Oscar Meza Tovar / Earth & Environmental Sciences / Faculty Mentor: Arne Winguth
Temporal variability of density and dissolved oxygen (DO) in subtropical reservoirs are complex since they depend on momentum and buoyancy forcing and inflow into the reservoir. They are of importance for ecosystems, recreation, water quality, and water resource management. In addition, heat sources from the cooling of power plants may affect the density and DO. In this study, we combine weekly meteorological, temperature, and DO data collection on the lake with a one-dimensional (1-D) heat diffusion model to simulate vertical density gradients in Lake Arlington to test the hypothesis that complex 1-D models may be sufficient to explain the seasonal variability in reservoirs. The 1-D heat-diffusion model will be improved in the first step by considering the depth-dependent eddy diffusivity coefficient that depends on both the wind speed and the vertical density gradient. In the second step, a solar heating term will be added to the diffusion equation, and in the third step, this equation will expand by a heating term induced by the powerplant. Finally, a vertical convective term will be introduced to consider buoyancy-induced cooling by, e.g., a frontal system. Preliminary findings reveal distinct thermocline and oxycline patterns due to surface heating in early Fall. With a decline in solar radiation and convective cooling by frontal systems, the reservoir is more mixed. In the future steps, we assimilate a portion of the observations in the reservoir model and compare the outcome with independent observation. Thus, this study provides a predictive tool for reservoir management by considering both natural and anthropogenic factors.
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