Scalar dispersion within a model canopy: Measurements and three-dimensional Lagrangian models
Modeling scalar transport within canopies remains a vexing research problem in eco-hydrology and eco-hydraulics. Canopy turbulence is inhomogeneous, non-Gaussian, and highly dissipative, thereby posing unique challenges to three-dimensional Lagrangian Dispersion Models (LDM). Standard LDM approaches usually satisfy the well-mixed condition and account for turbulence inhomogeneity but not for its non-Gaussian statistics and enhanced dissipation. While numerous studies evaluated the importance of the former (with mixed results), few studies to date considered the latter. In this paper we present new data and explore: (1) the skill of LDM in reproducing mean scalar concentration distributions within dense and rigid canopies for source releases near the canopy top and near the ground, and (2) the extent to which these estimates are sensitive to the formulation of the mean turbulent kinetic energy dissipation rate (∈) profile. Toward this end, Laser Induced Florescence (LIF) and Laser Doppler Anemometry (LDA) were used to measure scalar concentration and Eulerian flow statistics within a dense model canopy in a rectangular flume. It is shown that LDM concentration predictions are sensitive to how ∈ is estimated. Good agreement between measured and modelled mean concentration distributions were obtained when ∈ was estimated from the mean squared longitudinal velocity graients and isotropic turbulence principles. However, when ∈ was estimated from the widely used scaling arguments that employ a constant Lagrangian time scale (Tl) and a specified vertical velocity variance (σw2) profile, the predicted concentrations diverged significantly from the LIF measurements. Better agreement was obtained when a constant mixing length scale was used with the σw2 profile. © 2005 Elsevier Ltd. All rights reserved.
Poggi, D; Katul, G; Albertson, J
Volume / Issue
Start / End Page
International Standard Serial Number (ISSN)
Digital Object Identifier (DOI)