A Method for Predicting Unsaturated Loess Landslides Based on Rainfall Intensity and Validation

A Method for Predicting Unsaturated Loess Landslides Based on Rainfall Intensity and Validation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Method for Predicting Unsaturated Loess Landslides Based on Rainfall Intensity and Validation xuanyu YANG, zhijie Sun This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6242866/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Oct, 2025 Read the published version in Natural Hazards → Version 1 posted 5 You are reading this latest preprint version Abstract Landslide prediction remains a pivotal yet enduring challenge in disaster risk reduction. This study presents a novel physical model tailored for unsaturated loess slopes in China’s Loess Plateau, uniquely integrating dynamic rainfall infiltration processes with depth-resolved shear strength degradation. Unlike conventional approaches reliant on static thresholds, the model quantifies stability through moisture-dependent shear strength and stability coefficients across soil depths, capturing the transient interplay between rainfall intensity and stratigraphic heterogeneity. Validation was achieved via meticulously designed laboratory experiments, where a 0.5 m high, 40° inclined slope with controlled drainage (10 cm gravel base) was subjected to simulated rainfall. Pore water pressure and volumetric moisture content were monitored at 5 cm depth intervals (L1–L5), revealing three distinct infiltration phases: rapid percolation, stabilization, and saturation. Key findings include: (1) Pore water pressure surges exponentially as saturation initiates, particularly in deeper layers; (2) Shear strength deteriorates progressively, with surface layers losing 70% of strength within 150 minutes, while deeper strata exhibit delayed but complete strength loss upon saturation; (3) Stability coefficients ( Fs ) decline nonlinearly with depth, transitioning from shallow sliding (residual strength insufficient to resist sliding forces) to deep-seated failure (total strength loss). The model’s reliability was further corroborated by numerical simulations replicating field-scale conditions, demonstrating its capacity to predict both timing and depth of slope instability. By bridging theoretical rigor with practical validation, this work advances landslide prediction frameworks, offering actionable insights for region-specific risk assessment and mitigation strategies in loess terrains. Loess Landslide Prediction Stability Coefficient Rainfall Intensity Full Text Cite Share Download PDF Status: Published Journal Publication published 08 Oct, 2025 Read the published version in Natural Hazards → Version 1 posted Reviewers agreed at journal 20 Mar, 2025 Reviewers invited by journal 19 Mar, 2025 Editor invited by journal 17 Mar, 2025 Editor assigned by journal 17 Mar, 2025 First submitted to journal 17 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6242866","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":430994975,"identity":"c776ad28-8b73-448a-80ea-8c7f7810e2ae","order_by":0,"name":"xuanyu YANG","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYBADHn5m5sMPSNFhwCPZzpZmQJIWBoPzPAoSxKm9kWPA+LPtj4zxYR6gxhqbaMJazpwxYOY5Y8Bjdpj3wAOGY2m5DQS1HO8xYGaoAGnhSzBgbDhMhJbDPAaMPwwMeIybeQwkiNMCtIWBB2gL0HlEapE8c6wA6BdjHonDwEBOIMYvfDeSNwBDTM6ev//w4QcfamwIa1E4wGH+A85LIKQcBOQb2B8Qo24UjIJRMApGMgAAAtQ4vGaiT4sAAAAASUVORK5CYII=","orcid":"","institution":"Chinese Academy of Sciences Wuhan Institute of Rock and Soil Mechanics","correspondingAuthor":true,"prefix":"","firstName":"xuanyu","middleName":"","lastName":"YANG","suffix":""},{"id":430994976,"identity":"b62909c0-a0d5-45ea-ae21-44f9aff6c5ed","order_by":1,"name":"zhijie Sun","email":"","orcid":"","institution":"Shanxi Transportation Research Institute","correspondingAuthor":false,"prefix":"","firstName":"zhijie","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2025-03-17 09:09:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6242866/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6242866/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11069-025-07611-7","type":"published","date":"2025-10-08T15:57:11+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":93420000,"identity":"68db283b-f564-4b00-bb68-acf72f7761bc","added_by":"auto","created_at":"2025-10-13 16:09:12","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":889185,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptsubmit.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6242866/v1_covered_5c03d58f-573e-49a1-9ba7-3ba24962d7fa.pdf"}],"financialInterests":"","formattedTitle":"A Method for Predicting Unsaturated Loess Landslides Based on Rainfall Intensity and Validation","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"natural-hazards","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nhaz","sideBox":"Learn more about [Natural Hazards](https://www.springer.com/journal/11069)","snPcode":"11069","submissionUrl":"https://submission.nature.com/new-submission/11069/3","title":"Natural Hazards","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Loess, Landslide, Prediction, Stability Coefficient, Rainfall Intensity","lastPublishedDoi":"10.21203/rs.3.rs-6242866/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6242866/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLandslide prediction remains a pivotal yet enduring challenge in disaster risk reduction. This study presents a novel physical model tailored for unsaturated loess slopes in China\u0026rsquo;s Loess Plateau, uniquely integrating dynamic rainfall infiltration processes with depth-resolved shear strength degradation. Unlike conventional approaches reliant on static thresholds, the model quantifies stability through moisture-dependent shear strength and stability coefficients across soil depths, capturing the transient interplay between rainfall intensity and stratigraphic heterogeneity. Validation was achieved via meticulously designed laboratory experiments, where a 0.5 m high, 40\u0026deg; inclined slope with controlled drainage (10 cm gravel base) was subjected to simulated rainfall. Pore water pressure and volumetric moisture content were monitored at 5 cm depth intervals (L1\u0026ndash;L5), revealing three distinct infiltration phases: rapid percolation, stabilization, and saturation. Key findings include: (1) Pore water pressure surges exponentially as saturation initiates, particularly in deeper layers; (2) Shear strength deteriorates progressively, with surface layers losing 70% of strength within 150 minutes, while deeper strata exhibit delayed but complete strength loss upon saturation; (3) Stability coefficients ( Fs ) decline nonlinearly with depth, transitioning from shallow sliding (residual strength insufficient to resist sliding forces) to deep-seated failure (total strength loss). The model\u0026rsquo;s reliability was further corroborated by numerical simulations replicating field-scale conditions, demonstrating its capacity to predict both timing and depth of slope instability. By bridging theoretical rigor with practical validation, this work advances landslide prediction frameworks, offering actionable insights for region-specific risk assessment and mitigation strategies in loess terrains.\u003c/p\u003e","manuscriptTitle":"A Method for Predicting Unsaturated Loess Landslides Based on Rainfall Intensity and Validation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-27 11:45:53","doi":"10.21203/rs.3.rs-6242866/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-03-20T05:03:23+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-19T11:05:57+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Natural Hazards","date":"2025-03-17T23:54:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-17T11:22:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Natural Hazards","date":"2025-03-17T05:05:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"natural-hazards","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nhaz","sideBox":"Learn more about [Natural Hazards](https://www.springer.com/journal/11069)","snPcode":"11069","submissionUrl":"https://submission.nature.com/new-submission/11069/3","title":"Natural Hazards","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"a1b8de5a-1e37-48fa-9888-dbe37e675fe3","owner":[],"postedDate":"March 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-13T16:06:38+00:00","versionOfRecord":{"articleIdentity":"rs-6242866","link":"https://doi.org/10.1007/s11069-025-07611-7","journal":{"identity":"natural-hazards","isVorOnly":false,"title":"Natural Hazards"},"publishedOn":"2025-10-08 15:57:11","publishedOnDateReadable":"October 8th, 2025"},"versionCreatedAt":"2025-03-27 11:45:53","video":"","vorDoi":"10.1007/s11069-025-07611-7","vorDoiUrl":"https://doi.org/10.1007/s11069-025-07611-7","workflowStages":[]},"version":"v1","identity":"rs-6242866","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6242866","identity":"rs-6242866","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}