DFlee: An Agent-Based Model for Flood-Induced Population Displacement

DFlee: An Agent-Based Model for Flood-Induced Population Displacement | 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 DFlee: An Agent-Based Model for Flood-Induced Population Displacement Alireza Jahani, Michael J. Puma, Laura Harbach, Maziar Ghorbani, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7923329/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 14 You are reading this latest preprint version Abstract Each year, natural disasters displace millions globally, highlighting the need for accurate population movement predictions to improve disaster response. This study presents DFlee, an agent-based model for simulating flood-induced evacuations. Built on the Flee toolkit, originally developed for conflict-driven displacement, DFlee has been adapted for flood scenarios through revised rule sets, refined parameters, and new algorithms. The model integrates flood data and agent behaviour to simulate evacuation and return decisions across diverse hydrological contexts. We ground synthetic scenarios within U.S. Geological Survey (USGS) flood frequency classifications, testing DFlee across riverine minor floods (10--25 year recurrence), riverine major floods (50--100 year), coastal storm surges (25--50 year), and compound flooding (100+ year). Given the limited availability of empirical flood-displacement datasets, validation is conducted using stylised facts, robust behavioural regularities reported in the literature. We focus on three well-documented facts: (i) evacuees prefer closer safe locations, (ii) most households return promptly after floodwaters recede, and (iii) evacuation timing is heterogeneous, with delayed responses influenced by social observation. DFlee reproduces these dynamics, providing confidence in its behavioural realism. The model also demonstrates near-linear scalability, completing simulations with up to 160,000 agents in under 10 minutes, making it a practical tool for forecasting displacement trends and informing humanitarian decisions in flood-prone regions. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Hydrology Earth and environmental sciences/Natural hazards Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Reviews received at journal 24 May, 2026 Reviewers agreed at journal 18 May, 2026 Reviewers agreed at journal 15 May, 2026 Reviews received at journal 15 May, 2026 Reviewers agreed at journal 24 Apr, 2026 Reviews received at journal 27 Nov, 2025 Reviewers agreed at journal 10 Nov, 2025 Reviewers agreed at journal 06 Nov, 2025 Reviewers agreed at journal 06 Nov, 2025 Reviewers invited by journal 05 Nov, 2025 Editor assigned by journal 05 Nov, 2025 Editor invited by journal 28 Oct, 2025 Submission checks completed at journal 27 Oct, 2025 First submitted to journal 27 Oct, 2025 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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This study presents DFlee, an agent-based model for simulating flood-induced evacuations. Built on the Flee toolkit, originally developed for conflict-driven displacement, DFlee has been adapted for flood scenarios through revised rule sets, refined parameters, and new algorithms. The model integrates flood data and agent behaviour to simulate evacuation and return decisions across diverse hydrological contexts. We ground synthetic scenarios within U.S. Geological Survey (USGS) flood frequency classifications, testing DFlee across riverine minor floods (10--25 year recurrence), riverine major floods (50--100 year), coastal storm surges (25--50 year), and compound flooding (100+ year). Given the limited availability of empirical flood-displacement datasets, validation is conducted using stylised facts, robust behavioural regularities reported in the literature. We focus on three well-documented facts: (i) evacuees prefer closer safe locations, (ii) most households return promptly after floodwaters recede, and (iii) evacuation timing is heterogeneous, with delayed responses influenced by social observation. DFlee reproduces these dynamics, providing confidence in its behavioural realism. 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