Assessing Long-Term Flood Risk and Elevation Ordinance Comparisons Using a Web-Based Geospatial Decision Tool

To support resilient community planning and informed hazard mitigation decisions, having an effective flood risk evaluation is very important especially in coastal and flood prone areas. This presentation is focused on the development of an interactive web-based decision-making platform designed to analyze future flood risk and elevation ordinance impacts across five parishes in Louisiana, USA. The website allows users to explore long-term flood risk projections and ordinance related costs over multiple future decades from 2030 to 2100. The platform integrates various geospatial datasets including multi-return-period flood depth projections, decadal population forecasts, and building inventories. Flood depth raster datasets are converted from raster to point data using python and then assigned to building data obtained from Coastal Protection and Restoration Authority (CPRA) using spatial join. Then the obtained datasets are used to calculate Average Annual Loss (AAL) for different elevation ordinances. This framework incorporates a range of flood elevation ordinances, including ASCE 24-14, ASCE 24-24, and freeboard-based standards (BFE +1’, +2’, and +3’), with ordinance costs and risk outcomes by decade. ArcGIS Pro is used for spatial analysis and 3D geospatial visualization, while interactive webpages and different elevation ordinance scenario comparisons are implemented with react vita app. To improve accessibility for non-technical users, the website integrates AI-driven features that assist users in navigating the tool, interpreting results, and comparing ordinance scenarios. The platform supports hotspot analysis, side-by-side visualization of present and future flood risks, and iterative refinement through user feedback sessions. Overall, this tool provides planners, homeowners, and policymakers with a forward-looking environment to assess flood mitigation strategies, ordinance performance, and population-driven risk changes over time by combining advanced spatial analytics with interactive and user-centered design.