiuti [UNESP]
Bernardes, George de Paula [UNESP]
Giacheti, Heraldo Luiz [UNESP]
author_role author
author2 Bazzan, Thiago
Motta, Mariana Ferreira Benessiuti [UNESP]
Bernardes, George de Paula [UNESP]
Giacheti, Heraldo Luiz [UNESP]
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
Natl Inst Space Res
dc.contributor.author.fl_str_mv Ramos, Leila Maria [UNESP]
Bazzan, Thiago
Motta, Mariana Ferreira Benessiuti [UNESP]
Bernardes, George de Paula [UNESP]
Giacheti, Heraldo Luiz [UNESP]
dc.subject.por.fl_str_mv Geotechnical cartography
GIS
Landslide studies
Susceptibility
Rainfall
topic Geotechnical cartography
GIS
Landslide studies
Susceptibility
Rainfall
description Mass 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.
publishDate 2022
dc.date.none.fl_str_mv 2022-11-30T13:45:04Z
2022-11-30T13:45:04Z
2022-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.3934/geosci.2022024
Aims Geosciences. Springfield: Amer Inst Mathematical Sciences-aims, v. 8, n. 3, p. 438-451, 2022.
2471-2132
http://hdl.handle.net/11449/237791
10.3934/geosci.2022024
WOS:000829674000001
url http://dx.doi.org/10.3934/geosci.2022024
http://hdl.handle.net/11449/237791
identifier_str_mv Aims Geosciences. Springfield: Amer Inst Mathematical Sciences-aims, v. 8, n. 3, p. 438-451, 2022.
2471-2132
10.3934/geosci.2022024
WOS:000829674000001
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Aims Geosciences
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 438-451
dc.publisher.none.fl_str_mv Amer Inst Mathematical Sciences-aims
publisher.none.fl_str_mv Amer Inst Mathematical Sciences-aims
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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