Application and validation of a three-dimensional hydrodynamic model of a macrotidal salt marsh

A three-dimensional hydrodynamic model is used to study the relative influence of salt marsh vegetation on flows in a macrotidal estuary using a system of three connected grids that resolve currents in tidal drainage channels incised in a marsh platform. The model incorporates the effects of vegetation on flow drag, parameterized by the stem height, diameter and plant density. Model predictions are compared to novel field observations of macrotidal water levels and tidal currents using pressure and acoustic current sensors over 6 tidal cycles at spring tide, collected in areas of different roughness corresponding to high marsh grass (Spartina patens), low marsh grass (Spartina alterniflora), and a muddy tidal channel bed. High resolution airborne Lidar and multibeam bathymetry data are used to define the bathymetry and spatially-variable vegetation maps in the multi-domain model. A detailed comparison between field observations and model results is presented, necessary for model validation in this macrotidal environment with large water level gradients and high sensitivity to model input parameter values. The model results indicate that the vegetation plays a major role in controlling flow speed and drainage patterns, especially over the macrotidal marsh platform. Differences in flow resistance between vegetated and un-vegetated areas result in faster flows over un-vegetated areas, with vegetated areas having flow directions locally perpendicular to channels as water levels exceed creek bank elevations and the marsh platform is flooded. Including the marsh grasses in the model causes stronger near-surface currents, significantly weaker near-bed currents, and concentrated flows in the channels resulting in strong vertical variation in the horizontal flow. The results indicate that including the effects of vegetation in a numerical model is crucial in simulating the hydrodynamic conditions over macrotidal salt marsh platforms and in channels. (C) 2016 Elsevier B.V. All rights reserved.