Regional sediment thickness mapping via microtremor HVSR spatial variability

Regional sediment thickness mapping via microtremor HVSR spatial variability | 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 Regional sediment thickness mapping via microtremor HVSR spatial variability YiFan Yang, LiJing Shi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6326507/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Due to its simplicity and cost-effectiveness, the microtremor Horizontal-to-Vertical Spectral Ratio method is widely used for estimating site-specific fundamental frequencies and sediment thicknesses. However, most existing applications estimate sediment thickness site-by-site, overlooking the spatial variability of microtremor HVSR frequencies ( \(\:{f}_{mHVSR}\) ). This study leverages the spatial correlation of \(\:{f}_{mHVSR}\) ​ to develop a regional sediment thickness mapping approach. Using microtremor HVSR data from 22 sites across a study area spanning several hundred square kilometers, where sediment thickness ranges from a few meters to several tens of meters, this study employs geostatistical methods to analyze the spatial variability of \(\:{f}_{mHVSR}\) . Sediment thickness estimates from the proposed and existing methods are compared with measured values for validation. Finally, based on the HVSR and sediment thickness data from these sites, a regional sediment thickness model for the study area was developed. The results show that the spatial correlation range of \(\:{f}_{mHVSR}\) in the study area is 5.07 km, highlighting its regional variability. Compared to existing methods, the proposed approach not only significantly reduces prediction errors but also ensures a more uniform spatial distribution of errors. Furthermore, by comparing with the measured sediment thickness from 80 boreholes, the regional sediment thickness model developed in this study accurately captures the spatial variation characteristics of sediment thickness within the study area. Additionally, we propose an optimal strategy for selecting reference boreholes, recommending the one whose \(\:{f}_{mHVSR}\) ​ most closely matches the detection site within the spatial correlation range. By integrating \(\:{f}_{mHVSR}\) spatial variability, this study providing a more precise and efficient method for sediment thickness mapping framework. Regional sediment thickness Spatial variability Semivariogram Microtremor Horizontal-to-Vertical Spectral Ratio method Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 07 May, 2025 Reviews received at journal 04 May, 2025 Reviews received at journal 04 May, 2025 Reviewers agreed at journal 28 Apr, 2025 Reviewers agreed at journal 27 Apr, 2025 Reviewers agreed at journal 25 Apr, 2025 Reviewers invited by journal 25 Apr, 2025 Editor assigned by journal 23 Apr, 2025 Submission checks completed at journal 23 Apr, 2025 First submitted to journal 28 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-6326507","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":449317285,"identity":"7d640f89-b89d-4ee5-83ab-10f8d717d1fc","order_by":0,"name":"YiFan Yang","email":"","orcid":"","institution":"Institute of Engineering Mechanics,China Earthquake Administration.Key Laboratory of Earthquake Engineering and Engineering Vibration,China Earthquake Administration","correspondingAuthor":false,"prefix":"","firstName":"YiFan","middleName":"","lastName":"Yang","suffix":""},{"id":449317287,"identity":"77e28177-a709-4bc9-b53f-f8401fa15d19","order_by":1,"name":"LiJing Shi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArUlEQVRIiWNgGAWjYDACCeYGgw8GpGlhbDCcQbIWZh6SdMjPbmwotimwiWZgP/yA4ecOIrQY3DnYYJxjkJbbwJNmwNh7hhgtEokgLYdzGxhyGJgZ24hx2AygFguD/7kN/G+I1MJwA6iFweBAboMEsbYYALUY9hgk57ZJPDM42Eucw5KPGfz4Y5fbz5/88MFPohzGwMAGjkg2ID5AnAYGBuYHxKocBaNgFIyCEQoA58syc3HpomkAAAAASUVORK5CYII=","orcid":"","institution":"Institute of Engineering Mechanics,China Earthquake Administration.Key Laboratory of Earthquake Engineering and Engineering Vibration,China Earthquake Administration","correspondingAuthor":true,"prefix":"","firstName":"LiJing","middleName":"","lastName":"Shi","suffix":""}],"badges":[],"createdAt":"2025-03-28 08:53:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6326507/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6326507/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81626216,"identity":"21071080-1757-4854-9c85-e62db3994dc9","added_by":"auto","created_at":"2025-04-29 10:21:04","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1017764,"visible":true,"origin":"","legend":"","description":"","filename":"RegionalsedimentthicknessmappingviamicrotremorHVSRspatialvariability.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6326507/v1_covered_cfdca9c9-2c4f-42eb-883c-d9b7cefddd97.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Regional sediment thickness mapping via microtremor HVSR spatial variability","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":"discover-geoscience","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Geoscience](https://www.springer.com/journal/44288)","snPcode":"44288","submissionUrl":"https://submission.nature.com/new-submission/44288","title":"Discover Geoscience","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Regional sediment thickness, Spatial variability, Semivariogram, Microtremor Horizontal-to-Vertical Spectral Ratio method","lastPublishedDoi":"10.21203/rs.3.rs-6326507/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6326507/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDue to its simplicity and cost-effectiveness, the microtremor Horizontal-to-Vertical Spectral Ratio method is widely used for estimating site-specific fundamental frequencies and sediment thicknesses. However, most existing applications estimate sediment thickness site-by-site, overlooking the spatial variability of microtremor HVSR frequencies (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{f}_{mHVSR}\\)\u003c/span\u003e\u003c/span\u003e). This study leverages the spatial correlation of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{f}_{mHVSR}\\)\u003c/span\u003e\u003c/span\u003e​ to develop a regional sediment thickness mapping approach. Using microtremor HVSR data from 22 sites across a study area spanning several hundred square kilometers, where sediment thickness ranges from a few meters to several tens of meters, this study employs geostatistical methods to analyze the spatial variability of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{f}_{mHVSR}\\)\u003c/span\u003e\u003c/span\u003e. Sediment thickness estimates from the proposed and existing methods are compared with measured values for validation. Finally, based on the HVSR and sediment thickness data from these sites, a regional sediment thickness model for the study area was developed. The results show that the spatial correlation range of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{f}_{mHVSR}\\)\u003c/span\u003e\u003c/span\u003e in the study area is 5.07 km, highlighting its regional variability. Compared to existing methods, the proposed approach not only significantly reduces prediction errors but also ensures a more uniform spatial distribution of errors. Furthermore, by comparing with the measured sediment thickness from 80 boreholes, the regional sediment thickness model developed in this study accurately captures the spatial variation characteristics of sediment thickness within the study area. Additionally, we propose an optimal strategy for selecting reference boreholes, recommending the one whose \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{f}_{mHVSR}\\)\u003c/span\u003e\u003c/span\u003e​ most closely matches the detection site within the spatial correlation range. By integrating \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{f}_{mHVSR}\\)\u003c/span\u003e\u003c/span\u003e spatial variability, this study providing a more precise and efficient method for sediment thickness mapping framework.\u003c/p\u003e","manuscriptTitle":"Regional sediment thickness mapping via microtremor HVSR spatial variability","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-29 09:48:58","doi":"10.21203/rs.3.rs-6326507/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-07T19:47:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-04T15:13:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-04T04:36:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"251986812391114981775080465783889642978","date":"2025-04-28T20:50:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"332363210645958757622252207205243761537","date":"2025-04-27T22:48:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3052388644691753718166709078014367297","date":"2025-04-25T17:26:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-25T16:46:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-23T09:54:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-23T09:49:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Geoscience","date":"2025-03-28T08:45:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-geoscience","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Geoscience](https://www.springer.com/journal/44288)","snPcode":"44288","submissionUrl":"https://submission.nature.com/new-submission/44288","title":"Discover Geoscience","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b3e67682-e480-483b-b40b-900fc42f51b4","owner":[],"postedDate":"April 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-06-20T12:08:43+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-29 09:48:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6326507","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6326507","identity":"rs-6326507","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}