Comparison of Implicit and Explicit Vegetation Representations in SWAN Hindcasting Wave Dissipation by Coastal Wetlands in Chesapeake Bay
Assessing the accuracy of nearshore numerical models—such as SWAN—is important to ensure their effectiveness in representing physical processes and predicting flood hazards. In particular, for application to coastal wetlands, it is important that the model accurately represents wave attenuation by v...
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Veröffentlicht in: | Geosciences (Basel) 2019-01, Vol.9 (1), p.8 |
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Sprache: | eng |
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Zusammenfassung: | Assessing the accuracy of nearshore numerical models—such as SWAN—is important to ensure their effectiveness in representing physical processes and predicting flood hazards. In particular, for application to coastal wetlands, it is important that the model accurately represents wave attenuation by vegetation. In SWAN, vegetation might be implemented either implicitly, using an enhanced bottom friction; or explicitly represented as drag on an immersed body. While previous studies suggest that the implicit representation underestimates dissipation, field data has only recently been used to assess fully submerged vegetation. Therefore, the present study investigates the performance of both the implicit and explicit representations of vegetation in SWAN in simulating wave attenuation over a natural emergent marsh. The wave and flow modules within Delft3D are used to create an open-ocean model to simulate offshore wave conditions. The domain is then decomposed to simulate nearshore processes and provide the boundary conditions necessary to run a standalone SWAN model. Here, the implicit and explicit representations of vegetation are finally assessed. Results show that treating vegetation simply as enhanced bottom roughness (implicitly) under-represents the complexity of wave-vegetation interaction and, consequently, underestimates wave energy dissipation (error > 30%). The explicit vegetation representation, however, shows good agreement with field data (error < 20%). |
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ISSN: | 2076-3263 2076-3263 |
DOI: | 10.3390/geosciences9010008 |