Estimate of the Reduction in the Impact of Rainwater on Road Degradation in the Mbanya Catchment Area

Estimate of the Reduction in the Impact of Rainwater on Road Degradation in the Mbanya Catchment Area | 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 Estimate of the Reduction in the Impact of Rainwater on Road Degradation in the Mbanya Catchment Area Achille Clovice Goune, Bathelemy Essombo Essombo, Jean Calvin Seutche, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5849140/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 This article is part of the sustainable development of road infrastructure. It assesses the effects of rainwater on unpaved roads in the Mbanya catchment area between January 2019 and December 2023, and proposes mitigation measures. July is the month when the risk of deterioration on these unsealed roads is highest. The aim of the work is to limit the impact of rainwater on the deterioration of roads in the Mbanya catchment area. To this end, an experimental study was carried out to determine the initial water content in the soil and the quantity of quicklime needed to stabilise the soil. Genetic algorithms and neural networks were used to estimate the water content at different depths in the soil. The square correlation coefficient, with a value of around 0.72, and the root mean square error, with a value of around 0.37 on all the test data are performance indicators that demonstrate the high accuracy of the coupled genetic algorithm-neural network model. Porosity and the quantity of lime were used as input parameters for the model, and the results show that porosity and the quantity of lime have an influence on the evolution of the water content in the soil. The pavement construction project is possible on these unsealed roads in the Mbanya watershed, as the soils have a bearing capacity P ≥ .20MPa. However, the increase in water content can weaken as well as reduce the bearing capacity of the soil. Treating the soil with quicklime can lower the water content after water consumption and strengthen the bearing capacity. Modelling content rainwater degradation genetic algorithm neural networks 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. 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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-5849140","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":405636232,"identity":"c8bb9884-3638-4164-9b3c-e3262402cfc2","order_by":0,"name":"Achille Clovice Goune","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYPACCwYGZiD1AYjZ2InTIgHWwjgDpIWZaC1AwMwDJgmolXfvMXvwoUZCzuA488PHNr+2yfMxMzB++JiDW4vhmTPmhjOOSRgbHGYzNs7tu23YxszALDlzGx4tM3LMpHkbJBJnNvOwSef23GYEamFj5iWk5S9EC/tvy57b9gS1yEsAtTACtfQz8wDD6sftRIJaDHiOlUn2AP3Cz8xmLNnbcDu5jZmxGa9f5Nubt0n8qLGRY+M//PDDjz+3bee3Nx/88BGfLQeQeYxtYLIBt3qQLajSf/AqHgWjYBSMghEKAArpRn16cBlRAAAAAElFTkSuQmCC","orcid":"","institution":"University of Yaounde 1","correspondingAuthor":true,"prefix":"","firstName":"Achille","middleName":"Clovice","lastName":"Goune","suffix":""},{"id":405636233,"identity":"7e107a1b-d190-452b-bdc5-2beec44a4c58","order_by":1,"name":"Bathelemy Essombo Essombo","email":"","orcid":"","institution":"University of Yaounde 1","correspondingAuthor":false,"prefix":"","firstName":"Bathelemy","middleName":"Essombo","lastName":"Essombo","suffix":""},{"id":405636234,"identity":"65908f66-0b4a-429c-911e-dc5b29375aba","order_by":2,"name":"Jean Calvin Seutche","email":"","orcid":"","institution":"University of Yaounde 1","correspondingAuthor":false,"prefix":"","firstName":"Jean","middleName":"Calvin","lastName":"Seutche","suffix":""},{"id":405636235,"identity":"9c965fa1-6ee8-4ed6-b332-ae3a5674172e","order_by":3,"name":"Yannick Roger Ekani","email":"","orcid":"","institution":"University of Douala","correspondingAuthor":false,"prefix":"","firstName":"Yannick","middleName":"Roger","lastName":"Ekani","suffix":""},{"id":405636236,"identity":"67c17184-a66c-44c3-847f-70981ca84a05","order_by":4,"name":"Jean Luc Nsouandele","email":"","orcid":"","institution":"University of Maroua","correspondingAuthor":false,"prefix":"","firstName":"Jean","middleName":"Luc","lastName":"Nsouandele","suffix":""},{"id":405636237,"identity":"98e9957a-19df-4ce6-af58-b1b637cee1b4","order_by":5,"name":"Germain Hubert Ben-Bolie","email":"","orcid":"","institution":"University of Yaounde 1","correspondingAuthor":false,"prefix":"","firstName":"Germain","middleName":"Hubert","lastName":"Ben-Bolie","suffix":""}],"badges":[],"createdAt":"2025-01-17 12:23:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5849140/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5849140/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78598847,"identity":"1791a5fb-b277-4ee7-86ce-479d28b7be45","added_by":"auto","created_at":"2025-03-16 07:08:18","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":576173,"visible":true,"origin":"","legend":"","description":"","filename":"ArticleA7.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5849140/v1_covered_1d35f3c9-945d-4862-8c30-c62257f6fd15.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEstimate of the Reduction in the Impact of Rainwater on Road Degradation in the Mbanya Catchment Area \u003c/p\u003e","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":"Modelling, content, rainwater, degradation, genetic algorithm, neural networks","lastPublishedDoi":"10.21203/rs.3.rs-5849140/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5849140/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis article is part of the sustainable development of road infrastructure. It assesses the effects of rainwater on unpaved roads in the Mbanya catchment area between January 2019 and December 2023, and proposes mitigation measures. July is the month when the risk of deterioration on these unsealed roads is highest. The aim of the work is to limit the impact of rainwater on the deterioration of roads in the Mbanya catchment area. To this end, an experimental study was carried out to determine the initial water content in the soil and the quantity of quicklime needed to stabilise the soil. Genetic algorithms and neural networks were used to estimate the water content at different depths in the soil. The square correlation coefficient, with a value of around 0.72, and the root mean square error, with a value of around 0.37 on all the test data are performance indicators that demonstrate the high accuracy of the coupled genetic algorithm-neural network model. 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