Authors: Hari Dhital, Sujan Maharjan, Bong-Chul Seo – Missouri University of Science and Technology; Witold F. Krajewski – The University of Iowa; Wendy Pearson, Scott Dummer – Missouri Basin River Forecast Center, NOAA
Title: A CIROH flood inundation mapping (FIM) ecosystem: towards a unified framework for flood mapping, evaluation, and dissemination
Presentation Type: Poster Presentation
Abstract: Accurate and scalable Flood Inundation Mapping (FIM) is essential for disaster preparedness, emergency response, and climate risk assessment, particularly as flood frequency increases globally. Despite advances in operational forecasting frameworks, flood map generation, accuracy evaluation, and access to high-resolution benchmark datasets remain fragmented or limited, technically complex, and difficult to reproduce at scale. No integrated, community-accessible platform currently unifies these components into a coherent, end-to-end ecosystem. This work presents a unified FIM ecosystem comprising three tightly integrated core components. The first, FIMserv, streamlines the NOAA Office of Water Prediction (OWP) operational Height Above Nearest Drainage (HAND) FIM framework for US-scale flood inundation mapping. FIMserv supports multi-watershed and multi-event simulations by incorporating retrospective and forecast discharge inputs from the National Water Model (NWM) v3.0, USGS, and global hydrological models such as GeoGLOWS, and is deployed across local and cloud environments.
The second, FIMeval, establishes a standardized, open-source evaluation framework that connects directly to FIMbench- a rigorously quality-controlled benchmark database providing multiple tiers of flood maps across the CONUS. FIMbench offers an interactive web platform for exploring benchmarks of FIM extent and availability, querying events, and directly retrieving datasets. Its high-level APIs streamline benchmark FIM retrieval and integration within evaluation workflows and beyond. The integration with FIMeval supports both pixel-based accuracy metrics and impact-based assessments of building footprints against flood model outcomes and geographic regions. All components are being progressively integrated into FIMbox—a highly flexible, modular testbed that unifies flood-mapping and evaluation workflows across local and cloud environments, including CIROH 2i2c, with a composable, API-driven architecture that adapts to diverse institutional pipelines and operational contexts. This ecosystem reduces technical barriers to operational flood modeling, standardizes evaluation practices, and provides essential data infrastructure for rigorous, scalable assessment.