Search

Both submerged aquatic vegetation and salt marsh are important coastal ecosystems known for their effectiveness in sediment trapping and carbon burial. However, their proximity can lead to competition for limited sediment resources, potentially compromising their capacity to facilitate sufficient sediment deposition to withstand sea-level rise. Here we applied the Delft3D flow and sediment transport model in a shallow coastal bay to assess how seasonal variations in seagrass density and storms modulate sediment retention and connectivity between subtidal flats and intertidal marsh. Results show that submerged seagrass meadows acted as temporary storage for fine sediment and altered the timing of sediment transport to an adjacent marsh through seasonal growth cycles. When seagrass occupied subtidal flats, sediment flux to the marsh was controlled by seasonal seagrass density variations, with peak fluxes during winter senescence. In contrast, wave-induced sediment resuspension on the flats was the major contributor for marsh sediment input in the simulation with no seagrass, with peak storm-driven fluxes in summer/autumn. Overall, seagrass meadows significantly increased annual sediment accumulation on the vegetated subtidal flats by tenfold, while reducing annual marsh sediment flux and edge erosion by 20%. Seagrass meadows and marsh were both able to maintain a sediment deposition rate comparable to the rapid sea-level rise at the study site despite the absence of terrestrial sediment sources. Our findings highlight the strong seasonal control subtidal aquatic vegetation has in the vertical and horizontal dynamics of tidal flat-marsh systems and provide insights that can inform wetland restoration and management strategies in similar systems. [ABSTRACT FROM AUTHOR]

Seagrass meadows are important carbon sinks in the global coastal carbon cycle yet are also among the most rapidly declining marine habitats. Their ability to sequester carbon depends on flow–sediment–vegetation interactions that facilitate net deposition, as well as high rates of primary production. However, the effects of seasonal and episodic variations in seagrass density on net sediment and carbon accumulation have not been well quantified. Understanding these dynamics provides insight into how carbon accumulation in seagrass meadows responds to disturbance events and climate change. Here, we apply a spatially resolved sediment transport model that includes coupling of seagrass effects on flow, waves, and sediment resuspension in a seagrass meadow to quantify seasonal rates of sediment and carbon accumulation in the meadow. Our results show that organic carbon accumulation rates were largely determined by sediment accumulation and that they both changed non‐linearly as a function of seagrass shoot density. While seagrass meadows effectively trapped sediment at meadow edges during spring–summer growth seasons, during winter senescence low‐density meadows (< 160 shoots m−2) were erosional with rates sensitive to density. Small variations in winter densities resulted in large changes in annual sediment and carbon accumulation in the meadow; meadow‐scale (hundreds of square meters) summer seagrass dieback due to marine heatwaves can result in annual erosion and carbon loss. Our findings highlight the strong temporal and spatial variability in sediment accumulation within seagrass meadows and the implications for annual sediment carbon burial rates and the resilience of seagrass carbon stocks under future climate change. [ABSTRACT FROM AUTHOR]

Storm surge has the potential to significantly increase suspended sediment flux to microtidal marshes. However, the overall effects of storm surge on microtidal marsh deposition have not been well quantified, with most modeling studies focusing on regular (astronomical) tidal flooding. Here we applied the Delft3D model to a microtidal bay‐marsh complex in Hog Bay, Virginia to quantify the contributions of storm surge to marsh deposition. We validated the model using spatially distributed hydrodynamic and suspended sediment data collected from the site and ran model simulations under different storm surge conditions with/without storm‐driven water level changes. Our results show that episodic storm surge events occurred 5% of the time at our study site, but contributed 40% of marsh deposition during 2009–2020. Our simulations illustrate that while wind‐driven waves control sediment resuspension on tidal flats, marsh deposition during storms was largely determined by tidal inundation associated with storm‐driven water levels. A moderate storm surge event can double sediment flux to most marshes around the bay and deliver more sediment to the marsh interior compared to simulations that include wind waves but not storm surge variations in water levels. Simulations of bay and marsh response to different storm surge events with varying magnitude of storm surge intensity reveal that total marsh deposition around the bay increased linearly with storm surge intensity, suggesting that future changes to storm magnitude and/or frequency would have significant implications for sediment supply to marshes at our study site. Plain Language Summary: Storm surge is a rise of water level beyond normal tidal levels caused by a storm. It can result in longer and deeper inundation on the marsh platform and potentially provide more sediment for microtidal marshes (tidal range <2 m) to gain elevation at a rate comparable to sea level rise. However, the overall importance of storm surge to sediment deposition on these marshes is not well understood. Here we used a well‐tested coastal model in a shallow microtidal bay fringed by intertidal salt marshes to run model simulations for different storm surge events with varying magnitude of storm surge intensity to determine the contributions of storm surge to marsh deposition. Our simulation results show that infrequently occurring storm surge events contributed ∼40% of marsh deposition at our study site and that total mass of marsh deposition around the bay increased linearly with the magnitude of storm surge events. Our findings have significant implications for predicting marsh change, especially if we experience a stormier future climate. Modeling studies that do not resolve storm surge effects on marsh deposition will likely underestimate rates of marsh elevation change. Key Points: A numerical model was used to quantify the contributions of storm surge on marsh deposition in a microtidal bay‐marsh complexStorm surge events occurred 5% of the time, but contributed 40% of marsh deposition during 2009–2020Marshes will likely be supplied with more sediment during storms if storm magnitudes and/or frequencies increase in the future [ABSTRACT FROM AUTHOR]

Seagrass growth and senescence exert a strong influence on flow structure and sediment transport processes in coastal environments. However, most previous studies of seasonal seagrass effects either focused on small-scale field measurements or did not fully resolve the synergistic effects of flow-wave-vegetation-sediment interaction at a meadow scale. In this study, we applied a coupled Delft3DFLOW and SWAN model that included effects of seagrass on flow, waves, and sediment resuspension in a shallow coastal bay to quantify seasonal seagrass impacts on bay dynamics. The model was extensively validated using seasonal field hydrodynamic and suspended sediment data within a seagrass meadow and a nearby unvegetated site. Our results show that seagrass meadows significantly attenuated flow (60%) and waves (20%) and reduced suspended sediment concentration (85%) during summer when its density reached a maximum. Probability density distributions of combined wave-current bed shear stress within the seagrass meadow indicate that significant reductions in sediment resuspension during summer were mainly caused by flow retardation rather than wave attenuation. Although low-density seagrass in winter resulted in much smaller reductions in flow and waves compared with summer meadows, small changes in winter seagrass density resulted in large differences in the magnitude of attenuation of flow and shear stress. Similarly, while high seagrass densities effectively trapped sediment during summer, small changes in winter density resulted in strong changes in net sediment flux into/out of the meadow. At our study site, low seagrass densities provided significant reductions in wintertime sediment loss compared to losses associated with completely unvegetated conditions. Plain Language Summary Seagrasses are valuable ecosystems that inhabit shallow coastal waters. In summertime, their dense canopies can significantly slow tidal currents and lower wave energy, thereby reducing sediment resuspension and improving light environments for seagrass growth. This strong seagrass control on bay dynamics diminishes during winter, however, when seagrass density is low. In order to better understand seasonal seagrass impacts on shallow coastal environments, we ran a coastal model that includes effects of seagrass on flow, waves, and sediment resuspension under both summer and winter conditions in a shallow coastal bay. We found that dense seagrass during summer can considerably lower the energy levels of the bay and effectively trap fine particles. The strong reductions in sediment resuspension are mainly due to flow reduction caused by seagrass rather than wave attenuation. During winter, although low densities of seagrass had relatively limited effects on flow and waves, vegetation was still very important to protect the seabed from erosion. Our model predicts a small change of seagrass density in winter could result in strong changes in sediment input/output of the meadows. This effect had not been well characterized before, and it is important to understand because it has a significant impact on seagrass ecosystems. [ABSTRACT FROM AUTHOR]

Macroalgae structure coastal ecosystems affecting metabolism, nutrient dynamics, and food webs. Spatially explicit prediction of macroalgal abundance is critical for understanding coastal ecosystems and trajectories. However, models of macroalgal distribution tend to be mechanistic and generalize poorly, or biogeographic and too coarse to use over spatial scales most appropriate to ecosystem research and management (1–100 km2). Our objective was to develop spatial distribution models for benthic macroalgae in soft‐sediment environments. We compared macroalgal abundance quantified as percent cover, with environmental drivers on 1 ha intertidal flats in a > 900 km2 lagoon system along the Atlantic Coast of Virginia, U.S.A. Physical drivers of macroalgae (e.g., depth‐mediated light availability, exposure to waves) are related to bed morphology. We developed a novel topographic index (τ) to determine whether bed morphology predicts macroalgal abundance. This topographic index described variation in elevation occurring over spatial scales relevant to macroalgae, ranging from smooth to hummocky (τ = 0.01–1.07). Models tested τ along with mean elevation, fetch, and water residence time as predictors of macroalgal abundance. τ, and the interaction with water residence time, were most strongly related to macroalgal abundance. Hummocky flats accumulated less macroalgae than smoother flats, but exceptions occurred with short residence times. Model error (root mean square error) was low, varying between 8% and 18% across models. These models, based on readily measured physical features, are a useful approach for assessing macroalgal abundance in relation to shoreline hardening, species invasions, sea‐level rise, and changing sedimentation affecting coastal ecosystems. [ABSTRACT FROM AUTHOR]

Abstract: Coastal bays and, specifically, back‐barrier tidal basins host productive ecosystems, coastal communities, and critical infrastructure. As sea level continues to rise and tropical cyclones increase in intensity, these coastal systems are increasingly at risk. Developing a sediment budget is imperative to understanding how storm events affect the system's resilience, where net import of sediment indicates growth and resilience against sea level rise, and net export of sediment indicates deterioration. Using high‐resolution numerical simulations, we show that intense storms import sediment into a system of bays in Virginia, USA. Duration and magnitude of storm surge are among the most important factors in sediment import, suggesting that intense storms increase the stability of tidal bays by providing the sediment necessary to counteract sea level rise. Since climate models project that tropical cyclones will increase in intensity in coming decades, our results have significant implications for the resilience of tidal bays and the future of coastal communities worldwide. [ABSTRACT FROM AUTHOR]

Sediment resuspension and related increases in turbidity in shallow coastal bays are strongly controlled by local bed properties. However, knowledge of bed properties in coastal bays is typically sparse at best. In this study, we developed a method to estimate the spatial distribution of bed properties in shallow coastal bays using a combination of bed sediment measurements and residence time calculations that requires neither extensive dedicated modeling nor extensive sampling. We found a strong relationship between water residence times derived from a coastal hydrodynamic model and observed bed grain size fractions in a system of coastal bays and used that relationship to transform maps of residence time to maps of grain size fractions throughout the bays. Because grain-size fractions are related to other bed properties such as organic fraction, permeability and cohesion, these maps provide valuable information for habitat studies as well as morphodynamic modeling. We used our maps of grain size distributions to initialize a 2-month-long model simulation of currents, waves and suspended sediment forced with measured wind and tides. Spatial variations in suspended sediment concentration (SSC) reflected spatial gradients in sand and mud abundance in the bed. Lower SSC in sandier regions of the bays, near barrier islands and inlets, resulted in higher benthic light availability but lower sediment supply for deposition on back-barrier marshes. Higher SSC in more landward, muddier regions resulted in greater light attenuation and sediment availability for deposition on mainland fringing marshes. The proposed methodology facilitates quantification of these bed-dependent spatial variations in SSC. [ABSTRACT FROM AUTHOR]

A variety of surface roughness characterizations have emerged from nineteenth and twentieth century studies of channel hydraulics. When the water depth h is much larger than the characteristic roughness height k s, roughness formulations such as Manning's n and the friction factor f can be explicitly related to the momentum roughness height z o in the log-law formulation for turbulent boundary layers, thereby unifying roughness definitions for a given surface. However, when h is comparable to (or even smaller than) k s, the log-law need not be valid. Using a newly proposed mixing layer analogy for the inflectional velocity profile within and just above the roughness layer, a model for the flow resistance in shallow flows is developed. The key model parameter is the characteristic length scale describing the depth of the Kelvin-Helmholtz wave instability. It is shown that the new theory, originally developed for canopy turbulence, recovers much of the earlier roughness results for flume experiments and shallow gravel streams. This study is the first to provide such a unifying framework between canopy atmospheric turbulence and shallow gravel stream roughness characterization. The broader implication of this study is to support the merger of a wealth of surface roughness characterizations independently developed in nineteenth and twentieth century hydraulics and atmospheric sciences and to establish a connection between roughness formulations across traditionally distinct boundary layer types. [ABSTRACT FROM AUTHOR]

In drainage basin evolution models the implementation of sediment transport and sediment balance is constrained by numerical instabilities. In order to overcome these difficulties an implicit finite difference method is proposed. The method simultaneously adjusts the elevation at each node of the numerical grid, is unconditionally stable, and significantly reduces the computational time. The performance of the method is tested and briefly discussed with a numerical example. [ABSTRACT FROM AUTHOR]

A model for the velocity field over a poorly sorted bed is derived herein and applied to flow in steep streams with coarse gravel beds. In such streams, large clasts often are comparable in size to stream depth and act as obstacles to the flow. The effect of these obstacles on a flow is estimated by partitioning total stress, proportional to the depth-slope product, into a purely fluid component and a form-drag component associated with flow around the obstacles. An eddy viscosity closure is used, with a length scale dependent on both distance from the boundary and wake dimension. Resulting velocity profiles agree well with profiles measured by Marchand et al. (1984) in nine mountain streams in Colorado. Model runs for a range of conditions reveal that the velocity distribution depends primarily on D84 z and flow depth h; D84 z is the length of the vertically oriented axis of clasts at the 84th percentile of the grain size distribution. Calculated values of mean velocity, normalized by shear velocity, are well represented by a simple log linear relationship in terms of relative roughness D84/ h. [ABSTRACT FROM AUTHOR]

An expression for the critical shear stress noncohesive sediment is derived from the balance of forces on individual particles at the surface of a bed. The resulting equation, for a given grain size and density, depends on the near-bed drag force, lift force to drag force ratio, and particle angle of repose. Calculated values of the critical shear stress for uniformly sized sediment correspond closely to those determined from Shields' diagram. The initial motion problem for mixed grain sizes additionally depends on the relative protrusion of the grains into the flow and the particle angle of repose. The latter decreases when the diameter of a moving grain, D, is larger than the length scale of the bed roughness, ks ( D/ks > 1), and increases when D/ks < 1, producing a corresponding decrease or increase in critical shear stress. Using the Miller and Byrne experimental relationship between D/ks and particle angle of repose, which is consistent with Shields' definition of initial motion, we obtain results that are in good agreement with the available experimental critical shear stress data for heterogeneous beds. [ABSTRACT FROM AUTHOR]

We investigated the size and shape of the area on the sediment surface, the so-called footprint, that contributes to the flux in subaqueous eddy correlation measurements. Tracer tracking simulations were performed for a dissolved conservative tracer released from the sediment surface into a current-driven flow not affected by density stratifications and surface waves. Simulations revealed that the footprint length (l) can be calculated as l = -2.783 - 158.7h + 159.2h² - 120.8h log(z0) (all units in m) for eddy correlation measurements heights (h) between 0.05 and 0.3 m above the sediment surface and for sediment surface roughness parameter (z0) values between 7.04 x 10-6 and 0.01 m. The upstream distance (xmax) to the location that contributes the strongest flux signal can likewise be estimated as xmax = -0.09888 - 11.53h + 10.25h² - 6.650h log (z0). Because vertical turbulent mixing scales with mean current velocity, l and xmax are independent of current velocity. The footprint width (w) can be calculated as w = 6.531h. These expressions were developed for water depths (H) of H > 27h. In the depth interval 6.7h > H > 27h, l can be calculated by multiplying the length, as given above, by the factor 1 + 8.347exp(-0.2453 H/h), whereas xmax is independent of H. For H > 6.7h, the tracer transfer rate over the air-water interface controls the size and shape of the footprint. All expressions are valid for isotropic turbulence, but as a first-order estimate, the expressions for l and xmax also hold for anisotropic conditions. In contrast, w scales with sqrt(Ey/Ex), where Ey and Ez are the transverse and the vertical eddy diffusivity, respectively. Finally, we describe how site-specific values of z0 and levels of anisotropy in a turbulent near-bottom flow can be extracted directly from eddy correlation measurements [ABSTRACT FROM AUTHOR]