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- W175034705 abstract "In this thesis, the wave prediction model SWAN is validated on field data obtained from wave growth experiments that were done in Lake George, a shallow lake in Australia. SWAN, which is an acronym for Simulation of WAves in Nearshore areas, is a numerical model, developed at the University of Technology in Delft, to obtain estimates of wave parameters in coastal areas, lakes and estuaries from given wind-, bottom- and current conditions. In the first part of the thesis, a number of academic test cases has been executed with SWAN. Growth curves for dimensionless energy as function of dimensionless fetch for three flat bottom cases with different dimensionless depths were calculated with SWAN. These curves showed reasonable agreement with empirically derived growth curve formulas. The regions of dimensionless depth for which the dissipative processes play an important role on the fully developed wave height were determined with the SWAN model. According to the test results, it appeared that the process of depth induced wave breaking has significant influence on the fully developed wave height for dimensionless depths smaller than 0.1 and the process of bottom friction for dimensionless depths between approximately 0.1 and 2. For the validation of SWAN on the field data from Lake George, three cases with differing wind speeds were selected out of the data set. In this lake, eight wave measuring stations were established along the longest axis. A number of SWAN test series was executed in order to find the combination of different options to formulate the wave physics, which yielded best results in comparison with the measured significant wave heights at the stations. Starting with a standard case with default settings of these options, the influence of one certain process (for example the wind input and the bottom friction) on the wave growth was researched in each test serie. The mean of the relative absolute error in significant wave height for all three cases was used to determine a 'best run', which is the SWAN run with the optimal choice of these options. It appeared that this error was 0.16 for the standard case; for the best run, this error was 0.06. The SWAN energy density spectra for this best run showed reasonable agreement with the measured spectra as well." @default.
- W175034705 created "2016-06-24" @default.
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- W175034705 date "1996-08-01" @default.
- W175034705 modified "2023-09-26" @default.
- W175034705 title "Validation of the wave prediction model SWAN using field data from Lake George, Australia" @default.
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