Identification of Flash Flood Zones by using RS & GIS and MCDA

Identification of Flash Flood Zones by using RS & GIS and MCDA | 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 Identification of Flash Flood Zones by using RS & GIS and MCDA HANUMANTHU RAMAMOHAN, S. K. Ray, B. Bhargavi, B. Balakrishna, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8681165/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Flash floods are among the most destructive hazards, causing sudden loss of life, infrastructure damage, and environmental degradation, particularly in climate sensitive and rapidly urbanizing regions. The study aims to generate flash flood susceptibility maps using land use land cover, slope, lithology, drainage density, rainfall, and elevation through Multi-Criteria Decision Analysis, Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). The results reveal clear spatial variations in flash flood susceptibility across the study area. High and very high risk zones are mainly associated with low elevation, steep slope transitions, dense drainage networks, and impervious land use land cover classes. Receiver Operating Characteristic based validation confirms strong predictive accuracy, indicating the robustness of the proposed fuzzy MCDA framework. The generated thematic maps, including LULC, slope, lithology, drainage density, rainfall, and elevation, along with the final flash flood susceptibility map, provide valuable decision support tools for urban planners, engineers, disaster management authorities, and policymakers. The integration of Fuzzy AHP, Fuzzy TOPSIS, and MCDA ensures realistic handling of uncertainty and accurate prioritization of flood prone zones. Municipal bodies can apply the results for land use zoning, infrastructure design, and stormwater planning. Disaster response agencies benefit from improved preparedness and evacuation planning, while farmers and local communities gain awareness for safer settlements and agricultural activities, supporting sustainable and climate-resilient development. Remote Sensing (RS) and Geographic Information System (GIS) based flash flood assessment integrates land use, slope, drainage, rainfall and elevation to map susceptibility zones for disaster preparedness and risk mitigation. Remote Sensing Geographic Information System Multi-Criteria Decision Analysis Fuzzy Analytic Hierarchy Process Fuzzy Technique for Order Preference by Similarity to Ideal Solution Receiver Operating Characteristic Full Text Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 10 Mar, 2026 Reviewers invited by journal 04 Feb, 2026 Editor invited by journal 03 Feb, 2026 Editor assigned by journal 25 Jan, 2026 First submitted to journal 24 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. We do this by developing innovative software and high quality services for the global research community. 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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-8681165","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":585913858,"identity":"7249a18c-71b0-4fa2-a8d8-c5fc0ab2543a","order_by":0,"name":"HANUMANTHU RAMAMOHAN","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABE0lEQVRIiWNgGAWjYFACHghlAOMbMDAfAFISMkRrkTBgYEsA0TykaOExQBLHBLrtvQc/F+6xizZnP3tM6kbNnTpziZzPr27UWPAwsB8+ugGLFrMz55KlZzxLzt3Zk5cmnXPsmYTljNxt1jnHgA7jSUu7gU3LjRwDaZ4DzLkbDuSYSeewHZYwuJG7zTiHDahFgscMhxbj3zwH6nM3nH8D1PIPpCXnmXHOP7xazIC2HM7dAGLktoG1MD/ObcOj5cwZM2ueA8eBWt4YW+f2HZbccOaZGXNunwQPGy6/HO8xvs1zoBrosBzD2znfDvMbHE9+/DnnW50cP/vhY9i0YAVsEmCSWOUgwPyBFNWjYBSMglEw7AEARK5nnAK/AToAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-9918-3078","institution":"Aditya Institute of Technology and Management","correspondingAuthor":true,"prefix":"","firstName":"HANUMANTHU","middleName":"","lastName":"RAMAMOHAN","suffix":""},{"id":585913859,"identity":"7a0f9864-a574-422d-894f-eaeec7f1cc76","order_by":1,"name":"S. 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