Compounding hazards increase flood economic losses across Europe

Compounding hazards increase flood economic losses across Europe | 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 Compounding hazards increase flood economic losses across Europe Michele Ronco, Alois Tilloy, Christina Corbane, Damien Delforge, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7075867/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 Compound events—combinations of multiple hazards that contribute to societal or environmental risk—can significantly exacerbate disaster impacts. However, their effect on flood-related losses remains insufficiently quantified. In this study, we compile a novel, pan-European multi-hazard dataset spanning 1981–2020 at sub-national resolution. This dataset reveals that nearly 80% of recorded flood events in Europe involve compounding hazards, encompassing meteorological extremes such as heatwaves, cold spells, and windstorms, alongside anomalous river discharge linked to floods and droughts, with an increasing trend over time. Notably, the top 1% of these events, in terms of economic losses, are all compound. We introduce a novel metric to characterize the complexity of these compound events in a single index. By integrating flood loss records with data on hazards, exposure, and vulnerability, our ensemble machine learning models predict that flood losses for compound events are 3.4 times higher than for single events. Using explainable AI, we demonstrate that higher compound hazard complexity significantly amplifies flood damage, with a relative increase in impact of 0.34 units in high-vulnerability regions compared to low-vulnerability areas. To our knowledge, this study provides the first comprehensive, data-driven evidence that compound events are associated with higher flood losses across Europe. This underscores the importance of incorporating compound hazard information into risk modeling and disaster preparedness strategies and offers insights that could support the development of multi-hazard early warning systems as part of the Early Warnings for All initiative. Earth and environmental sciences/Natural hazards Earth and environmental sciences/Environmental social sciences/Climate-change impacts/Governance disaster risk management compound events extreme weather climate change machine learning explainable AI Full Text Additional Declarations There is NO Competing Interest. 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. 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-7075867","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":486536647,"identity":"ce892b0b-1794-46b5-b7b3-8abce5041f3f","order_by":0,"name":"Michele 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