To provide coastal engineers and scientists with a detailed inter-comparison of widely used parametric wave transformation models, several models are tested and calibrated with extensive observations from 6 field experiments on barred and unbarred beaches. Using previously calibrated ("default") values of a free parameter γ, all models predict the observations reasonably well (median root-mean-square wave height errors are between 10% and 20%) at all field sites. Model errors can be reduced by roughly 50% by tuning γ for each data record. No tuned or default model provides the best predictions for all data records or at all experiments. Tuned γ differ for the different models and experiments, but in all cases γ increases as the hyperbolic tangent of the deep-water wave height, H o . Data from 2 experiments are used to estimate empirical, universal curves for γ based on H o . Using the new parameterization, all models have similar accuracy, and usually show increased skill relative to using default γ.Keywords: Wave models, surfzone, wave breaking, nearshore 2
IntroductionNumerical modeling increasingly is used to optimize coastal management and protection strategies. Nearshore wave transformation models used to predict currents, setup, and sediment transport range in complexity from wave-resolving, high-order solutions of the extended Boussinesq equations [Nwogu, 1993;Kennedy et al., 2000] to wave energy balances using parameterizations of breaking-wave dissipation [Battjes and Janssen, 1978;Thornton and Guza, 1983]. Here, the accuracy of the parametric models, widely used because they are easy to code and are computationally efficient, is examined.In all the models examined here, the breaking wave heights are assumed to follow simple probability distributions, and wave-breaking energy dissipation is parameterized using a theory for idealized bores. All the models contain a free parameter γ that can be tuned using wave height observations to provide more accurate predictions of the wave field at spatially dense locations, or to improve wave height forecasts for different time periods or locations.After the models are outlined (section 2), the observations are described (section 3), and the method of model analysis is explained (section 4). Next, the models are evaluated using the observations, and a new parameterization for γ is developed (section 5). The results are then discussed (section 6), and the conclusions are summarized (section 7).