{"paper_id":"42b38d75-abe7-41a5-a06d-9eb146104d2f","body_text":"Predicting Road Failure Susceptibility through Integrated Geologic, Geomorphologic, and Geotechnical Analysis: A Case Study from Southeastern 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 Article Predicting Road Failure Susceptibility through Integrated Geologic, Geomorphologic, and Geotechnical Analysis: A Case Study from Southeastern Nigeria Chukwuebuka Emeh, Ahaneku Chibuzo Valeria, Martins Josephine Chinonye This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8497806/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Inadequate engineering geological site investigations are major cause of road failure due to a lack of complete information for project design. Considering the cost of conducting site investigations and the need for the economical use of project funds, intensive sampling spacing is often sacrificed in favour of intuitive assumptions, leading to an increase in the error margin. For this reason, it became imperative to assess an alternative engineering geological site investigation method that provides contiguous data over a large area at low cost. To this end, digital elevation model (DEM) – a remotely sensed data was integrated with geological field investigations and geotechnical laboratory tests to ascertain the geotechnical properties of the underlying geologic materials in areas obscured by the built environment. The derived geologic, geotechnical, and DEM data were integrated and geospatially distributed within the study area using geostatistical methods. This resulted in geomorphologic and lithostratigraphic maps, which revealed the spatial distributions of the slope and geologic materials, respectively. The distribution of the road failure events (RFEs) on the geomorphologic and lithologic map revealed that flat areas underlain by argillaceous materials are more susceptible to road failure than steep areas underlain by arenaceous materials. Boundaries between argillaceous and arenaceous materials are also susceptible to road failure because of the hydraulic conditions of the area. The high predictability of RFEs following this method was evidence that it could serve as an alternative low-cost method for engineering geological site investigations. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Natural hazards Earth and environmental sciences/Solid earth sciences DEM Site Investigations Remote Sensing Soil Geotechnical Properties Geostatistics Engineering Geology Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 16 Apr, 2026 Reviewers agreed at journal 06 Apr, 2026 Reviewers agreed at journal 06 Apr, 2026 Reviews received at journal 31 Mar, 2026 Reviewers agreed at journal 26 Mar, 2026 Reviewers agreed at journal 20 Jan, 2026 Reviewers invited by journal 15 Jan, 2026 Editor invited by journal 05 Jan, 2026 Editor assigned by journal 02 Jan, 2026 Submission checks completed at journal 02 Jan, 2026 First submitted to journal 01 Jan, 2026 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-8497806\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":575963526,\"identity\":\"8a2df08b-a36c-4510-a283-1a9ce0c6c37b\",\"order_by\":0,\"name\":\"Chukwuebuka 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Considering the cost of conducting site investigations and the need for the economical use of project funds, intensive sampling spacing is often sacrificed in favour of intuitive assumptions, leading to an increase in the error margin. For this reason, it became imperative to assess an alternative engineering geological site investigation method that provides contiguous data over a large area at low cost. To this end, digital elevation model (DEM) \\u0026ndash; a remotely sensed data was integrated with geological field investigations and geotechnical laboratory tests to ascertain the geotechnical properties of the underlying geologic materials in areas obscured by the built environment. The derived geologic, geotechnical, and DEM data were integrated and geospatially distributed within the study area using geostatistical methods. This resulted in geomorphologic and lithostratigraphic maps, which revealed the spatial distributions of the slope and geologic materials, respectively. The distribution of the road failure events (RFEs) on the geomorphologic and lithologic map revealed that flat areas underlain by argillaceous materials are more susceptible to road failure than steep areas underlain by arenaceous materials. Boundaries between argillaceous and arenaceous materials are also susceptible to road failure because of the hydraulic conditions of the area. 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