Statistical and Nonlinear Dynamics of Rogue Waves in Varying Bathymetric Environments

Statistical and Nonlinear Dynamics of Rogue Waves in Varying Bathymetric Environments | 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 Statistical and Nonlinear Dynamics of Rogue Waves in Varying Bathymetric Environments Reine Matar, Nizar Abcha, Nicolas Lecoq, Emma-Imen Turki This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7632046/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 31 Jan, 2026 Read the published version in Journal of Ocean Engineering and Marine Energy → Version 1 posted 10 You are reading this latest preprint version Abstract Investigating the transformation of ocean surface waves from intermediate to shallow water is essential for predicting extreme coastal events such as rogue waves. In this study, controlled wave-flume experiments employing dispersive focusing were conducted to generate breaking waves with varying spectral bandwidths and nonlinearities. Two bathymetric configurations were examined: a single-sloped profile (Bathy_1) and a compound profile with a steep slope followed by a flat bottom (Bathy_2). The nonlinear dynamics were assessed using wavelet-based bicoherence, whereas the non-Gaussian behavior of rogue waves was investigated in both bathymetric configurations through statistical parameters derived from the time series. In Bathy_2, autobicoherence revealed stronger nonlinear interactions over the steep slope. Kurtosis increased during wave focusing in both bathymetries, while skewness diverged: it decreased and shifted negative in Bathy_2 but increased in Bathy_1. After breaking, both metrics returned to initial levels. Probability distributions in both cases deviated from the Rayleigh model, with the largest discrepancies at the slope end. The compound profile (Bathy_2) showed a higher probability of extreme wave heights. These findings advance understanding of wave evolution by linking bathymetric variability to rogue wave generation and statistical behavior. They highlight the need to incorporate non-Gaussian dynamics and bathymetric effects into predictive frameworks for coastal hazards. Ultimately, the results provide a scientific basis for improving the reliability of coastal engineering design, early warning systems, and risk mitigation strategies in regions vulnerable to extreme wave events. Coastal extreme events Rogue waves Wave flume experiments Dispersive focusing Nonlinear wave behavior Skewness and kurtosis Probability distribution functions Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 31 Jan, 2026 Read the published version in Journal of Ocean Engineering and Marine Energy → Version 1 posted Editorial decision: Revision requested 13 Nov, 2025 Reviews received at journal 12 Nov, 2025 Reviewers agreed at journal 06 Nov, 2025 Reviews received at journal 02 Oct, 2025 Reviewers agreed at journal 22 Sep, 2025 Reviewers agreed at journal 22 Sep, 2025 Reviewers invited by journal 22 Sep, 2025 Editor assigned by journal 18 Sep, 2025 Submission checks completed at journal 18 Sep, 2025 First submitted to journal 16 Sep, 2025 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. 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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-7632046","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":523718353,"identity":"8043d6f7-1638-4e46-866a-117b6eb74c23","order_by":0,"name":"Reine Matar","email":"","orcid":"","institution":"Normandy University, UNICAEN, UNIROUEN, CNRS, UMR","correspondingAuthor":false,"prefix":"","firstName":"Reine","middleName":"","lastName":"Matar","suffix":""},{"id":523718354,"identity":"12a3f37d-49a4-429b-976e-d415cafc7796","order_by":1,"name":"Nizar 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