ABSTRACT One of the most prominent sources of error and uncertainty in water quality modelling results is the input data. In this study, data from three meteorological databases were used to test the performance of a water temperature model of Lake Diefenbaker: the data from Environment and Climate Change Canada (ECCC) had long-term quality control history (>20 years); the data from the AccuWeather had short-term quality control history (<10 years), and the data from the MeteoBlue database were modelled values. The CE-QUAL-W2 hydrodynamic and water quality model was used for this study. The model was calibrated by adjusting model coefficients controlling the amounts of measured solar radiation and wind that reach the surface of the water. The sensitivity results showed very similar performances, with slightly better performances (root mean square root difference of ± 0.1) with the ECCC data followed by the MeteoBlue data and thereafter by the AccuWeather data.

ABSTRACT One of the most prominent sources of error and uncertainty in water quality modelling results is the input data. In this study, data from three meteorological databases were used to test the performance of a water temperature model of Lake Diefenbaker: the data from Environment and Climate Change Canada (ECCC) had long-term quality control history (>20 years); the data from the AccuWeather had short-term quality control history (<10 years), and the data from the MeteoBlue database were modelled values. The CE-QUAL-W2 hydrodynamic and water quality model was used for this study. The model was calibrated by adjusting model coefficients controlling the amounts of measured solar radiation and wind that reach the surface of the water. The sensitivity results showed very similar performances, with slightly better performances (root mean square root difference of ± 0.1) with the ECCC data followed by the MeteoBlue data and thereafter by the AccuWeather data.

Climate mediated warming water temperature, drought and extreme flooding are projected to shift the phenology of nutrients in receiving lakes and reservoirs further intensifying eutrophication and algal blooms, especially in temperate reservoirs. An emerging issue in reservoir management is the prediction of climate change impacts, a necessity for sound decision making and sustainable management. Lake Diefenbaker is a large multipurpose reservoir in the Canadian Prairies. In this study, the impact of climate change on nutrient speciation in Lake Diefenbaker is examined using loosely linked SpAtially Referenced Regression On Watershed attributes (SPARROW) and CE-QUAL-W2 models. Two climate mediated scenarios, RCP 8.5 representing the most extreme climate change, and climate induced streamflow were modelled. Nutrient levels are anticipated to double under the climate change and streamflow scenarios. Winter and spring were identified as hot moments for nitrogen pollution with a plausible saturation of nitrous oxides in the future. Of concern is a plausible recycling of nitrate through dissimilatory nitrate reduction to ammonium. Summer and fall on the other hand represent the period for phosphorus enrichment and internal loading with a probable succession of cyanobacteria in the summer. • Nutrient cycling in a large reservoir is investigated under two climate mediated scenarios. • Two loosely coupled models are forced with projected climate and streamflow changes. • Nitrogen pollution is projected to worsen during winter and spring during the 2040 decade. • Reservoir internal loading is anticipated to accelerate during the intermediate decade.

Dam operations are known to have significant impacts on reservoir hydrodynamics and solute transport processes. The Gardiner Dam, one of the structures that forms the Lake Diefenbaker reservoir located in the Canadian Prairies, is managed for hydropower generation and agricultural irrigation and is known to have widely altering temperature regimes and nutrient circulations. This study applies the hydrodynamic and nutrient CE-QUAL-W2 model to explore how various withdrawal depths (5, 15, 25, 35, 45, and 55 m) influence the concentrations and distribution of nutrients, temperature, and dissolved oxygen (DO) within the Lake Diefenbaker reservoir. As expected, the highest dissolved nutrient (phosphate, PO43--P and nitrate, NO3--N ) concentrations were associated with hypoxic depth horizons in both studied years. During summer high flow period spillway operations impact the distribution of nutrients, water temperatures, and DO as increased epilimnion flow velocities route the incoming water through the surface of the reservoir and reduce mixing and surface warming. This reduces reservoir concentrations but can lead to increased outflow nitrogen (N) and phosphorus (P) concentrations. Lower withdrawal elevations pull warmer surface water deeper within the reservoir and decrease reservoir DO during summer stratification. During fall turnover low outflow elevations increase water column mixing and draws warmer water deeper, leading to slightly higher temperatures and nutrient concentrations than shallow withdrawal elevations. The 15 m depth (540 m above sea level) outflow generally provided the best compromise for overall reservoir and outflow nutrient reduction.

Abstract Dams are typically designed to serve as flood protection, provide water for irrigation, human and animal consumption, and harness hydropower. Despite these benefits, dam operations can have adverse effects on in-reservoir and downstream water temperature regimes, biogeochemical cycling and aquatic ecosystems. We present a water quality dataset of water withdrawal scenarios generated after implementing the 2D hydrodynamic and water quality model, CE-QUAL-W2. The scenarios explore how six water extraction scenarios, starting at 5 m above the reservoir bottom at the dam and increasing upward at 10 m intervals to 55 m, influence water quality in Lake Diefenbaker reservoir, Saskatchewan, Canada. The model simulates daily water temperature, dissolved oxygen, total phosphorus, phosphate as phosphorus, labile phosphorus, total nitrogen, nitrate as nitrogen, labile nitrogen, and ammonium at 87 horizontal segments and at 60 water depths during the 2011–2013 period. This dataset intends to facilitate a broader investigation of in-reservoir nutrient dynamics under dam operations, and to extend the understanding of reservoir nutrient dynamics globally.

Abstract Algal simulations in many water quality models perform poorly because of oversimplifications in the process descriptions of the algae growth mechanisms. In this study, algae simulations were improved by implementing variable chlorophyll a/algal biomass ratios in the CE-QUAL-W2 model, a sophisticated two-dimensional laterally-averaged water quality model. Originally a constant in the model, the chlorophyll a/algal biomass ratio was reprogrammed to vary according to the nutrient and light limiting conditions in the water column. The modified model was tested on Lake Diefenbaker, a prairie reservoir in Saskatchewan, Canada, where, similar to many other lakes in the world, field observations confirm variable spatiotemporal ratios between chlorophyll a and algal biomass. The modified version yielded more accurate simulations compared to the standard version and provides a promising algorithm to improve results for many lakes and reservoirs globally.

In this study, we built a two-dimensional sediment transport model of Lake Diefenbaker, Saskatchewan, Canada. It was calibrated by using measured turbidity data from stations along the reservoir and satellite images based on a flood event in 2013. In June 2013, there was heavy rainfall for two consecutive days on the frozen and snow-covered ground in the higher elevations of western Alberta, Canada. The runoff from the rainfall and the melted snow caused one of the largest recorded inflows to the headwaters of the South Saskatchewan River and Lake Diefenbaker downstream. An estimated discharge peak of over 5200 m3/s arrived at the reservoir inlet with a thick sediment front within a few days. The sediment plume moved quickly through the entire reservoir and remained visible from satellite images for over 2 weeks along most of the reservoir, leading to concerns regarding water quality. The aims of this study are to compare, quantitatively and qualitatively, the efficacy of using turbidity data and satellite images for sediment transport model calibration and to determine how accurately a sediment transport model can simulate sediment transport based on each of them. Both turbidity data and satellite images were very useful for calibrating the sediment transport model quantitatively and qualitatively. Model predictions and turbidity measurements show that the flood water and suspended sediments entered upstream fairly well mixed and moved downstream as overflow with a sharp gradient at the plume front. The model results suggest that the settling and resuspension rates of sediment are directly proportional to flow characteristics and that the use of constant coefficients leads to model underestimation or overestimation unless more data on sediment formation become available. Hence, this study reiterates the significance of the availability of data on sediment distribution and characteristics for building a robust and reliable sediment transport model.