Lévy-induced Stochastic Differential Equation Models in Rainfall-Runoff Systems for Assessing Extreme Hydrological Event Risks

Lévy-induced Stochastic Differential Equation Models in Rainfall-Runoff Systems for Assessing Extreme Hydrological Event Risks | 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 Lévy-induced Stochastic Differential Equation Models in Rainfall-Runoff Systems for Assessing Extreme Hydrological Event Risks Sianou Ezéckiel Houénafa, Erick K. Erick K. Ronoh, Olatunji Johnson, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4618006/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Feb, 2025 Read the published version in Stochastic Environmental Research and Risk Assessment → Version 1 posted 4 You are reading this latest preprint version Abstract Stochastic Differential Equations (SDEs) driven by Gaussian noise have proven effective for studying the dynamics of river basin discharges, while accounting for uncertainties inherent in rainfall-runoff systems. However, these uncertainties clearly exhibit many non-Gaussian characteristics, necessitating the use of more complex noises to model various levels of variability and anomalies in river basin discharges, ultimately enhancing the assessment of extreme hydrological risks. This paper considers uncertainties in rainfall-runoff systems by developing a Langevin-type SDE driven by non-Gaussian α-stable Lévy noises. The different methods’ applicability is demonstrated on the Ouémé at Bonou river basin, Benin. The SDE model parameters were estimated through a developed heuristic method based on a Monte Carlo simulation approach. To access extreme hydrological event risks, the equivalent Fractional Fokker-Planck Equation (FFPE) was derived and solved numerically using an adaptive finite difference method. The results showed that Lévy stable noises better capture uncertainties in rainfall-runoff systems, highlighting anomalous diffusion in daily river basin discharges. The SDE and FFPE model solutions were consistent, aligning with actual observations, and the risks of extreme events were evaluated in terms of daily and cumulative probabilities. Rainfall-runoff Uncertainties α-stable Lévy noises Fractional FokkerPlanck Equation Extreme events Benin Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Feb, 2025 Read the published version in Stochastic Environmental Research and Risk Assessment → Version 1 posted Editorial decision: Revision requested 22 Jun, 2024 Editor assigned by journal 22 Jun, 2024 Submission checks completed at journal 22 Jun, 2024 First submitted to journal 21 Jun, 2024 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-4618006","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":317712763,"identity":"f79411af-efea-48e8-8864-3e396d6fe93f","order_by":0,"name":"Sianou Ezéckiel Houénafa","email":"data:image/png;base64,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","orcid":"","institution":"Pan African University Institute for Science, Technology and Innovation, Pan African University","correspondingAuthor":true,"prefix":"","firstName":"Sianou","middleName":"Ezéckiel","lastName":"Houénafa","suffix":""},{"id":317712765,"identity":"796c97e0-62f0-4fc0-8404-4e2ff3123d44","order_by":1,"name":"Erick K. 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