Assessing Rainfall Disaggregation Techniques and Subdaily Rainfall Patterns Across Uganda’s Tropical Climatic Zones

Assessing Rainfall Disaggregation Techniques and Subdaily Rainfall Patterns Across Uganda’s Tropical Climatic Zones | 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 Assessing Rainfall Disaggregation Techniques and Subdaily Rainfall Patterns Across Uganda’s Tropical Climatic Zones Martin Okirya, JA Du Plessis This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6946352/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 Accurate subdaily rainfall data are critical for the design of hydrological infrastructure and effective flood risk assessment, particularly in data-scarce regions such as Uganda, where rainfall records are typically available only at daily resolutions. This research used observed hourly rainfall data to derive site-specific parameters for daily rainfall disaggregation. It then evaluated the performance of several disaggregation methods, including empirical approaches, statistical distributions, the Bartlett–Lewis rectangular pulse (BLRP) stochastic model, and the aligned time distribution (TD) method. The method performance was assessed via the root mean square error (RMSE), mean absolute error (MAE), percent bias (PBIAS), and Kolmogorov–Smirnov (KS) tests. To demonstrate the practical applicability of the derived parameters, the designed TD method was applied to disaggregate daily rainfall and construct intensity‒duration‒frequency (IDF) curves. The results revealed that rainfall events across all stations were temporally skewed, with peak intensities generally occurring within the first 1–3 hours of a storm. Among the methods tested, the aligned TD method consistently performed best, achieving the lowest RMSE values (1.02–1.35 mm) and KS statistics (0.14–0.24) across all stations. The derived IDF curves revealed sharper intensity peaks for shorter durations, closely reflecting the observed storm characteristics. The research concludes that the aligned TD method offers a robust and reliable approach for disaggregating daily rainfall into subdaily values suitable for IDF curve development. Finally, this research recommends the use of site-specific disaggregation parameters in hydrological infrastructure design and emphasizes the need for further research into the transferability of storm profiles across diverse regions. Hydrology Civil Engineering Environmental Engineering Intensity-Duration-Frequency Empirical Aligned Bartlett–Lewis Rectangular Pulse Gamma Exponential Lognormal Weibull Generalized Extreme Value Full Text Additional Declarations The authors declare no competing interests. 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-6946352","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":474528217,"identity":"1ee10de4-1b74-4068-83fc-15e77661dffd","order_by":0,"name":"Martin Okirya","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIie3OMYvCQBCG4QmB5YqBtBMCSWe9EoiNeH9lg5DKwsrKIjZec5g2/o6A9R4Lsdm7ay0DthbaWKqxtHEDNhb7lAMv3wBY1hvyQG2Pp8sQvc6Jv6gzp2RZ6OddE650z/1gKuay80yt2R7QTat/nTQwH0H0ZYid799tPCWWbnaTAYd63F7E88SlPxGUHNsEEwImwQVDwqIDD1BQWhW6TS4SmNc8TxB0EqDkMYdJQs5SApJhhdr3++tchLTLZpSuxkhkWPmU6qc55Vf0CrWh43kURoVh5ZG4f2pZlmW97gZwVEGDp4EV4QAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0009-1913-7107","institution":"Stellenbosch University","correspondingAuthor":true,"prefix":"","firstName":"Martin","middleName":"","lastName":"Okirya","suffix":""},{"id":474528255,"identity":"2026f78b-24ff-46e7-9830-d4099cbddc70","order_by":1,"name":"JA Du Plessis","email":"","orcid":"https://orcid.org/0000-0001-8093-6711","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"JA","middleName":"","lastName":"Du Plessis","suffix":""}],"badges":[],"createdAt":"2025-06-21 17:50:46","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6946352/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6946352/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85294828,"identity":"0242ab7d-f28c-4f4c-9991-910a8d75a6e9","added_by":"auto","created_at":"2025-06-24 10:47:10","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1364925,"visible":true,"origin":"","legend":"","description":"","filename":"reviewedManuscriptpreprint.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6946352/v1_covered_2ffa9292-4bff-4178-a9cb-7531b0e29094.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAssessing Rainfall Disaggregation Techniques and Subdaily Rainfall Patterns Across Uganda’s Tropical Climatic Zones\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Stellenbosch University","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":"Intensity-Duration-Frequency, Empirical, Aligned, Bartlett–Lewis Rectangular Pulse, Gamma, Exponential, Lognormal, Weibull, Generalized Extreme Value","lastPublishedDoi":"10.21203/rs.3.rs-6946352/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6946352/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAccurate subdaily rainfall data are critical for the design of hydrological infrastructure and effective flood risk assessment, particularly in data-scarce regions such as Uganda, where rainfall records are typically available only at daily resolutions. This research used observed hourly rainfall data to derive site-specific parameters for daily rainfall disaggregation. It then evaluated the performance of several disaggregation methods, including empirical approaches, statistical distributions, the Bartlett\u0026ndash;Lewis rectangular pulse (BLRP) stochastic model, and the aligned time distribution (TD) method. The method performance was assessed via the root mean square error (RMSE), mean absolute error (MAE), percent bias (PBIAS), and Kolmogorov\u0026ndash;Smirnov (KS) tests. To demonstrate the practical applicability of the derived parameters, the designed TD method was applied to disaggregate daily rainfall and construct intensity‒duration‒frequency (IDF) curves. The results revealed that rainfall events across all stations were temporally skewed, with peak intensities generally occurring within the first 1\u0026ndash;3 hours of a storm. 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