On the wave attenuation properties of seagrass meadows: Fid-Bau Portal

On the wave attenuation properties of seagrass meadows

Vettori, Davide / Pezzutto, Paolo / Bouma, Tjeerd J. / Shahmohammadi, Amirarsalan / Manes, Costantino

Abstract The wave attenuation properties of seagrass meadows were investigated in a flume facility using dynamically-scaled models of seagrass exposed to regular long crested waves. Experiments were conducted for 66 wave conditions and with four plant densities; waves were measured with eight resistance wave gauges. The data collected represent the most-comprehensive dataset of its kind. They reveal that the wave attenuation coefficient $K_{D}$ of a seagrass meadow reaches a uniform value after a distance of approximately 1.5–3 times the water depth from the meadow start and that both $K_{D}$ and the drag coefficient $C_{d}$ depend significantly on the plant density. An improved model of $K_{D}$ based on the work of Lei and Nepf (2019) is proposed that takes into account the effects of the solid volume fraction of the plant model through a correction on $C_{d}$ and that of plant density via an effective vegetation frontal area $a_{v - e}$ . The effective vegetation frontal area is described as a power law of the roughness density $λ_{f}$ . The model, which was validated with the data of $K_{D}$ obtained from the laboratory experiments described herein, displays an excellent agreement with data from the literature. It can predict $K_{D}$ accurately also for cases whereby the maximum wave orbital excursion is comparable with the blade length, despite this condition violates the model’s assumptions. This work provides a comprehensive dataset and a new model that can be used to improve the prediction of wave attenuation of seagrass meadows.

Highlights • Wave attenuation of seagrass meadows was measured with laboratory experiments. • An improved model is proposed to predict the wave attenuation coefficient $K_{D}$ . • An effective frontal area is introduced to include the effect of plant density. • The model works well in a broad range of conditions.