WIND-BASED MODELS FOR ESTIMATING THE DISSIPATION RATES OF TURBULENT ENERGY IN AQUATIC ENVIRONMENTS - EMPIRICAL COMPARISONS

The rate at which turbulent kinetic energy is dissipated influences gr owth, encounter probability, coagulation rates and vertical distributi on of plankton. In this study we quantified the effectiveness with whi ch boundary (wall) layer theory represents turbulent dissipation rates (epsilon, W m-3) measured within natural surface mixing layers. This model explained 58 % of the variance in 818 literature-derived estimat es of turbulent dissipation rates measured at 11 different geographic sites. The residual mean square error (RMSE) associated with the regre ssion of log10 observed dissipation rate vs log10 predicted dissipatio n rate showed that ca 68 % of surface layer dissipation rates observed in nature were within a factor +/- 5.2-fold of dissipation rates esti mated using boundary layer theory. Dissipation rates in more complex m ixing environments, where turbulence was known to be caused by additio nal hydrographic phenomena (free convection, breaking of waves in the upper 1.5 m of the water column, current shear, upwelling), exceeded t he boundary layer prediction by 1.5- to 26-fold depending on the mecha nism associated with turbulence-generation. We found no evidence that turbulence near the surface (0 to 5 or 0 to 10 m) during high winds (g reater-than-or-equal-to 7.5 or greater-than-or-equal-to 10 m s-1) was higher than the boundary layer prediction. When all data were combined into one data set, n = 1088), a multiple regression model having wind speed (W) and sampling depth (z) as inputs (log epsilon = 2.688 log W - 1.322 log z - 4.812) explained 54 % of the variance in surface laye r turbulent dissipation rates (RMSE = +/- 5.5-fold). The potential for developing more precise empirical models of mixing layer turbulent di ssipation rates is high and can be achieved by reporting wind conditio ns prior to, and during, turbulence measurements more thoroughly, and by collecting replicate turbulence profiles. The existing theoretical and empirical models are, however, adequate for many biological applic ations such as estimating the nature and magnitude of interactions amo ng, and distributions of, many plankton taxa as a result of wind forci ng.