The relevance of geotechnical-unit characterization for landslide-susceptibility mapping with SHALSTAB

Detalhes bibliográficos
Autor(a) principal: Melo, Carla Moreira
Data de Publicação: 2021
Outros Autores: Kobiyama, Masato, Michel, Gean Paulo, Brito, Mariana Madruga de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/233834
Resumo: Given the increasing occurrence of landslides worldwide, the improvement of predictive models for landslide mapping is needed. Despite the influence of geotechnical parameters on SHALSTAB model outputs, there is a lack of research on models’ performance when considering different variables. In particular, the role of geotechnical units (i.e., areas with common soil and lithology) is understudied. Indeed, the original SHALSTAB model considers that the whole basin has homogeneous soil. This can lead to the under-or-overestimation of landslide hazards. Therefore, in this study, we aimed to investigate the advantages of incorporating geotechnical units as a variable in contrast to the original model. By using locally sampled geotechnical data, 13 slope-instability scenarios were simulated for the Jaguar creek basin, Brazil. This allowed us to verify the sensitivity of the model to different input variables and assumptions. To evaluate the model performance, we used the Success Index, Error Index, ROC curve, and a new performance index: the Detective Performance Index of Unstable Areas. The best model performance was obtained in the scenario with discretized geotechnical units’ values and the largest sample size. Results indicate the importance of properly characterizing the geotechnical units when using SHALSTAB. Hence, future applications should consider this to improve models’ predictivity.
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spelling Melo, Carla MoreiraKobiyama, MasatoMichel, Gean PauloBrito, Mariana Madruga de2022-01-07T04:27:10Z20212624-795Xhttp://hdl.handle.net/10183/233834001134596Given the increasing occurrence of landslides worldwide, the improvement of predictive models for landslide mapping is needed. Despite the influence of geotechnical parameters on SHALSTAB model outputs, there is a lack of research on models’ performance when considering different variables. In particular, the role of geotechnical units (i.e., areas with common soil and lithology) is understudied. Indeed, the original SHALSTAB model considers that the whole basin has homogeneous soil. This can lead to the under-or-overestimation of landslide hazards. Therefore, in this study, we aimed to investigate the advantages of incorporating geotechnical units as a variable in contrast to the original model. By using locally sampled geotechnical data, 13 slope-instability scenarios were simulated for the Jaguar creek basin, Brazil. This allowed us to verify the sensitivity of the model to different input variables and assumptions. To evaluate the model performance, we used the Success Index, Error Index, ROC curve, and a new performance index: the Detective Performance Index of Unstable Areas. The best model performance was obtained in the scenario with discretized geotechnical units’ values and the largest sample size. Results indicate the importance of properly characterizing the geotechnical units when using SHALSTAB. Hence, future applications should consider this to improve models’ predictivity.application/pdfengGeoHazards. Basel. Vol. 2, n.4 (Dec. 2021), p. 383-397GeotecniaEscorregamentos translacionaisModelos matemáticosMapeamento geotécnicoGeotechnical unitDetective performance index of unstable areasModel performanceSHALSTABLandslide hazardThe relevance of geotechnical-unit characterization for landslide-susceptibility mapping with SHALSTABEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001134596.pdf.txt001134596.pdf.txtExtracted Texttext/plain54127http://www.lume.ufrgs.br/bitstream/10183/233834/2/001134596.pdf.txt18dcc2ed99ddb38f7760417c94099d91MD52ORIGINAL001134596.pdfTexto completo (inglês)application/pdf9542561http://www.lume.ufrgs.br/bitstream/10183/233834/1/001134596.pdfed91c29d243f0bbca3d7dfec258a0d0bMD5110183/2338342022-02-22 04:47:40.29321oai:www.lume.ufrgs.br:10183/233834Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2022-02-22T07:47:40Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv The relevance of geotechnical-unit characterization for landslide-susceptibility mapping with SHALSTAB
title The relevance of geotechnical-unit characterization for landslide-susceptibility mapping with SHALSTAB
spellingShingle The relevance of geotechnical-unit characterization for landslide-susceptibility mapping with SHALSTAB
Melo, Carla Moreira
Geotecnia
Escorregamentos translacionais
Modelos matemáticos
Mapeamento geotécnico
Geotechnical unit
Detective performance index of unstable areas
Model performance
SHALSTAB
Landslide hazard
title_short The relevance of geotechnical-unit characterization for landslide-susceptibility mapping with SHALSTAB
title_full The relevance of geotechnical-unit characterization for landslide-susceptibility mapping with SHALSTAB
title_fullStr The relevance of geotechnical-unit characterization for landslide-susceptibility mapping with SHALSTAB
title_full_unstemmed The relevance of geotechnical-unit characterization for landslide-susceptibility mapping with SHALSTAB
title_sort The relevance of geotechnical-unit characterization for landslide-susceptibility mapping with SHALSTAB
author Melo, Carla Moreira
author_facet Melo, Carla Moreira
Kobiyama, Masato
Michel, Gean Paulo
Brito, Mariana Madruga de
author_role author
author2 Kobiyama, Masato
Michel, Gean Paulo
Brito, Mariana Madruga de
author2_role author
author
author
dc.contributor.author.fl_str_mv Melo, Carla Moreira
Kobiyama, Masato
Michel, Gean Paulo
Brito, Mariana Madruga de
dc.subject.por.fl_str_mv Geotecnia
Escorregamentos translacionais
Modelos matemáticos
Mapeamento geotécnico
topic Geotecnia
Escorregamentos translacionais
Modelos matemáticos
Mapeamento geotécnico
Geotechnical unit
Detective performance index of unstable areas
Model performance
SHALSTAB
Landslide hazard
dc.subject.eng.fl_str_mv Geotechnical unit
Detective performance index of unstable areas
Model performance
SHALSTAB
Landslide hazard
description Given the increasing occurrence of landslides worldwide, the improvement of predictive models for landslide mapping is needed. Despite the influence of geotechnical parameters on SHALSTAB model outputs, there is a lack of research on models’ performance when considering different variables. In particular, the role of geotechnical units (i.e., areas with common soil and lithology) is understudied. Indeed, the original SHALSTAB model considers that the whole basin has homogeneous soil. This can lead to the under-or-overestimation of landslide hazards. Therefore, in this study, we aimed to investigate the advantages of incorporating geotechnical units as a variable in contrast to the original model. By using locally sampled geotechnical data, 13 slope-instability scenarios were simulated for the Jaguar creek basin, Brazil. This allowed us to verify the sensitivity of the model to different input variables and assumptions. To evaluate the model performance, we used the Success Index, Error Index, ROC curve, and a new performance index: the Detective Performance Index of Unstable Areas. The best model performance was obtained in the scenario with discretized geotechnical units’ values and the largest sample size. Results indicate the importance of properly characterizing the geotechnical units when using SHALSTAB. Hence, future applications should consider this to improve models’ predictivity.
publishDate 2021
dc.date.issued.fl_str_mv 2021
dc.date.accessioned.fl_str_mv 2022-01-07T04:27:10Z
dc.type.driver.fl_str_mv Estrangeiro
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dc.language.iso.fl_str_mv eng
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dc.relation.ispartof.pt_BR.fl_str_mv GeoHazards. Basel. Vol. 2, n.4 (Dec. 2021), p. 383-397
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