Drivers of extreme water levels in a large, urban, high-energy coastal estuary – A case study of the San Francisco Bay
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Abstract
Reliable and long-term hindcast data of water levels are essential in quantifying return period and values of extreme water levels. In order to inform design decisions on a local flood control district level, process-based numerical modeling has proven an essential tool to provide the needed temporal and spatial coverage for different extreme value analysis methods. To determine the importance of different physical processes to the extreme water levels we developed a process-based numerical model (Delft3D Flexible Mesh) and applied it to simulate a large, urban, high-energy coastal estuary (the San Francisco Bay). The unstructured grid with 1D/2DH model elements, allows for efficient model simulations and therefore it was possible to simulate over 70 years between 1950 and 2019. Results show significant skill in reproducing observations for the entire modeled time period with an average root-mean-square error of 8.0 cm. A process-based modeling approach allows for the explicit in- and exclusion of different physical processes to quantify their importance to the extremes. For the 100-year still water level (SWL), tide (70%) and non-tidal residual (NTR) (25%) explain the majority of the simulated high water levels in the Bay relative to Mean Higher High Water (MHHW). However, closer to the Delta, local fluvial inflow increases in importance. For longer return periods, the importance of tide decreases and the importance of remote NTRs and fluvial inflow increases.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Drivers of extreme water levels in a large, urban, high-energy coastal estuary – A case study of the San Francisco Bay |
| Series title | Coastal Engineering |
| DOI | 10.1016/j.coastaleng.2021.103984 |
| Volume | 170 |
| Year Published | 2021 |
| Language | English |
| Publisher | Elsevier |
| Contributing office(s) | Pacific Coastal and Marine Science Center |
| Description | 103984, 12 p. |
| Country | United States |
| State | California |
| Other Geospatial | San Francisco Bay |
| Google Analytic Metrics | Metrics page |