Wave Parameter Hindcasting in a Lake Using the SWAN Model

Abstract. Wind-induced wave characteristics are one of the most important factors in the design
of coastal and marine structures. Therefore, accurate estimation of wave parameters is of considerable
importance. The wave climate study can be conducted by eld measurements, empirical studies, physical
modeling and numerical simulations. In this paper, the skill of a third-generation spectral model called
SWAN has been evaluated in the prediction of wave parameters. The varying wind and wave climate of
Lake Erie in the year 2002 has been used for evaluation of the model. The signicant wave height (Hs)
and the peak spectral wave period (Tp) were the parameters employed in the study and the model has
been executed in a nonstationary mode. The linear and exponential growth from wind input, four-wave
nonlinear interaction, whitecapping and bottom friction have been considered in the simulation. The results
of this study show that in the investigated case, the average scatter index of SWAN is about 19 percent for
signicant wave height and 23 percent for the peak period. The error of the SWAN model in prediction of
the wave height and period reduced about 3 percent after elimination of wave heights less than 0.5 meters.
It was also found that using the cumulative steepness method for whitecapping dissipation yields worse
results for signicant wave height and better results for peak spectral period estimation. After using this
method, the average scatter index for the prediction of Hs increased about 5 percent and decreased more
than 4 percent for Tp. It should be mentioned that the computational time required by using this method
is approximately more than twice that of the Komen option.