EVALUATION OF SUSCEPTIBILITY TO SHALLOW LANDSLIDES IN MAQUINÉ/RS AND THE FIELD DATA INFLUENCE ON THE QUALITY OF HAZARD MAPPING

Detalhes bibliográficos
Autor(a) principal: Franck, Alessandro Gustavo
Data de Publicação: 2023
Outros Autores: Menezes, Danrlei de, Kobiyama, Masato
Tipo de documento: Artigo
Idioma: por
Título da fonte: Caminhos de Geografia
Texto Completo: https://seer.ufu.br/index.php/caminhosdegeografia/article/view/64452
Resumo: Identifying susceptible regions to landslides and mapping hazardous areas are essential tools in managing the risk and disasters associated with these natural phenomena. One of the most used tools for mapping these areas is numerical modeling. Thus, the objective of the present study was to characterize the geotechnical units (UGs) in the Maquiné/RS river basin, perform hazard mapping and evaluate the influence of geotechnical data collected in the field on the quality of the mapping. The SHALSTAB model was used, considering the characterization of the basin's UGs with data obtained through in situ and laboratory soil analyses. Thus, three scenarios were simulated: scenario-1: default (with the values ​​recommended by the original SHALSTAB); scenario-2: average (with a single value for each parameter, this being the average of the values ​​obtained in the field); and scenario-3: discretized (with spatialized values ​​for each UG). Through the efficiency indexes used (Hit Index and Error Index), the results obtained showed that scenario-3 presented the best performance, demonstrating the importance of spatialization with the GUs and the use of local data for a greater quality of the mappings performed with SHALSTAB.
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spelling EVALUATION OF SUSCEPTIBILITY TO SHALLOW LANDSLIDES IN MAQUINÉ/RS AND THE FIELD DATA INFLUENCE ON THE QUALITY OF HAZARD MAPPINGAVALIAÇÃO DA SUSCEPTIBILIDADE A ESCORREGAMENTOS TRANSLACIONAIS EM MAQUINÉ/RS E INFLUÊNCIA DOS DADOS DE CAMPO NA QUALIDADE DO MAPEAMENTO DE PERIGOSHALSTABUnidades GeotécnicasMovimentos de massaGeomorfologiaSHALSTABGeotechnical UnitsMass movementsGeomorphologyIdentifying susceptible regions to landslides and mapping hazardous areas are essential tools in managing the risk and disasters associated with these natural phenomena. One of the most used tools for mapping these areas is numerical modeling. Thus, the objective of the present study was to characterize the geotechnical units (UGs) in the Maquiné/RS river basin, perform hazard mapping and evaluate the influence of geotechnical data collected in the field on the quality of the mapping. The SHALSTAB model was used, considering the characterization of the basin's UGs with data obtained through in situ and laboratory soil analyses. Thus, three scenarios were simulated: scenario-1: default (with the values ​​recommended by the original SHALSTAB); scenario-2: average (with a single value for each parameter, this being the average of the values ​​obtained in the field); and scenario-3: discretized (with spatialized values ​​for each UG). Through the efficiency indexes used (Hit Index and Error Index), the results obtained showed that scenario-3 presented the best performance, demonstrating the importance of spatialization with the GUs and the use of local data for a greater quality of the mappings performed with SHALSTAB.Identificar regiões suscetíveis a escorregamentos e realizar mapeamentos das áreas de perigo são ferramentas essenciais na gestão de risco e desastres associados a esses fenômenos naturais. Uma das ferramentas mais utilizadas para a elaboração de mapeamentos dessas áreas é a modelagem numérica. Dessa forma, o objetivo do presente estudo foi caracterizar as unidades geotécnicas (UGs) na bacia hidrografia do rio Maquiné/RS, realizar o mapeamento de perigo e avaliar a influência dos dados geotécnicos coletados em campo na qualidade do mapeamento. Foi utilizado o modelo SHALSTAB, com a consideração da caracterização das UGs da bacia com dados obtidos através de análises de solo in situ e em laboratório. Assim, foram simulados três cenários: cenário-1: default (com os valores recomendados pelo SHALSTAB original); cenário-2: médio (com um valor único para cada parâmetro, sendo esse a média dos valores obtidos em campo); e cenário-3: discretizado (com os valores espacializados para cada UG). Através dos índices de eficiência utilizados (Índice de Acerto e Índice de Erro), os resultados obtidos demonstraram que o cenário-3 apresentou o melhor desempenho, demonstrando a importância da espacialização com as UGs e da utilização de dados locais para uma maior qualidade dos mapeamentos realizados com o SHALSTAB.EDUFU - Editora da Universidade Federal de Uberlândia2023-06-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAvaliado pelos paresapplication/pdfhttps://seer.ufu.br/index.php/caminhosdegeografia/article/view/6445210.14393/RCG249364452Caminhos de Geografia; Vol. 24 No. 93 (2023): Junho; 367-384Caminhos de Geografia; Vol. 24 Núm. 93 (2023): Junho; 367-384Caminhos de Geografia; v. 24 n. 93 (2023): Junho; 367-3841678-6343reponame:Caminhos de Geografiainstname:Universidade Federal de Uberlândia (UFU)instacron:UFUporhttps://seer.ufu.br/index.php/caminhosdegeografia/article/view/64452/36134Copyright (c) 2023 Alessandro Gustavo Franck, Danrlei de Menezes, Masato Kobiyamahttp://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessFranck, Alessandro GustavoMenezes, Danrlei deKobiyama, Masato2023-06-12T17:08:57Zoai:ojs.www.seer.ufu.br:article/64452Revistahttps://seer.ufu.br/index.php/caminhosdegeografia/indexPUBhttp://www.seer.ufu.br/index.php/caminhosdegeografia/oaiflaviasantosgeo@gmail.com1678-63431678-6343opendoar:2023-06-12T17:08:57Caminhos de Geografia - Universidade Federal de Uberlândia (UFU)false
dc.title.none.fl_str_mv EVALUATION OF SUSCEPTIBILITY TO SHALLOW LANDSLIDES IN MAQUINÉ/RS AND THE FIELD DATA INFLUENCE ON THE QUALITY OF HAZARD MAPPING
AVALIAÇÃO DA SUSCEPTIBILIDADE A ESCORREGAMENTOS TRANSLACIONAIS EM MAQUINÉ/RS E INFLUÊNCIA DOS DADOS DE CAMPO NA QUALIDADE DO MAPEAMENTO DE PERIGO
title EVALUATION OF SUSCEPTIBILITY TO SHALLOW LANDSLIDES IN MAQUINÉ/RS AND THE FIELD DATA INFLUENCE ON THE QUALITY OF HAZARD MAPPING
spellingShingle EVALUATION OF SUSCEPTIBILITY TO SHALLOW LANDSLIDES IN MAQUINÉ/RS AND THE FIELD DATA INFLUENCE ON THE QUALITY OF HAZARD MAPPING
Franck, Alessandro Gustavo
SHALSTAB
Unidades Geotécnicas
Movimentos de massa
Geomorfologia
SHALSTAB
Geotechnical Units
Mass movements
Geomorphology
title_short EVALUATION OF SUSCEPTIBILITY TO SHALLOW LANDSLIDES IN MAQUINÉ/RS AND THE FIELD DATA INFLUENCE ON THE QUALITY OF HAZARD MAPPING
title_full EVALUATION OF SUSCEPTIBILITY TO SHALLOW LANDSLIDES IN MAQUINÉ/RS AND THE FIELD DATA INFLUENCE ON THE QUALITY OF HAZARD MAPPING
title_fullStr EVALUATION OF SUSCEPTIBILITY TO SHALLOW LANDSLIDES IN MAQUINÉ/RS AND THE FIELD DATA INFLUENCE ON THE QUALITY OF HAZARD MAPPING
title_full_unstemmed EVALUATION OF SUSCEPTIBILITY TO SHALLOW LANDSLIDES IN MAQUINÉ/RS AND THE FIELD DATA INFLUENCE ON THE QUALITY OF HAZARD MAPPING
title_sort EVALUATION OF SUSCEPTIBILITY TO SHALLOW LANDSLIDES IN MAQUINÉ/RS AND THE FIELD DATA INFLUENCE ON THE QUALITY OF HAZARD MAPPING
author Franck, Alessandro Gustavo
author_facet Franck, Alessandro Gustavo
Menezes, Danrlei de
Kobiyama, Masato
author_role author
author2 Menezes, Danrlei de
Kobiyama, Masato
author2_role author
author
dc.contributor.author.fl_str_mv Franck, Alessandro Gustavo
Menezes, Danrlei de
Kobiyama, Masato
dc.subject.por.fl_str_mv SHALSTAB
Unidades Geotécnicas
Movimentos de massa
Geomorfologia
SHALSTAB
Geotechnical Units
Mass movements
Geomorphology
topic SHALSTAB
Unidades Geotécnicas
Movimentos de massa
Geomorfologia
SHALSTAB
Geotechnical Units
Mass movements
Geomorphology
description Identifying susceptible regions to landslides and mapping hazardous areas are essential tools in managing the risk and disasters associated with these natural phenomena. One of the most used tools for mapping these areas is numerical modeling. Thus, the objective of the present study was to characterize the geotechnical units (UGs) in the Maquiné/RS river basin, perform hazard mapping and evaluate the influence of geotechnical data collected in the field on the quality of the mapping. The SHALSTAB model was used, considering the characterization of the basin's UGs with data obtained through in situ and laboratory soil analyses. Thus, three scenarios were simulated: scenario-1: default (with the values ​​recommended by the original SHALSTAB); scenario-2: average (with a single value for each parameter, this being the average of the values ​​obtained in the field); and scenario-3: discretized (with spatialized values ​​for each UG). Through the efficiency indexes used (Hit Index and Error Index), the results obtained showed that scenario-3 presented the best performance, demonstrating the importance of spatialization with the GUs and the use of local data for a greater quality of the mappings performed with SHALSTAB.
publishDate 2023
dc.date.none.fl_str_mv 2023-06-12
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Avaliado pelos pares
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://seer.ufu.br/index.php/caminhosdegeografia/article/view/64452
10.14393/RCG249364452
url https://seer.ufu.br/index.php/caminhosdegeografia/article/view/64452
identifier_str_mv 10.14393/RCG249364452
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://seer.ufu.br/index.php/caminhosdegeografia/article/view/64452/36134
dc.rights.driver.fl_str_mv Copyright (c) 2023 Alessandro Gustavo Franck, Danrlei de Menezes, Masato Kobiyama
http://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2023 Alessandro Gustavo Franck, Danrlei de Menezes, Masato Kobiyama
http://creativecommons.org/licenses/by-nc-nd/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv EDUFU - Editora da Universidade Federal de Uberlândia
publisher.none.fl_str_mv EDUFU - Editora da Universidade Federal de Uberlândia
dc.source.none.fl_str_mv Caminhos de Geografia; Vol. 24 No. 93 (2023): Junho; 367-384
Caminhos de Geografia; Vol. 24 Núm. 93 (2023): Junho; 367-384
Caminhos de Geografia; v. 24 n. 93 (2023): Junho; 367-384
1678-6343
reponame:Caminhos de Geografia
instname:Universidade Federal de Uberlândia (UFU)
instacron:UFU
instname_str Universidade Federal de Uberlândia (UFU)
instacron_str UFU
institution UFU
reponame_str Caminhos de Geografia
collection Caminhos de Geografia
repository.name.fl_str_mv Caminhos de Geografia - Universidade Federal de Uberlândia (UFU)
repository.mail.fl_str_mv flaviasantosgeo@gmail.com
_version_ 1797067010489712640

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