| Summary: | Protecting coastal infrastructure requires a thorough understanding of coastal processes and wave propagation from deep water. The southeast Queensland coast is exposed to a highly dynamic variety of wave sources including high-energy tropical cyclones, persistent trade winds, east coast lows and Southern Ocean storms. Strong effects of currents on wave propagation often occur near tidal entrances, however the impact of strong currents on wave propagation offshore is rarely considered. The effect of the East Australian Current (EAC) and its variability on deep-water wave propagation to the coast is the focus of this study. We explore wave-current interaction by process-based modelling of the EAC and its influence on wave propagation to coastal waters. Data from a suite of deep water and nearshore monitoring buoys in Southeast Queensland were analysed to study the wave transformation under the influence of the EAC. These data were compared to the Centre for Australian Weather and Climate Research (CAWCR) hindcast wave model data and used for calibration of a local numerical model employed in this study. The results indicate that the wave hindcast model tends to underestimate significant wave height during highenergy events. To address this limitation, an artificial neural network (ANN) model is employed, incorporating output from a hindcast-driven numerical model. The ANN model successfully improves the wave hindcast data used as wave boundaries, thereby enhancing the performance of the local numerical model in accurately representing deep and nearshore wave data. We conducted tests with the coupled wave and hydrodynamic models to compare wave propagation under various scenarios, including tidal forcing, boundary current input from regional models, and local and regional wind conditions. These results demonstrate the variability of the EAC, but also reveal an underestimation of the current compared to observed data. No Full Text
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