A probabilistic framework for rainfall-induced instability in unsaturated slopes using bivariate rainfall and multivariate soil random fields

IF 3.7 2区 工程技术 Q3 ENGINEERING, ENVIRONMENTAL
Meaza Girma Demisa, Shuhong Wang, Qinkuan Hou, Sun Wenpan, Furui Dong, Bowen Han
{"title":"A probabilistic framework for rainfall-induced instability in unsaturated slopes using bivariate rainfall and multivariate soil random fields","authors":"Meaza Girma Demisa,&nbsp;Shuhong Wang,&nbsp;Qinkuan Hou,&nbsp;Sun Wenpan,&nbsp;Furui Dong,&nbsp;Bowen Han","doi":"10.1007/s10064-025-04171-9","DOIUrl":null,"url":null,"abstract":"<div><p>Rainfall is a critical factor in triggering landslides globally, with slope failure probability serving as a key metric for assessing landslide risks. While the spatial variability of soil properties and rainfall uncertainty significantly influence slope failure probability, limited studies have addressed these factors concurrently. Most existing research either emphasizes the spatial variability of soil properties or rainfall uncertainty, often neglecting their combined effects. To address this gap, this study introduces an integrated probabilistic framework that incorporates soil spatial variability and rainfall uncertainty into a slope model for the probabilistic slope seepage analysis based on Monte Carlo simulations. Multivariate soil random fields are employed to represent spatial variability, while rainfall uncertainty is modeled using a bivariate distribution of intensity and duration. This approach allows for the derivation of critical metrics, including the probability of slope failure under single rainfall events, annual failure probabilities, and failure probabilities over multiple years. The proposed framework was applied to a soil slope from the Sawala Laska road project in Ethiopia to demonstrate its effectiveness. Compared to traditional methods that consider only rainfall uncertainty or treat soil properties as deterministic, the framework provides a broader range of safety factor values and more precise estimates of critical rainfall durations. It also reveals that the probability of failure during a single rainfall event decreases, while annual failure probability increases gradually with more frequent rainfall events. By integrating spatial soil variability and rainfall uncertainty within a unified framework, this study advances landslide risk assessments and provides practical tools for slope stability analysis under real-world conditions.</p></div>","PeriodicalId":500,"journal":{"name":"Bulletin of Engineering Geology and the Environment","volume":"84 4","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bulletin of Engineering Geology and the Environment","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s10064-025-04171-9","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
引用次数: 0

Abstract

Rainfall is a critical factor in triggering landslides globally, with slope failure probability serving as a key metric for assessing landslide risks. While the spatial variability of soil properties and rainfall uncertainty significantly influence slope failure probability, limited studies have addressed these factors concurrently. Most existing research either emphasizes the spatial variability of soil properties or rainfall uncertainty, often neglecting their combined effects. To address this gap, this study introduces an integrated probabilistic framework that incorporates soil spatial variability and rainfall uncertainty into a slope model for the probabilistic slope seepage analysis based on Monte Carlo simulations. Multivariate soil random fields are employed to represent spatial variability, while rainfall uncertainty is modeled using a bivariate distribution of intensity and duration. This approach allows for the derivation of critical metrics, including the probability of slope failure under single rainfall events, annual failure probabilities, and failure probabilities over multiple years. The proposed framework was applied to a soil slope from the Sawala Laska road project in Ethiopia to demonstrate its effectiveness. Compared to traditional methods that consider only rainfall uncertainty or treat soil properties as deterministic, the framework provides a broader range of safety factor values and more precise estimates of critical rainfall durations. It also reveals that the probability of failure during a single rainfall event decreases, while annual failure probability increases gradually with more frequent rainfall events. By integrating spatial soil variability and rainfall uncertainty within a unified framework, this study advances landslide risk assessments and provides practical tools for slope stability analysis under real-world conditions.

Abstract Image

基于二元降雨和多元土壤随机场的非饱和边坡降雨失稳的概率框架
降雨是引发全球滑坡的关键因素,边坡失稳概率是评估滑坡风险的关键指标。虽然土壤性质的空间变异性和降雨的不确定性显著影响边坡破坏概率,但有限的研究同时解决了这些因素。现有的研究要么强调土壤性质的空间变异性,要么强调降雨的不确定性,往往忽略了它们的综合效应。为了解决这一差距,本研究引入了一个综合概率框架,该框架将土壤空间变异性和降雨不确定性纳入基于蒙特卡罗模拟的概率边坡渗流分析模型中。多变量土壤随机场被用来表示空间变异性,而降雨不确定性是用强度和持续时间的二元分布来建模的。这种方法可以推导出关键指标,包括单次降雨事件下边坡破坏的概率、年度破坏概率和多年的破坏概率。将提议的框架应用于埃塞俄比亚Sawala Laska公路项目的一个土坡,以证明其有效性。与只考虑降雨不确定性或将土壤性质视为确定性的传统方法相比,该框架提供了更大范围的安全系数值和更精确的临界降雨持续时间估计。单次降雨事件的失效概率减小,而随着降雨事件的频繁,年失效概率逐渐增大。通过在统一的框架内整合空间土壤变异性和降雨不确定性,本研究推进了滑坡风险评估,并为现实条件下的边坡稳定性分析提供了实用工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Bulletin of Engineering Geology and the Environment
Bulletin of Engineering Geology and the Environment 工程技术-地球科学综合
CiteScore
7.10
自引率
11.90%
发文量
445
审稿时长
4.1 months
期刊介绍: Engineering geology is defined in the statutes of the IAEG as the science devoted to the investigation, study and solution of engineering and environmental problems which may arise as the result of the interaction between geology and the works or activities of man, as well as of the prediction of and development of measures for the prevention or remediation of geological hazards. Engineering geology embraces: • the applications/implications of the geomorphology, structural geology, and hydrogeological conditions of geological formations; • the characterisation of the mineralogical, physico-geomechanical, chemical and hydraulic properties of all earth materials involved in construction, resource recovery and environmental change; • the assessment of the mechanical and hydrological behaviour of soil and rock masses; • the prediction of changes to the above properties with time; • the determination of the parameters to be considered in the stability analysis of engineering works and earth masses.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信