Improved parameterization of seagrass blade dynamics and wave attenuation based on numerical and laboratory experiments

Seagrass blade dynamics were explored through numerical and laboratory experiments in order to improve parameterization of wave attenuation by submerged aquatic vegetation in the presence of a background current. In the numerical model, a single blade was modeled as a series of rigid plates attached...

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Bibliographic Details
Published in:Limnology and oceanography Vol. 59; no. 1; pp. 251 - 266
Main Authors: Zeller, Robert B., Weitzman, Joel S., Abbett, Morgan E., Zarama, Francisco J., Fringer, Oliver B., Koseff, Jeffrey R.
Format: Journal Article
Language:English
Published: Waco, TX John Wiley and Sons, Inc 01-01-2014
American Society of Limnology and Oceanography
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Summary:Seagrass blade dynamics were explored through numerical and laboratory experiments in order to improve parameterization of wave attenuation by submerged aquatic vegetation in the presence of a background current. In the numerical model, a single blade was modeled as a series of rigid plates attached by torsion springs. For the laboratory model, strips of low-density polyethylene were placed in a recirculating wave flume. A new form of the Keulegan–Carpenter number based on the horizontal excursion of the blade tip was found to be an excellent predictor of drag coefficient. An algebraic model for predicting wave attenuation was developed based on the following observations. During the portion of the wave period when the fluid velocities are highest, the blade motion is almost completely arrested and the vast majority of the turbulence production occurs during this time. Turbulence production when the blade is pronated is accurately predicted by the maximum fluid velocity over the wave period. The relative contribution to the total turbulence production over the wave period is determined by the relative strength of the waves and the current. Therefore, using a simple algebraic fit, the total depth-integrated, time-averaged turbulence production can be accurately predicted by two flow parameters: the maximum fluid velocity over the wave period, and a non-dimensional number that compares the wave and current velocities. By fitting the algebraic model to data from a particular site, it can be used to efficiently estimate wave attenuation and drag coefficient in seagrass exposed to waves with a background current.
ISSN:0024-3590
1939-5590
DOI:10.4319/lo.2014.59.1.0251