Landslide susceptibility mapping based on rainfall scenarios: a case study from Sao Paulo in Brazil
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
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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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 |
|
_version_ |
1808128253318135808 |