Vincent S. Neary

LES study of turbulent flows with submerged vegetation

Fully developed turbulent flows with a submerged vegetation are investigated using Large Eddy Simulation (LES), with a focus on understanding the role of the coherent structures on the momentum transfer across the water-plant interface. The LES model results compare reasonably well with laboratory measurements reported in the literature. As with Reynolds-Averaged Navier–Stokes models, LES models effectively simulate the effects of submerged vegetation on the mean flow field, but they also account for the anisotropy of the Reynolds stresses due to the vegetation layer, and resolve coherent structures observed in the instantaneous flow field. Comparisons with fully developed flows in unobstructed (non-vegetated) channels are made to show how the vegetation significantly changes the mean flow, Reynolds shear stress, turbulence intensities, turbulence event frequencies and the energy budget within and above the vegetation layer. LES provides direct visual evidence that coherent structures, namely spanwise vortices (rolls) and streamwise vortices (ribs), develop at the water-plant interface at the top of the vegetation due to the well-known Kelvin–Helmholtz instability

Effects of Vegetation on Turbulence, Sediment Transport, and Stream Morphology

AbstractVegetation as multiple stems in various configurations or an isolated stem profoundly alters turbulent flows. Past research has shown that these alterations influence sediment transport and stream morphology, but entail complex interactions and feedbacks between flow, vegetation, and sediment processes that involve many parameters. These interactions are examined here for a variety of macrophyte patterns and scales in riverine environments. Flow Reynolds number, canopy density, and submergence ratio are just a few of the key parameters that influence the spatial variability of the flow, momentum transfer, vortex shedding and dissipation, and instantaneous stresses that are known to affect sediment and morphological processes in rivers. Knowledge gaps, though, still remain. A taxonomy that classifies vegetated flows as dense, sparse, or isolated on the basis of threshold parameters like the ratio of stem diameter to stem spacing would be useful for comparing studies among researchers and predicting...

HYDROLOGIC MODELING AS A DEVELOPMENT TOOL FOR HGM FUNCTIONAL ASSESSMENT MODELS

The hydrogeomorphic (HGM) approach to wetland classification and functional assessment was developed to facilitate the rapid assessment of wetland functions and support implementation of the 404 regulatory program in the U.S. This paper describes development of a functional assessment model for the hydrologic regime function of depressional wetlands on the Tennessee Highland Rim. Model output is a functional capacity index that ranges from 0 to 1 and indicates the level of alteration to the wetland hydrologic regime relative to the unaltered condition. The model initially includes four variables, each corresponding to an alteration type common in the study area. One variable reflects alterations to wetland morphology that increase or decrease storage capacity. Two variables reflect alterations to the wetland watershed that result in increased surface runoff. The remaining variable reflects changes in evapotranspiration losses resulting from timber harvesting. Model variable sensitivity and interaction are examined by simulating 47 years of hydrology for a single depressional wetland site. Based on the simulation of hypothetical alterations representing the range of conditions anticipated in the reference domain, three important variable interactions were identified and one variable eliminated from consideration. Several forms of the aggregation equation relating a functional capacity index to three model variables were tested by comparison to index values based on an independent quantitative measure that was simulated with a hydrologic model. Initial model forms, similar in form to many existing models, are improved by the addition of interaction terms and modification of variable weighting. This study demonstrates the utility of hydrologic modeling as a development tool for HGM functional assessment models. Even when limited field measurements are available for a rigorous calibration and validation, hydrologie modeling provides valuable insight into model variable sensitivity and interaction.