2023: Efficient modeling of wave generation and propogation in a semi-enclosed estuary, Washington, U.S.A.


Accurate, and high-resolution wave statistics are critical for regional hazard mapping and planning. However, long-term simulations at high spatial resolution are often computationally prohibitive. Here, multiple rapid frameworks including fetch-limited, look-up-table (LUT), and linear propagation are combined and tested in a large estuary exposed to both remotely (swell) and locally generated waves. Predictions are compared with observations and a traditional SWAN implementation coupled to a regional hydrodynamic model. Fetch-limited and LUT approaches both perform well where local winds dominate with errors about 10%–20% larger than traditional SWAN predictions. Combinations of these rapid approaches with linear propagation methods where remotely generated energy is present also perform well with errors 0%–20% larger than traditional SWAN predictions. Model–model comparisons exhibit lower variance than comparisons to observations suggesting that, while model implementation impacts prediction skill, model boundary conditions (winds, offshore waves) may be a dominant source of error. Overall results suggest that with a relatively small loss in prediction accuracy, simulations computation cost can be significantly reduced (by 2–4 orders of magnitude) allowing for high resolution and long-term predictions to adequately define regional wave statistics.