Modeling coastal flooding in urbanized lowlands: a multi-dimensional high-resolution approach

                                                                                   

Brett F. Sanders, ProfessorTimu Gallien, Ph.D. Student

Civil and Environmental EngineeringUniversity of California, IrvineUC Center for Hydrologic Modelinghttp://sanders.eng.uci.edubsanders@uci.edu

 

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 LiDAR Spatial Resources

Flood Simulation, Houston, TX

Baldwin Hills Flood DWR

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 Static

January 10, 2005

(Gallien et al., in prep.)

San Francisco Bay, CANOAA Tsunami Inundation DEM (30 m)

Spatially variable grid resolution

Emphasis on topographic features (levees) near mean sea level

SF Bay 2100

South SF Bay 2050

South SF Bay 2100

Simulations2050: 16 inches SLR2100: 55 inches SLRTide: 12 hr period; Great Diurnal Range for SFComputing: ~1 hr on 64 processors

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