Community-Oriented Data Integration and Communication Framework for Streamflow Forecast Models and Flood Inundation Map Products

Kento Sugiyama, Carlos Erazo Ramirez, Ibrahim Demir

Access to critical flood risk information is often limited by expert-driven workflows that require specialized software, representing a barrier to stakeholder engagement and effective science communication. This study presents a generalized web-based framework that integrates federal datasets for real-time scenario-based flood forecasting and mapping at the CONUS scale. By leveraging state-of-the-art client-side technologies, including WebAssembly, Web Workers, and IndexedDB, we developed an on-demand geoprocessing framework for flood inundation maps directly in the browser. The flood maps can be generated based on flood forecast outputs from the National Water Model and products from the Office of Water Prediction Flood Inundation Mapping. The framework also provides FEMA HAZUS damage assessment capabilities applied to property data from the National Structure Inventory. The platform’s capabilities are demonstrated through a case study of the 2019 Midwestern Floods, showcasing its value as an accessible and scalable tool for emergency managers, planners, and communities to assess flood risks.