Assessing Coastal Water-Level Variability in the Salish Sea via a Spatially Extensive Network of Real-time Water-level Sensors and Hydrodynamic Modeling

Daniel J. Nowacki1, Andrew William Stevens2, Sean C Crosby2, Eric Grossman2, Nathan R VanArendonk3 and Babak Tehranirad2, (1)USGS Pacific Coastal and Marine Science Center, Santa Cruz, CA, United States, (2)USGS Pacific Coastal and Marine Science Center Santa Cruz, Santa Cruz, CA, United States, (3)Western Washington University, Bellingham, WA, United States
Continuous water levels measured by USGS at seven locations across Puget Sound in 2018–2019 are combined with data from five existing NOAA tide gauges in Puget Sound and the Strait of Juan de Fuca to evaluate the spatial and temporal dynamics of water-level variability across the Salish Sea, a large fjord-like estuarine system. Sensors surveyed to a geodetic datum with 2–3 cm total error help inform potential storm and flooding impacts around the highly populated Puget Sound area and greater Salish Sea region. Non-tidal residual water levels (NTRs)—i.e., observed minus tidally predicted—exhibit variability of up to 1 m at most sites. NTR ranges were greater in the Strait of Juan de Fuca and South Puget Sound relative to the Main Basin of Puget Sound. On average, the local inverse barometric effect (IBE) from atmospheric pressure is responsible for approximately 60% of the variation in NTR, with IBE being more important for sites farther up-estuary. The root-mean-square (RMS) of the NTR time series was 0.15 m; adjusting for IBE reduces the RMS to 0.08 m (if IBE were fully responsible for the total NTR, the IBE-adjusted RMS would be zero). Additional factors determining NTRs include interannual variability, coastal upwelling, and local winds; the magnitudes of these additional forcing mechanisms varied spatially and temporally. Measured total water levels (tides and NTRs) were compared with output from a USGS high-resolution hydrodynamic water-level and flooding model implemented in Delft3D Flexible Mesh using full wind and pressure forcing fields. Model output captures NTR timing and magnitude trends. The observed water-level variability and model output inform flood and coastal-change risk hazard in the U.S. Pacific Northwest and improve understanding of mechanisms that cause coastal impacts and change.