Water quality modeling of Lake Diefenbaker

Lake Diefenbaker is one of the most important sources of water in the prairie province of Saskatchewan, Canada. It is a long (181.6 km) and narrow (maximum width 6 km) reservoir formed along the South Saskatchewan River by the construction of the Gardiner and Qu'Appelle River dams in the 1960s. The reservoir has a surface elevation of 556.87 meters above sea level (full supply level) with a maximum depth of 60 m, a surface area of approximately 393 km2 and a volume of 9.03 km3. The reservoir and dams are part of a multipurpose hydraulic project, which provides water for irrigation, drinking water, eco-services, hydropower generation, aquaculture and recreation as well as for flood mitigation. Surface water quality modeling is a useful tool to simulate and predict nutrient dynamics in lakes, reservoirs, and rivers, as well as the fate and transport of sediment and toxic contaminants in freshwater environments. In this study, water quality modeling of Lake Diefenbaker was carried out in order to help understand the mixing regimes and biological processes in the aquatic environment of this strategic reservoir. Based on the study's objectives, the physical and chemical characteristics of the lake and available data, the laterally-averaged two-dimensional model CE-QUAL-W2 hydrodynamic and water quality model was deemed the best model for Lake Diefenbaker. CE-QUAL-W2 was developed by the US Army Corp of Engineers to simulate the hydrodynamics, water quality, aquatic biology and aquatic chemistry in surface waters. On the one hand, this study provided information on temperature and hydrodynamic behaviors of Lake Diefenbaker as well as sediment and nutrient transport, nutrient uptake and algal activities. On the other hand, it addressed some key and limitations in the application of water quality models. Limitations addressed include studying snow cover effects on the ice surface in winter, applying variable algal stoichiometry, using combined local/global optimization for model calibration, and running the model on High-Performance Cluster (HPC) systems