Spectral wave dissipation by submerged aquatic vegetation in a back‐barrier estuary

Abstract

Submerged aquatic vegetation is generally thought to attenuate waves, but this interaction remains poorly characterized in shallow-water field settings with locally generated wind waves. Better quantification of wave-vegetation interaction can provide insight to morphodynamic changes in a variety of environments and also is relevant to the planning of nature-based coastal protection measures. Toward that end, an instrumented transect was deployed across a Zostera marina (common eelgrass) meadow in Chincoteague Bay, Maryland/Virginia, U.S.A., to characterize wind-wave transformation within the vegetated region. Field observations revealed wave-height reduction, wave-period transformation, and wave-energy dissipation with distance into the meadow, and the data informed and calibrated a spectral wave model of the study area. The field observations and model results agreed well when local wind forcing and vegetation-induced drag were included in the model, either explicitly as rigid vegetation elements or implicitly as large bed-roughness values. Mean modeled parameters were similar for both the explicit and implicit approaches, but the spectral performance of the explicit approach was poor compared to the implicit approach. The explicit approach over-predicted low-frequency energy within the meadow because the vegetation scheme determines dissipation using mean wavenumber and frequency, in contrast to the bed-friction formulations, which dissipate energy in a variable fashion across frequency bands. Regardless of the vegetation scheme used, vegetation was the most important component of wave dissipation within much of the study area. These results help to quantify the influence of submerged aquatic vegetation on wave dynamics in future model parameterizations, field efforts, and coastal-protection measures. In the aforementioned studies, local (re-) generation of waves was not considered. However, in limited-fetch environments like back-barrier lagoons, local winds are critical to the wave field, the resulting bed stress, sediment transport, and ultimately the character of the local geomorphology. In addition to measuring bulk quantities like significant wave height, wave period, and wave dissipation in vegetated regions, a full quantification of the spectral wave field is crucial to understanding the wave dynamics and potential feedbacks between seagrass, sediment transport, and light availability.Wave-vegetation interaction models generally characterize vegetation as rigid cylinders with a constant drag Limnol. Oceanogr. 62, 2017, 736-753

Comparison of Implicit and Explicit Vegetation Representations in SWAN Hindcasting Wave Dissipation by Coastal Wetlands in Chesapeake Bay

“…For the implicit representation, the Manning "n" values of 0.055, 0.080 and 0.150 performed the same. This is likely caused by the limit placed on the friction factor formulation applied in SWAN, as discussed in [20]; overcoming this limitation would require an adjustment of the source code in order to change the friction factor formulation to that of [47]. However, it is important to note that the formulation used in [20] was implemented for fully submerged sea grass which behaves differently to the emergent vegetation observed at the Eastern Shore Project site.…”

“…This is likely caused by the limit placed on the friction factor formulation applied in SWAN, as discussed in [20]; overcoming this limitation would require an adjustment of the source code in order to change the friction factor formulation to that of [47]. However, it is important to note that the formulation used in [20] was implemented for fully submerged sea grass which behaves differently to the emergent vegetation observed at the Eastern Shore Project site. An n value of 0.055 was ultimately chosen as the appropriate value for the implicit representation because it represents marsh vegetation, whereas the other two represent coastal shrubs (n = 0.080) and coastal forest (n = 0.150).…”

“…Smith et al [19] indicated the potential limitations of using n to represent wave dissipation by vegetation and supported its conclusions with laboratory data. Nowacki et al [20] conducted an assessment similar to Smith et al [19] on fully submerged sea grass, indicating the potential shortcomings of relating vegetation characteristics to friction length and bottom friction by relation. Such assessments-where the formulations and input parameters of the numerical model are evaluated-may identify areas of improvement and, accordingly, improve how we manage coastal hazards.…”

“…These findings have led to several assessments of the vegetation representations in the widely-used nearshore numerical models, such as SWAN [2,[18][19][20] and XBeach [21]. Smith et al [19] indicated the potential limitations of using n to represent wave dissipation by vegetation and supported its conclusions with laboratory data.…”

Mechanisms for the Asymmetric Motion of Submerged Aquatic Vegetation in Waves: A Consistent‐Mass Cable Model

“…A single vegetation blade likely has little influence on waves, however, numerous blades as a SAV meadow can significantly impact waves by generating turbulence (Abdolahpour et al, ; Tan et al, ; Tang et al, ; Zhang et al, ), reducing wave energy (Garzon et al, ; Henderson et al, ; Infantes et al, ; Nowacki et al, ; Paul et al, ), and inducing mean currents (Abdolahpour et al, ; Chen et al, ; Luhar & Nepf, ). The wave‐driven currents in a vegetation meadow are expected to enhance the asymmetry of blade motion (e.g., Figure 8 of Lei & Nepf, ).…”