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Advanced Flood Risk Management: Integration of High-Resolution Geospatial Data and Models

This research focuses on coastal and inland flooding, driven by extreme high tides, waves, and intensified precipitation. Utilizing advanced technology integration and high-performance computing, the study enhances geospatial data coverage and resolution, enabling accurate flood risk mapping in topographically complex regions. Key findings include the need for improved vertical accuracy in modeling overtopping thresholds and recognizing the impact of tidal amplification and wave effects on flood extent. The work aims to develop predictive models and tools to effectively manage flood risks in areas vulnerable to climate change.

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Advanced Flood Risk Management: Integration of High-Resolution Geospatial Data and Models

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  1. Sanders Lab, UC Irvine • Motivation • Coastal flooding from extreme high tides and waves / sea level rise • Inland flooding from intensified precipitation/levee failure • Emergency Management • Zoning • Infrastructure Assessment and Planning • Technology Integration • Improved coverage and resolution of geospatial data • High performance computing • Advanced numerical methods • Predictive models for flood risk management • Physically representative parameters • High resolution (< 10 m ) • Timely • Developing knowledge base and tools for accurate mapping of flood impacts in topographically complex regions Aerial LiDARSpatial Resources Baldwin Hills FloodDWR Flood Simulation, Houston, TX

  2. Newport Harbor, CA Study • Flooding from high tides and waves • Highest tides in winter and summer • Non-tidal anomalies of ~0.3 m can exacerbate flooding (El Niño storms) • Wave effects magnified at high tide • Factors affecting flood map accuracy • Tidal amplification • Inventory of flow paths • Vertical accuracy of overtopping thresholds • Wave setup / wave overtopping flows • Erosion of flow barriers • Routing (hydraulic versus static) • Findings to date • Static models overestimate flood extent • LiDAR insufficient for overtopping thresholds • LiDAR vertical accuracy (~15 cm) • RTK survey vertical accuracy (~3 cm) • Flood extent sensitive to tide height • 4.4 cm tide height bias causes 250% increase in flood extent January 10, 2005 Static (Gallien et al., in prep.)

  3. San Francisco Bay, CA NOAA Tsunami Inundation DEM (30 m) Spatially variable grid resolution Emphasis on topographic features (levees) near mean sea level Simulations 2050: 16 inches SLR 2100: 55 inches SLR Tide: 12 hr period; Great Diurnal Range for SF Computing: ~1 hr on 64 processors SF Bay 2100 South SF Bay 2050 South SF Bay 2100

  4. Acknowledgements • We thank the National Science Foundation (CMMI-Resilient and Sustainable Infrastructure Program) and the UC Water Resources Center for grants that supported this work • And we thank the City of Newport Beach and Los Angeles County for their gracious cooperation • http://sanders.eng.uci.edu

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