Soil-erosion events on arable land are nowcast by machine learning

Soil-erosion events on arable land are nowcast by machine learning | 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 Brief Communication Soil-erosion events on arable land are nowcast by machine learning ‪Pedro Batista, Markus Möller, Karsten Schmidt, Timm Waldau, Kay Seufferheld, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4846916/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 estimates of the location, timing, and severity of soil-erosion events on arable land have eluded erosion-prediction technology for decades. Here, for the first time, we demonstrate how a machine learning model can nowcast the occurrence and relatively rank the severity of erosion events on arable field parcels at the regional scale with high accuracy and interpretable outputs. Our findings pave the way for dynamic, large-scale erosion-monitoring systems to achieve healthy soils and improve food security. Scientific community and society/Agriculture Earth and environmental sciences/Solid Earth sciences/Geomorphology Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryInformationv2.5.pdf Supplementary information 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-4846916","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Brief Communication","associatedPublications":[],"authors":[{"id":335231185,"identity":"4e87fc59-8e10-4b8b-a806-c10a260a5922","order_by":0,"name":"‪Pedro 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