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The performance of the spectral wind wave model SWAN in tidal inlet seas was assessed on the basis of extensive wave measurements conducted in the Amelander Zeegat tidal inlet and the Dutch Eastern Wadden Sea, as well as relevant data from other inlets, lakes, estuaries and beaches. We found that the 2006 default SWAN model (version 40.51), the starting point of the investigation, performed reasonably well for measured storm conditions, but three aspects required further attention. First, over the near-horizontal tidal flats, the computed ratio of integral wave height over water depth showed an apparent upper limit using the default depth-limited wave breaking formulation and breaker parameter, resulting in an underprediction of wave heights. This problem has been largely solved using a new breaker formulation. The second aspect concerns wave-current interaction, specifically the wave age effect on waves generated in ambient current, and a proposed enhanced dissipation in negative current gradients. Third, the variance density of lower-frequency wind waves from the North Sea penetrating through the inlets into the Wadden Sea was underpredicted. This was improved by reducing the bottom friction dissipation relative to that of the default model. After a combined calibration, these improvements have resulted in a relative bias reduction in Hm0 from -3% to -1%, in Tm-1,0 from -7% to -3%, and in Tm01 from -6% to -2%, and consistent reductions in scatter, compared to the 2006 default model., Hydraulic Engineering, Civil Engineering and Geosciences

The spectral wind wave model SWAN (Booij et al. 1999) plays a key role in the estimation of the Hydraulic Boundary Conditions (HBC) for the primary sea defences of the Netherlands. Since some uncertainty remains with respect to the reliability of the wind wave model SWAN for application to the geographically complex area of the Wadden Sea, a number of activities have been initiated under the project ‘SBW Waddenzee’ to devise a strategy for the improvement of the model. In this regard, hindcast studies carried out with SWAN for the Amelander Zeegat in the Wadden Sea have shown that significant computational times are required to achieve results with the desired levels of numerical accuracy. This has prompted investigations into ways of reducing the computational time of SWAN. In the present study, various methods for reducing the simulation time of SWAN have been evaluated and refined, to facilitate the efficient execution of large numbers of SWAN simulations (possibly in combination with parallel computing) during the HBC computations. The methods evaluated here include the following: the Dynamical Deactivation Method (DDM), the Multigrid (MG) method, deactivating the action limiter and quadruplet interaction in the surf zone, improving the efficiency of the DIA quadruplet interaction term, and batch run organization using the so-called hotfile functionality of SWAN. These methods were all evaluated using the same set of eight field cases (featuring the Amelander Zeegat, the Eems-Dollard, Petten and Lake Sloten), and the same evaluation criteria, taking into account the total CPU time, iteration behaviour and mean convergence errors. This study has shown the DDM and batch run approaches to be the most successful techniques, both yielding reductions in total simulation time for Wadden Sea applications in the order of 31-35% with respect to the default SWAN model. The use of these methods affect model outcomes, which for the significant wave height and mean period can, SBW

Evolution of the wave field in a coastal bay is investigated, by comparison between field observations and numerical simulations using a spectral wave model (Simulating WAves Nearshore (SWAN)). The simulations were conducted for the passage of an extratropical storm, during which surface elevation spectra were bimodal owing to local wind-sea generation and swell propagation into the bay. SWAN was run in stationary and nonstationary mode for two whitecapping source term formulations. The first was developed by Komen et al. (1984) and is dependent on spectrally averaged wave steepness, and thus includes swell in the calculation of whitecapping dissipation and typically overestimates wind sea in the presence of swell. The second, proposed by van der Westhuysen et al. (2007), estimates whitecapping of wind sea locally in the wave spectrum and is not coupled to swell energy. This formulation reproduced the magnitude and shape of the observed wind-sea spectral peak much better than the previous formulation. Whitecapping dissipation rates have been estimated from observations, using the equilibrium range theory developed by Phillips (1985), and are well correlated with both wind speed and acoustic backscatter observations. These rates agree with SWAN estimates using the spectrally local expression, and provide additional physical validation for the whitecapping source term., Hydraulic Engineering, Civil Engineering and Geosciences

The spectral wind wave model SWAN plays a key role in the estimation of the Hydraulic Boundary Conditions (HBC) for the primary sea defences of the Netherlands. Since some uncertainty remains with respect to the reliability of SWAN for application to the geographically complex area of the Wadden Sea, a number of activities have been initiated under project H4918 ‘Uitvoering Plan van Aanpak SBW-RVW Waddenzee’ (Plan of Action on the Boundary Conditions for the Wadden Sea) to devise a strategy for the improvement of the model. In this context, hindcast and sensitivity studies carried out with SWAN for the Amelader Zeegat in the Wadden Sea have shown that significant computational times are required to achieve results with the desired levels of numerical accuracy. This finding has led to a drive towards exploring ways to reduce the computational time required by SWAN. The present study investigates the application of a multigrid method to SWAN, which would improve the initial guess used in the iterative solution procedure. The aim of the present study is to investigate the application of this multigrid method to stationary SWAN simulations of typical storm conditions in the Wadden Sea. It is firstly aimed to assess whether this method leads to a reduction in computational time in these hindcasts. A second, equally important aim is to determine whether the application of the multigrid method has any negative impacts on model accuracy. The application of a multigrid technique to SWAN was considered in two stages. During the first stage, multigrid operation is enabled by sequentially running two separate SWAN simulations - the first on a coarse computational grid and the second on the final, detailed grid resolution. The second stage, prompted by the positive results of the first stage, was to incorporate the multigrid into the SWAN source code. It was found that a reduction in geographical space appears to be the most promising candidate to use in the initial guess run. T, SBW

Civil Engineering and Geosciences