Circulation and Stream Plume Modeling in Conesus Lake

A three-dimensional hydrodynamic model that includes the effect of drag from macrophytes was applied to Conesus Lake to study the seasonal circulation and thermal structure during spring and early summer. Local weather conditions and stream flow data were used to drive the model. The drag coefficient for macrophytes was calculated as a function of leaf density. In general, the model results show good agreements with the observations, including vertical temperature profiles measured at two locations and average surface temperature derived from calibrated thermal imagery for large-scale simulations of the entire lake. Additional high-resolution simulations were carried out to understand water circulation and transport of sediment and model-generated tracer during hydrometeorological events at stream mouths for two experimental sites. The model results show that the plume development at stream mouths during storm events in Conesus Lake are site-dependent and may either be current- or wind-driven. The results also show a significant effect from the presence of macrophytes on sediment deposition near stream mouths.

[1]  J. Makarewicz,et al.  The impact of stream nutrient loading on macrophytes and metaphyton in Conesus Lake, USA , 2006 .

[2]  R. Simon,et al.  Wildlife identified as major source of Escherichia coli in agriculturally dominated watersheds by BOX A1R-derived genetic fingerprints. , 2007, Journal of environmental management.

[3]  D. Timothy Gerber,et al.  Comparison of leaf morphology among submersed species of Myriophyllum (Haloragaceae) from different habitats and geographical distributions , 1994 .

[4]  Heinz G. Stefan,et al.  Dynamics of vertical mixing in a shallow lake with submersed macrophytes , 2005 .

[5]  S. Effler,et al.  Inorganic tripton in the Finger Lakes of New York: importance to optical characteristics , 2005, Hydrobiologia.

[6]  A. Garrett.  Drainage Flow Prediction with a One-Dimensional Model Including Canopy, Soil and Radiation Parameterizations. , 1983 .

[7]  Enrique R. Vivoni,et al.  Flow structure in depth-limited, vegetated flow , 2000 .

[8]  P. Bates,et al.  3D numerical modelling of open-channel flow with submerged vegetation , 2001 .

[9]  A. J. Garrett,et al.  Application of Multispectral Imagery to Assessment of a Hydrodynamic Simulation of an Effluent Stream Entering the Clinch River , 2000 .

[10]  Alfred J. Garrett.  Analyses of MTI imagery of power plant thermal discharge , 2002, SPIE Optics + Photonics.

[11]  Julia A. Barsi,et al.  Calibration of Landsat thermal data and application to water resource studies , 2001 .

[12]  J. Makarewicz,et al.  Elevated Nutrient Levels from Agriculturally Dominated Watersheds Stimulate Metaphyton Growth , 2007 .

[13]  J. Makarewicz,et al.  Update of Soil and Nutrient Loss from Subwatersheds of Conesus Lake - 2001 , 2002 .

[14]  D. Beletsky,et al.  Modeling circulation and thermal structure in Lake Michigan: Annual cycle and interannual variability , 2001 .

[15]  D. W. Hayes,et al.  Cooling Lake Simulations Compared to Thermal Imagery and Dye Tracers , 1997 .

[16]  Tetsuji Yamada,et al.  Simulations of Nocturnal Drainage Flows by a q2l Turbulence Closure Model , 1983 .