Analysis of Temporal Patterns, Monitoring Techniques, and Risk Evolution for Floods and Cyclones in Sri Lanka (1975–2025): Evidence for Paradigm Shift from Reactive Response to Anticipatory Resilience

Analysis of Temporal Patterns, Monitoring Techniques, and Risk Evolution for Floods and Cyclones in Sri Lanka (1975–2025): Evidence for Paradigm Shift from Reactive Response to Anticipatory Resilience | 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 Analysis of Temporal Patterns, Monitoring Techniques, and Risk Evolution for Floods and Cyclones in Sri Lanka (1975–2025): Evidence for Paradigm Shift from Reactive Response to Anticipatory Resilience Partheepan Kulasegaram, Muneeb M. Musthafa, Bhavan Thangamani, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8616632/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract Sri Lanka has witnessed a struggle with floods and cyclones, transitioning from occasional emergencies to persistent and growing threats. This study provides the first consolidated, long-term temporal analysis synthesising 50 years (1975–2025) of meteorological trends with the parallel evolution of monitoring technology. Using Mann-Kendall trend analysis and Pettitt change-point detection, statistically significant increases in cyclonic disturbance frequency (1.3 events/year in 1975–1985 to 4.1 events/year in 2015–2025; Sen's slope: +0.73 systems/decade, 95% CI: +0.58 to +0.88 systems/decade, p<0.001) and extreme rainfall intensity (12.2 mm/decade increase in annual maximum 1-day rainfall; 95% CI: 9.4–14.8 mm/decade) were demonstrated. Change-point analysis identified 1998 as a statistically significant inflection year (Pettitt test, p<0.05), after which the cyclonic rainfall contribution increased by 18–25% in the northern and eastern provinces of Sri Lanka. While monitoring capabilities have advanced from rain-gauge dependence (pre-1990) through the satellite era (1990s–2000s) to real-time Earth observation integration (post-2015), a critical institutional gap persists: advanced forecasts fail to trigger effective grassroots actions. This "last-mile" problem is operationally defined as the persistent gap between the forecast lead time (72+ hours by 2025) and the actual evacuation completion times (18–36 hours), quantified through lead-time analysis by comparing forecast windows to evacuation completion times. It revealed no proportional improvement in response efficacy despite a 6-fold increase in forecast lead time (from 12–24 hours in 1975–1990 to 72–168 hours in 2015–2025). An integrated Sri Lanka Multi-Hazard Risk Monitoring and Decision-Support Platform (SL-RISK) that couples technical data integration with community-embedded monitoring, impact-based forecasting, and pre-arranged institutional response mechanisms is proposed, with a phased 18–36-month implementation roadmap. Without addressing this governance-technology mismatch, technological advances remain underutilised, perpetuating cycles of preventable disaster losses among vulnerable populations. Temporal trend analysis Cyclones Extreme rainfall Monitoring system evolution Institutional integration Early warning efficacy Sri Lanka Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 23 Feb, 2026 Reviews received at journal 22 Feb, 2026 Reviews received at journal 18 Feb, 2026 Reviews received at journal 15 Feb, 2026 Reviewers agreed at journal 10 Feb, 2026 Reviewers agreed at journal 10 Feb, 2026 Reviewers agreed at journal 09 Feb, 2026 Reviewers agreed at journal 08 Feb, 2026 Reviewers agreed at journal 08 Feb, 2026 Reviewers invited by journal 08 Feb, 2026 Editor invited by journal 30 Jan, 2026 Editor assigned by journal 24 Jan, 2026 Submission checks completed at journal 24 Jan, 2026 First submitted to journal 16 Jan, 2026 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-8616632","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":588810930,"identity":"67e50998-5444-46c1-a8fb-aa05e48a84a8","order_by":0,"name":"Partheepan Kulasegaram","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYJACZiA24AexEgqI08HYDNIi2QDSYkCKFoMDIDYxWszZzz5/XFBhY2x8fnXihwcGDPL8Ygfwa7HsSTdsnnEmzczsxtvNEkCHGc6cnYBfi8GBNMZm3rbDNmY3zm4AaUkwuE1Iy/lnQC3//tsYzzi7+QdxWm6AbGk4YGbA37uNOFssZzxjnM1zLNlY4gbvNosEAwnCfjHnT2P4zFNjZ9jff3bzzR8VNvL80oQcBmdJgFVK4FeOqoX/AGHVo2AUjIJRMDIBANp5Q1Ikxk0XAAAAAElFTkSuQmCC","orcid":"","institution":"United Nations Development Programme, Sri Lanka","correspondingAuthor":true,"prefix":"","firstName":"Partheepan","middleName":"","lastName":"Kulasegaram","suffix":""},{"id":588810932,"identity":"deefb3d0-eb2c-41e4-9f43-4ab767e437e4","order_by":1,"name":"Muneeb M. 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While monitoring capabilities have advanced from rain-gauge dependence (pre-1990) through the satellite era (1990s–2000s) to real-time Earth observation integration (post-2015), a critical institutional gap persists: advanced forecasts fail to trigger effective grassroots actions. This \"last-mile\" problem is operationally defined as the persistent gap between the forecast lead time (72+ hours by 2025) and the actual evacuation completion times (18–36 hours), quantified through lead-time analysis by comparing forecast windows to evacuation completion times. It revealed no proportional improvement in response efficacy despite a 6-fold increase in forecast lead time (from 12–24 hours in 1975–1990 to 72–168 hours in 2015–2025). 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