Predicting tidal flooding of urbanized embayments: A modeling framework and data requirements: Fid-Bau Portal

Predicting tidal flooding of urbanized embayments: A modeling framework and data requirements

Gallien, T.W. / Schubert, J.E. / Sanders, B.F.

Abstract Numerous urbanized embayments in California are at risk of flooding during extreme high tides caused by a combination of astronomical, meteorologic and climatic factors (e.g., El Niño), and the risk will increase as sea levels rise and storminess intensifies. Across California, the potential exists for billions of dollars in losses by 2100 and predictive inundation models will be relied upon at the local level to plan adaptation strategies and forecast localized flood impacts to support emergency management. However, the predictive skill of urban inundation models for extreme tide events has not been critically examined particularly in relation to data quality and flood mapping methodologies. With a case study of Newport Beach, California, we show that tidal flooding can be resolved along streets and at individual parcels using a 2D hydraulic inundation model that captures embayment amplification of the tide, overtopping of flood defenses, and overland flow along streets and into parcels. Furthermore, hydraulic models outperform equilibrium flood mapping methodologies which ignore hydraulic connectivity and are strongly biased towards over-prediction of flood extent. However, infrastructure geometry data including flood barriers, street and parcel elevations are crucial to accurate flood prediction. A real time kinematic (RTK) survey instrument with an error of approximately 1cm (RMSE) is found to be suitable for barrier height measurement, but an error of approximately15cm (RMSE) typical of aerial laser scanning or LiDAR is found to be inadequate. Finally, we note that the harbor waterfront in Newport Beach is lined by a patchwork of public and private parcels and flood barriers of varied designs and integrity. Careful attention to hydraulic connectivity (e.g., low points and gaps in barriers) is needed for successful flood prediction.