Development of a coupled wave-flow-vegetation interaction model
Development of a coupled wave-flow-vegetation interaction model
Date
2016-12-15
Authors
Beudin, Alexis
Kalra, Tarandeep S.
Ganju, Neil K.
Warner, John C.
Kalra, Tarandeep S.
Ganju, Neil K.
Warner, John C.
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DOI
10.1016/j.cageo.2016.12.010
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Keywords
Flexible aquatic vegetation
Coastal hydrodynamics
Numerical modeling
Coastal hydrodynamics
Numerical modeling
Abstract
Emergent and submerged vegetation can significantly affect coastal hydrodynamics. However, most deterministic numerical models do not take into account their influence on currents, waves, and turbulence. In this paper, we describe the implementation of a wave-flow-vegetation module into a Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system that includes a flow model (ROMS) and a wave model (SWAN), and illustrate various interacting processes using an idealized shallow basin application. The flow model has been modified to include plant posture-dependent three-dimensional drag, in-canopy wave-induced streaming, and production of turbulent kinetic energy and enstrophy to parameterize vertical mixing. The coupling framework has been updated to exchange vegetation-related variables between the flow model and the wave model to account for wave energy dissipation due to vegetation. This study i) demonstrates the validity of the plant posture-dependent drag parameterization against field measurements, ii) shows that the model is capable of reproducing the mean and turbulent flow field in the presence of vegetation as compared to various laboratory experiments, iii) provides insight into the flow-vegetation interaction through an analysis of the terms in the momentum balance, iv) describes the influence of a submerged vegetation patch on tidal currents and waves separately and combined, and v) proposes future directions for research and development.
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© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Computers & Geosciences 100 (2017): 76–86, doi:10.1016/j.cageo.2016.12.010.
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Computers & Geosciences 100 (2017): 76–86