Application of TOPSIS and AHP models in subsurface layers’ competence evaluation - case study of Ilaramokin, Southwestern Nigeria | 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 Application of TOPSIS and AHP models in subsurface layers’ competence evaluation - case study of Ilaramokin, Southwestern Nigeria Adeyemo Igbagbo Adedotun, Akande Victor Oluwatimilehin, Ayokunle Adewale Akinlalu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2373590/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Incessant collapse of buildings associated with geotechnical incompetence in different part of Nigeria and the rapid growth of Ilaramokin town near Akure Southwestern Nigeria provided the motivation for this work. Two multi-criteria decision analysis approaches were used in integrating geoelectric parameters (topsoil resistivity, weathered layer resistivity and bedrock resistivity), static water level measurements and geology in evaluating the subsurface geotechnical competence of Ilaramokin. Thirty (30) vertical electrical sounding, eighty-six (86) static water level measurement and geological map were used. The VES results were presented as topsoil, weathered layer and bedrock resistivity maps. The vertical electrical sounding (VES) results delineated three to five geoelectrical layers which are the A, H, K, KH, QH and HKH. The resistivity of the topsoil, weathered layer and bedrock varies from 48–701, 31–1065, 14–139, 132–6582 Ωm respectively while their thickness very from 0.4–4.1, 1.3–11.6 and 4.0–20.1 m in the three upper layers respectively. The VES results, static water level measurement and the geology were integrated using both TOPSIS and AHP models to produced geotechnical competence maps. Consistency test and grainsize analysis were carried out on 10 soil samples obtained across the area to validate the geotechnical competence model maps produced using both TOPSIS and AHP models. The validation showed that geotechnical model map produced from TOPSIS model have higher percentage (90%) of correlation with consistency tests and grain size analysis compared to that of AHP model (70%). Subsurface competence geoelectric parameters geotechnical Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-2373590","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":159899195,"identity":"a4c9e867-99fe-4702-8e75-cf6db697cccf","order_by":0,"name":"Adeyemo Igbagbo Adedotun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYBACNiCWALPYGx9AhA4QrYXnsAFENSEtDHAtEslEauFjP/zwxsc2m2h+ycds0h9qGOT4biSwPfyCz2E8acaWM9vScmfOTmaTOHCMwVjyRgK7sQxevySYSfO2Hc7dcDv/mMQBNobEDUBbpCXwaeF//k36b9v/3A03DwNt+cdQT1iLRI6ZNGPbgdwNN5jZJA62MSQYALVIfsCr5U2xZc+55NyZPcnMFmf7JAxnnnnYJo1HB4N8f/rGGz/K7HL72Q8z3qj4ZiPPdzz5mOQPfHpAgJENzgR5grGBmYeQFoY/6GYQtGUUjIJRMApGEgAAkLpOz6K8c48AAAAASUVORK5CYII=","orcid":"","institution":"Federal University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Adeyemo","middleName":"Igbagbo","lastName":"Adedotun","suffix":""},{"id":159899196,"identity":"fe9c65b2-10e1-46c7-86ca-25630d4ea0e8","order_by":1,"name":"Akande Victor Oluwatimilehin","email":"","orcid":"","institution":"Federal University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Akande","middleName":"Victor","lastName":"Oluwatimilehin","suffix":""},{"id":159899197,"identity":"e2adc0e8-4c4a-42bc-a72e-a06143231900","order_by":2,"name":"Ayokunle Adewale Akinlalu","email":"","orcid":"","institution":"Federal University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Ayokunle","middleName":"Adewale","lastName":"Akinlalu","suffix":""},{"id":159899198,"identity":"31dfc3a3-f5c4-4c89-8ccc-4990b9b14ed8","order_by":3,"name":"Sheriff Olumide Sanusi","email":"","orcid":"","institution":"Federal University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Sheriff","middleName":"Olumide","lastName":"Sanusi","suffix":""}],"badges":[],"createdAt":"2022-12-13 10:59:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2373590/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2373590/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":30388095,"identity":"abbb6ee2-505f-4d3e-8c35-1eb34d841efa","added_by":"auto","created_at":"2022-12-15 17:20:14","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":847255,"visible":true,"origin":"","legend":"","description":"","filename":"ApplicationofTOPSISandAHPmodelsinsubsurfacelayerscompetenceevaluationcasestudyofIlaramokinSouthwesternNigeria.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2373590/v1_covered.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Application of TOPSIS and AHP models in subsurface layers’ competence evaluation - case study of Ilaramokin, Southwestern Nigeria","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"
[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Subsurface, competence, geoelectric parameters, geotechnical","lastPublishedDoi":"10.21203/rs.3.rs-2373590/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2373590/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIncessant collapse of buildings associated with geotechnical incompetence in different part of Nigeria and the rapid growth of Ilaramokin town near Akure Southwestern Nigeria provided the motivation for this work. Two multi-criteria decision analysis approaches were used in integrating geoelectric parameters (topsoil resistivity, weathered layer resistivity and bedrock resistivity), static water level measurements and geology in evaluating the subsurface geotechnical competence of Ilaramokin. Thirty (30) vertical electrical sounding, eighty-six (86) static water level measurement and geological map were used. The VES results were presented as topsoil, weathered layer and bedrock resistivity maps. The vertical electrical sounding (VES) results delineated three to five geoelectrical layers which are the A, H, K, KH, QH and HKH. The resistivity of the topsoil, weathered layer and bedrock varies from 48\u0026ndash;701, 31\u0026ndash;1065, 14\u0026ndash;139, 132\u0026ndash;6582 Ωm respectively while their thickness very from 0.4\u0026ndash;4.1, 1.3\u0026ndash;11.6 and 4.0\u0026ndash;20.1 m in the three upper layers respectively. The VES results, static water level measurement and the geology were integrated using both TOPSIS and AHP models to produced geotechnical competence maps. Consistency test and grainsize analysis were carried out on 10 soil samples obtained across the area to validate the geotechnical competence model maps produced using both TOPSIS and AHP models. The validation showed that geotechnical model map produced from TOPSIS model have higher percentage (90%) of correlation with consistency tests and grain size analysis compared to that of AHP model (70%).\u003c/p\u003e","manuscriptTitle":"Application of TOPSIS and AHP models in subsurface layers’ competence evaluation - case study of Ilaramokin, Southwestern Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-12-15 17:20:04","doi":"10.21203/rs.3.rs-2373590/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"
[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"47125ea4-77c7-4c3c-a9af-4c133188f80a","owner":[],"postedDate":"December 15th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-03-05T08:44:26+00:00","versionOfRecord":[],"versionCreatedAt":"2022-12-15 17:20:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2373590","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2373590","identity":"rs-2373590","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.