Three-Dimensional Canopy Morphology and Wind Dynamics Govern Global Rainfall Interception

Three-Dimensional Canopy Morphology and Wind Dynamics Govern Global Rainfall Interception | 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 Three-Dimensional Canopy Morphology and Wind Dynamics Govern Global Rainfall Interception Qingliang Li, Xiaochun Jin, Zhongwang Wei, Cheng Zhang, Wei Shangguan, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8346448/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Accurate simulation of rainfall interception is critical for understanding the global water cycle, yet most earth system models rely on simplified, leaf area index (LAI)-centric vegetation representations that neglect the three-dimensional (3D) structure of plant canopies, introducing substantial structural uncertainty. Here we introduce Feature-Constrained Deep Symbolic Regression (FC-DSR), an interpretable artificial intelligence framework that derives explicit parameterizations for canopy interception. Global analyses show that 3D canopy morphology (canopy depth and width) and wind dynamics exert stronger control on interception than LAI. The resulting morphology-based parameterizations substantially outperform conventional LAI-based approaches, increasing site-level interception loss Kling–Gupta efficiency by 0.27–0.39. Budyko-based water-balance analyses confirm the improved interception scheme, with enhanced evapotranspiration at nearly 70% of global flux sites and stronger runoff dynamics across six major river basins. Implementation of the new scheme in the CoLM land surface model improves runoff simulations for 71.5% of U.S. catchments and better reproduces discharge variability in representative sites. Global applications further reveal highly nonlinear responses of interception to changes in rainfall intensity and vegetation structure. Together, these results highlight fundamental limitations of LAI-centered models and demonstrate that explicit representation of 3D canopy architecture is critical for reliable prediction of the terrestrial water balance. Earth and environmental sciences/Hydrology Earth and environmental sciences/Climate sciences/Hydrology Full Text Additional Declarations There is NO Competing Interest. Supplementary Files supplementary.docx SUPPLEMENTARY INFORMATION Cite Share Download PDF Status: Under Review 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. 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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-8346448","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":573120538,"identity":"898815ba-cfbf-42b6-a63b-be195b65839b","order_by":0,"name":"Qingliang 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