Investigations of grain size dependent sediment transport phenomena on multiple scales

Sediment transport processes in coastal and fluvial environments resulting from disturbances such as urbanization, mining, agriculture, military operations, and climatic change have significant impact on local, regional, and global environments. Primarily, these impacts include the erosion and deposition of sediment, channel network modification, reduction in downstream water quality, and the delivery of chemical contaminants. The scale and spatial distribution of these effects are largely attributable to the size distribution of the sediment grains that become eligible for transport. An improved understanding of advective and diffusive grain-size dependent sediment transport phenomena will lead to the development of more accurate predictive models and more effective control measures. To this end, three studies were performed that investigated grain-size dependent sediment transport on three different scales. Discrete particle computer simulations of sheet flow bedload transport on the scale of 0.1--100 millimeters were performed on a heterogeneous population of grains of various grain sizes. The relative transport rates and diffusivities of grains under both oscillatory and uniform, steady flow conditions were quantified. These findings suggest that boundary layer formalisms should describe surface roughness through a representative grain size that is functionally dependent on the applied flow parameters. On the scale of 1--10m, experiments were performed to quantify the hydrodynamics and sediment capture efficiency of various baffles installed in a sediment retention pond, a commonly used sedimentation control measure in watershed applications. Analysis indicates that an optimum sediment capture effectiveness may be achieved based on baffle permeability, pond geometry and flow rate. Finally, on the scale of 10--1,000m, a distributed, bivariate watershed terain evolution module was developed within GRASS GIS. Simulation results for variable grain sizes and for distributed rainfall infiltration and land cover matched observations. Although a unique set of governing equations applies to each scale, an improved physics-based understanding of small and medium scale behavior may yield more accurate parameterization of key variables used in large scale predictive models.