The relevance of geotechnical-unit characterization for landslide-susceptibility mapping with SHALSTAB
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Outros Autores: | , , |
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. |
id |
UFRGS-2_bab491b4c56490d00b37ca0fbc48c4ea |
---|---|
oai_identifier_str |
oai:www.lume.ufrgs.br:10183/233834 |
network_acronym_str |
UFRGS-2 |
network_name_str |
Repositório Institucional da UFRGS |
repository_id_str |
|
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 info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10183/233834 |
dc.identifier.issn.pt_BR.fl_str_mv |
2624-795X |
dc.identifier.nrb.pt_BR.fl_str_mv |
001134596 |
identifier_str_mv |
2624-795X 001134596 |
url |
http://hdl.handle.net/10183/233834 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
GeoHazards. Basel. Vol. 2, n.4 (Dec. 2021), p. 383-397 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFRGS instname:Universidade Federal do Rio Grande do Sul (UFRGS) instacron:UFRGS |
instname_str |
Universidade Federal do Rio Grande do Sul (UFRGS) |
instacron_str |
UFRGS |
institution |
UFRGS |
reponame_str |
Repositório Institucional da UFRGS |
collection |
Repositório Institucional da UFRGS |
bitstream.url.fl_str_mv |
http://www.lume.ufrgs.br/bitstream/10183/233834/2/001134596.pdf.txt http://www.lume.ufrgs.br/bitstream/10183/233834/1/001134596.pdf |
bitstream.checksum.fl_str_mv |
18dcc2ed99ddb38f7760417c94099d91 ed91c29d243f0bbca3d7dfec258a0d0b |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS) |
repository.mail.fl_str_mv |
|
_version_ |
1801225048082612224 |