Salt marshes are dynamic biogeomorphic systems that respond to external physical factors, including tides, sediment transport, and waves, as well as internal processes such as autochthonous soil formation. Predicting the fate of marshes requires a modeling framework that accounts for these processes in a coupled fashion. In this study, we implement two new marsh dynamic processes in the 3-D COAWST (coupled-ocean-atmosphere-wave sediment transport) model. The processes added are the erosion of the marsh edge scarp caused by lateral wave thrust from surface waves and vertical accretion driven by biomass production on the marsh platform. The sediment released from the marsh during edge erosion causes a change in bathymetry, thereby modifying the wave-energy reaching the marsh edge. Marsh vertical accretion due to biomass production is considered for a single vegetation species and is determined by the hydroperiod parameters (tidal datums) and the elevation of the marsh cells. Tidal datums are stored at user-defined intervals as a hindcast (on the order of days) and used to update the vertical growth formulation. Idealized domains are utilized to verify the lateral wave thrust formulation and show the dynamics of lateral wave erosion leading to horizontal retreat of marsh edge. The simulations of Reedy and Dinner Creeks within the Barnegat Bay estuary system demonstrate the model capability to account for both lateral wave erosion and vertical accretion due to biomass production in a realistic marsh complex. The simulations show that vertical accretion is dominated by organic deposition in the marsh interior, whereas deposition of mineral estuarine sediments occurs predominantly along the channel edges. The ability of the model to capture the fate of the sediment can be extended to model to simulate the impacts of future storms and relative sea-level rise (RSLR) scenarios on salt-marsh ecomorphodynamics.

The numerical simulation of estuarine dynamics requires accurate prediction for the transport of tracers, such as temperature and salinity. During the simulation of these processes, all the numerical models introduce two kinds of tracer mixing: (1) by parameterizing the tracer eddy diffusivity through turbulence models leading to a source of physical mixing and (2) discretization of the tracer advection term that leads to numerical mixing. Physical and numerical mixing both vary with the choice of horizontal advection schemes, grid resolution, and time step. By simulating four idealized cases, this study compares the physical and numerical mixing for three different tracer advection schemes. Idealized domains only involving physical and numerical mixing are used to verify the implementation of mixing terms by equating them to total tracer variance. Among the three horizontal advection schemes, the scheme that causes the least numerical mixing while maintaining a sharp front also results in larger physical mixing. Instantaneous spatial comparison of mixing components shows that physical mixing is dominant in regions of large vertical gradients, while numerical mixing dominates at sharp fronts that contain large horizontal tracer gradients. In the case of estuaries, numerical mixing might locally dominate over physical mixing; however, the amount of volume integrated numerical mixing through the domain compared to integrated physical mixing remains relatively small for this particular modeling system.

Coastal hydrodynamics can be greatly affected by the presence of submerged aquatic vegetation. The effect of vegetation has been incorporated into the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system. The vegetation implementation includes the plant-induced three-dimensional drag, in-canopy wave-induced streaming, and the production of turbulent kinetic energy by the presence of vegetation. In this study, we evaluate the sensitivity of the flow and wave dynamics to vegetation parameters using Sobol' indices and a least squares polynomial approach referred to as the Effective Quadratures method. This method reduces the number of simulations needed for evaluating Sobol' indices and provides a robust, practical, and efficient approach for the parameter sensitivity analysis. The evaluation of Sobol' indices shows that kinetic energy, turbulent kinetic energy, and water level changes are affected by plant stem density, height, and, to a lesser degree, diameter. Wave dissipation is mostly dependent on the variation in plant stem density. Performing sensitivity analyses for the vegetation module in COAWST provides guidance to optimize efforts and reduce exploration of parameter space for future observational and modeling work.

The salinity structure in an estuary is controlled by time‐dependent mixing processes. However, the locations and temporal variability of where significant mixing occurs is not well‐understood. Here we utilize a tracer variance approach to demonstrate the spatial and temporal structure of salinity mixing in the Hudson River Estuary. We run a 4‐month hydrodynamic simulation of the tides, currents, and salinity that captures the spring‐neap tidal variability as well as wind‐driven and freshwater flow events. On a spring‐neap time scale, salinity variance dissipation (mixing) occurs predominantly during the transition from neap to spring tides. On a tidal time scale, 60% of the salinity variance dissipation occurs during ebb tides and 40% during flood tides. Spatially, mixing during ebbs occurs primarily where lateral bottom salinity fronts intersect the bed at the transition from the main channel to adjacent shoals. During ebbs, these lateral fronts form seaward of constrictions located at multiple locations along the estuary. During floods, mixing is generated by a shear layer elevated in the water column at the top of the mixed bottom boundary layer, where variations in the along channel density gradients locally enhance the baroclinic pressure gradient leading to stronger vertical shear and more mixing. For both ebb and flood, the mixing occurs at the location of overlap of strong vertical stratification and eddy diffusivity, not at the maximum of either of those quantities. This understanding lends a new insight to the spatial and time dependence of the estuarine salinity structure.

Salt marshes are valuable ecosystems that must trap sediments and accrete in order to counteract the deleterious effect of sea level rise. Previous studies have shown that the capacity of marshes to build up vertically depends on both autogenous and exogenous processes including ecogeomorphic feedbacks and sediment supply from in‐land and coastal ocean. There have been numerous efforts to quantify the role played by the sediments coming from marsh edge erosion on the resistance of salt marshes to sea level rise. However, the majority of existing studies investigating the interplay between lateral and vertical dynamics use simplified modeling approaches, and they do not consider that marsh retreat can affect the regional‐scale hydrodynamics and sediment retention in back‐barrier basins. In this study, we evaluated the fate of the sediments originating from marsh lateral loss by using high‐resolution numerical model simulations of Jamaica Bay, a small lagoonal estuary located in New York City. Our findings show that up to 42% of the sediment released during marsh edge erosion deposits on the shallow areas of the basin and over the vegetated marsh platforms, contributing positively to the sediment budget of the remaining salt marshes. Furthermore, we demonstrate that with the present‐day sediment supply from the ocean, the system cannot keep pace with sea level rise even accounting for the sediment liberated in the bay through marsh degradation. Our study highlights the relevance of multiple sediment sources for the maintenance of the marsh complex.

The shoaling transformation from generally linear deep-water waves to asymmetric shallow-water waves modifies wave shapes and causes near-bed orbital velocities to become asymmetrical, contributing to net sediment transport. In this work, we used two methods to estimate the asymmetric wave shape from data at three sites. The first method converted wave measurements made at the surface to idealized near-bottom wave-orbital velocities using a set of empirical equations: the “parameterized” waveforms. The second method involved direct measurements of velocities and pressure made near the seabed: the “direct” waveforms. Estimates from the two methods were well correlated at all three sites (Pearson’s correlation coefficient greater than 0.85). Both methods were used to drive bedload-transport calculations that accounted for asymmetric waves, and the results were compared with a traditional excess-stress formulation and field estimates of bedload transport derived from ripple migration rates based on sonar imagery. The cumulative bedload transport from the parameterized waveform was 25% greater than the direct waveform, mainly because the parameterized waveform did not account for negative skewness. Calculated transport rates were comparable to rates estimated from ripple migration except during the largest event, when calculated rates were as much as 100 times greater, which occurred during high period waves.