Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithm

The susceptibility mapping of rainfall-induced landslides is an effective tool for predicting and locating disaster-prone zones at the regional scale. One of the most important parts of landslide susceptibility models is the hydrological model. In this context, the present study considers three pore...

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Autores: Cui, Hongzhi, Ji, Jian, Hurlimann Ziegler, Marcel|||0000-0003-0119-1438, Medina Iglesias, Vicente César de|||0000-0001-5578-3848
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/413393
Acceso en línea:https://hdl.handle.net/2117/413393
https://dx.doi.org/10.1007/s10346-024-02226-8
Access Level:acceso abierto
Palabra clave:Landslides
Landslide susceptibility
Slope stability
Rainfall transient infiltration
Probabilistic analysis
First-order reliability method (FORM)
Esllavissades
Àrees temàtiques de la UPC::Enginyeria civil::Geotècnia::Mecànica de sòls
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spelling Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithmCui, HongzhiJi, JianHurlimann Ziegler, Marcel|||0000-0003-0119-1438Medina Iglesias, Vicente César de|||0000-0001-5578-3848LandslidesLandslide susceptibilitySlope stabilityRainfall transient infiltrationProbabilistic analysisFirst-order reliability method (FORM)EsllavissadesÀrees temàtiques de la UPC::Enginyeria civil::Geotècnia::Mecànica de sòlsThe susceptibility mapping of rainfall-induced landslides is an effective tool for predicting and locating disaster-prone zones at the regional scale. One of the most important parts of landslide susceptibility models is the hydrological model. In this context, the present study considers three pore water pressure (PWP) profiles with surface runoff to estimate the spatiotemporal variation of wetting front depth (WFD) during rainfall episodes. To reasonably simulate the inherent uncertainty and variability involved in the hydrogeomechanical properties of the surficial soil layers at the regional scale, probabilistic analysis based on the recursive first-order reliability method (FORM) is employed to calculate the probability of slope failure. The regional time-dependent landslide susceptibility mapping is realised using a newly developed model called Physically-based probabilistic modelling of Rainfall Landslides using Simplified Transient Infiltration Model (PRL-STIM). The proposed model is applied in a representative area that suffered extensive rainfall-induced landslides in July 2013 (Niangniangba Town, Gansu Province, China). The results indicate that the PRL-STIM model achieved a satisfactory prediction accuracy of 75% AUC compared to existing models like transient rainfall infiltration and grid-based regional slope-stability model (72%) and the probabilistic analysis results based on the first-order second moment method (74%). It also performed well in predicting the spatial distribution of shallow landslides, with a success rate of 81.6%. Regarding the model efficiency, the completion of a raster file for calculating the landslide probabilities of the study area (including 711,051 cells) requires only 17.1 s. It is thus hoped that the proposed calculation framework of PRL-STIM that considers various uncertainties (e.g., nonlinearity of the physical model, non-normal probability distributions, random variable cross correlations, etc.) in geotechnical parameters is better suited for landslide susceptibility mapping at the regional scale, where only limited historical event data is available.Peer ReviewedSpringer20242024-06-0120242024-08-27journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/413393https://dx.doi.org/10.1007/s10346-024-02226-8reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4133932026-05-27T15:37:01Z
dc.title.none.fl_str_mv Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithm
title Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithm
spellingShingle Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithm
Cui, Hongzhi
Landslides
Landslide susceptibility
Slope stability
Rainfall transient infiltration
Probabilistic analysis
First-order reliability method (FORM)
Esllavissades
Àrees temàtiques de la UPC::Enginyeria civil::Geotècnia::Mecànica de sòls
title_short Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithm
title_full Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithm
title_fullStr Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithm
title_full_unstemmed Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithm
title_sort Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithm
dc.creator.none.fl_str_mv Cui, Hongzhi
Ji, Jian
Hurlimann Ziegler, Marcel|||0000-0003-0119-1438
Medina Iglesias, Vicente César de|||0000-0001-5578-3848
author Cui, Hongzhi
author_facet Cui, Hongzhi
Ji, Jian
Hurlimann Ziegler, Marcel|||0000-0003-0119-1438
Medina Iglesias, Vicente César de|||0000-0001-5578-3848
author_role author
author2 Ji, Jian
Hurlimann Ziegler, Marcel|||0000-0003-0119-1438
Medina Iglesias, Vicente César de|||0000-0001-5578-3848
author2_role author
author
author
dc.subject.none.fl_str_mv Landslides
Landslide susceptibility
Slope stability
Rainfall transient infiltration
Probabilistic analysis
First-order reliability method (FORM)
Esllavissades
Àrees temàtiques de la UPC::Enginyeria civil::Geotècnia::Mecànica de sòls
topic Landslides
Landslide susceptibility
Slope stability
Rainfall transient infiltration
Probabilistic analysis
First-order reliability method (FORM)
Esllavissades
Àrees temàtiques de la UPC::Enginyeria civil::Geotècnia::Mecànica de sòls
description The susceptibility mapping of rainfall-induced landslides is an effective tool for predicting and locating disaster-prone zones at the regional scale. One of the most important parts of landslide susceptibility models is the hydrological model. In this context, the present study considers three pore water pressure (PWP) profiles with surface runoff to estimate the spatiotemporal variation of wetting front depth (WFD) during rainfall episodes. To reasonably simulate the inherent uncertainty and variability involved in the hydrogeomechanical properties of the surficial soil layers at the regional scale, probabilistic analysis based on the recursive first-order reliability method (FORM) is employed to calculate the probability of slope failure. The regional time-dependent landslide susceptibility mapping is realised using a newly developed model called Physically-based probabilistic modelling of Rainfall Landslides using Simplified Transient Infiltration Model (PRL-STIM). The proposed model is applied in a representative area that suffered extensive rainfall-induced landslides in July 2013 (Niangniangba Town, Gansu Province, China). The results indicate that the PRL-STIM model achieved a satisfactory prediction accuracy of 75% AUC compared to existing models like transient rainfall infiltration and grid-based regional slope-stability model (72%) and the probabilistic analysis results based on the first-order second moment method (74%). It also performed well in predicting the spatial distribution of shallow landslides, with a success rate of 81.6%. Regarding the model efficiency, the completion of a raster file for calculating the landslide probabilities of the study area (including 711,051 cells) requires only 17.1 s. It is thus hoped that the proposed calculation framework of PRL-STIM that considers various uncertainties (e.g., nonlinearity of the physical model, non-normal probability distributions, random variable cross correlations, etc.) in geotechnical parameters is better suited for landslide susceptibility mapping at the regional scale, where only limited historical event data is available.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-06-01
2024
2024-08-27
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/413393
https://dx.doi.org/10.1007/s10346-024-02226-8
url https://hdl.handle.net/2117/413393
https://dx.doi.org/10.1007/s10346-024-02226-8
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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