Bayesian inverse analysis with field observation for slope failure mechanism and reliability assessment under rainfall accounting for nonstationary characteristics of soil properties
Slope failure mechanism and reliability assessment under rainfall usually not only ignores the nonstationary characteristics of soil hydraulic and shear strength parameters, but also does not make use of the freely available field observation that the slope remains stable under the natural condition...
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Elsevier
2025-02-01
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| Series: | Soils and Foundations |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0038080625000022 |
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| author | Xian Liu Shui-Hua Jiang Jiawei Xie Xueyou Li |
| author_facet | Xian Liu Shui-Hua Jiang Jiawei Xie Xueyou Li |
| author_sort | Xian Liu |
| collection | DOAJ |
| description | Slope failure mechanism and reliability assessment under rainfall usually not only ignores the nonstationary characteristics of soil hydraulic and shear strength parameters, but also does not make use of the freely available field observation that the slope remains stable under the natural condition. In this paper, the nonstationary characteristics and spatial variabilities of soil hydraulic and shear strength parameters, along with model bias, are explicitly accounted for. Firstly, Bayesian inverse analysis is conducted to infer the spatially varying shear strength parameters and reduce their uncertainties by incorporating the field observation. Following this, an infinite slope model is taken as an example to perform slope seepage, stability and reliability analyses subjected to a rainfall event based on the posterior statistics of soil shear strength parameters. The probabilities of slope failure and distributions of critical slip surface for various rainfall durations are then evaluated within a Monte-Carlo simulation framework. Based on these, the slope failure mechanism induced solely by the rainfall is investigated. The results indicate that the probability of failure of the infinite slope, when evaluated using the posterior statistics of soil shear strength parameters, is close to zero (7.24 × 10−2), which aligns with the field observation wherein the slope remains stable under the natural condition. The triggering factors for slope failure vary across different stages of rainfall infiltration are identified and elucidated in this paper. Ignoring the field observation and the nonstationary characteristics of soil properties can lead to inaccurate assessments of both the failure mechanisms and probabilities of slopes induced by the rainfall. The research can provide a new perspective for understanding the slope failure mechanism caused by the rainfall. |
| format | Article |
| id | doaj-art-7bbe65c2877c47038e9d7a4fa6c06ca0 |
| institution | Kabale University |
| issn | 2524-1788 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Soils and Foundations |
| spelling | doaj-art-7bbe65c2877c47038e9d7a4fa6c06ca02025-01-26T05:03:13ZengElsevierSoils and Foundations2524-17882025-02-01651101568Bayesian inverse analysis with field observation for slope failure mechanism and reliability assessment under rainfall accounting for nonstationary characteristics of soil propertiesXian Liu0Shui-Hua Jiang1Jiawei Xie2Xueyou Li3School of Infrastructure Engineering, Nanchang University, Xuefu Road 999, Nanchang 330031, China; School of Civil Engineering, Sun Yat-Sen University, Zhuhai 519082, ChinaSchool of Infrastructure Engineering, Nanchang University, Xuefu Road 999, Nanchang 330031, China; Jiangxi Provincial Key Laboratory of Hydraulic Geotechnical Engineering Safety, Nanchang University, 999 Xuefu Road, Nanchang 330031, China; Corresponding author at: School of Infrastructure Engineering, Nanchang University, Xuefu Road 999, Nanchang 330031, China.Discipline of Civil, Surveying and Environmental Engineering, Faculty of Engineering and Built Environment, The University of Newcastle, Callaghan, NSW 2308, AustraliaSchool of Civil Engineering, Sun Yat-Sen University, Zhuhai 519082, ChinaSlope failure mechanism and reliability assessment under rainfall usually not only ignores the nonstationary characteristics of soil hydraulic and shear strength parameters, but also does not make use of the freely available field observation that the slope remains stable under the natural condition. In this paper, the nonstationary characteristics and spatial variabilities of soil hydraulic and shear strength parameters, along with model bias, are explicitly accounted for. Firstly, Bayesian inverse analysis is conducted to infer the spatially varying shear strength parameters and reduce their uncertainties by incorporating the field observation. Following this, an infinite slope model is taken as an example to perform slope seepage, stability and reliability analyses subjected to a rainfall event based on the posterior statistics of soil shear strength parameters. The probabilities of slope failure and distributions of critical slip surface for various rainfall durations are then evaluated within a Monte-Carlo simulation framework. Based on these, the slope failure mechanism induced solely by the rainfall is investigated. The results indicate that the probability of failure of the infinite slope, when evaluated using the posterior statistics of soil shear strength parameters, is close to zero (7.24 × 10−2), which aligns with the field observation wherein the slope remains stable under the natural condition. The triggering factors for slope failure vary across different stages of rainfall infiltration are identified and elucidated in this paper. Ignoring the field observation and the nonstationary characteristics of soil properties can lead to inaccurate assessments of both the failure mechanisms and probabilities of slopes induced by the rainfall. The research can provide a new perspective for understanding the slope failure mechanism caused by the rainfall.http://www.sciencedirect.com/science/article/pii/S0038080625000022SlopeNonstationary characteristicsBayesian inverse analysisRainfall-induced failure mechanismReliability assessment |
| spellingShingle | Xian Liu Shui-Hua Jiang Jiawei Xie Xueyou Li Bayesian inverse analysis with field observation for slope failure mechanism and reliability assessment under rainfall accounting for nonstationary characteristics of soil properties Soils and Foundations Slope Nonstationary characteristics Bayesian inverse analysis Rainfall-induced failure mechanism Reliability assessment |
| title | Bayesian inverse analysis with field observation for slope failure mechanism and reliability assessment under rainfall accounting for nonstationary characteristics of soil properties |
| title_full | Bayesian inverse analysis with field observation for slope failure mechanism and reliability assessment under rainfall accounting for nonstationary characteristics of soil properties |
| title_fullStr | Bayesian inverse analysis with field observation for slope failure mechanism and reliability assessment under rainfall accounting for nonstationary characteristics of soil properties |
| title_full_unstemmed | Bayesian inverse analysis with field observation for slope failure mechanism and reliability assessment under rainfall accounting for nonstationary characteristics of soil properties |
| title_short | Bayesian inverse analysis with field observation for slope failure mechanism and reliability assessment under rainfall accounting for nonstationary characteristics of soil properties |
| title_sort | bayesian inverse analysis with field observation for slope failure mechanism and reliability assessment under rainfall accounting for nonstationary characteristics of soil properties |
| topic | Slope Nonstationary characteristics Bayesian inverse analysis Rainfall-induced failure mechanism Reliability assessment |
| url | http://www.sciencedirect.com/science/article/pii/S0038080625000022 |
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