Amir Sadeghian

The South Saskatchewan River Basin is one of the Canada's largest river basins, containing approximately 75% of Canada's irrigated agriculture. Water quality and climate change are key concerns in this heavily managed watershed that is fed by snow and ice melt from the Canadian Rockies, and experiences both floods and droughts. This study applies a loosely coupled modelling framework to Lake Diefenbaker, the largest reservoir in the South Saskatchewan River Basin, to predict future water quality at the reservoir's two outflow dams. Model scenarios are developed in a two-dimensional water quality model of Lake Diefenbaker built in CE-QUAL-W2. The framework incorporates data from the cold-region hydrology Modélisation Environmentale Communautaire – Surface and Hydrology (MESH) model, the watershed nutrient export SPARROW model, and climate data from Coupled Model Intercomparison Project Phase 6 (CMIP6). Results predict that reservoir water quality at the outflow locations will deteriorate by the end of the century. Results differ between the thermal layers and the two dams. The epilimnion will generally see the greatest response to changes in climate and watershed inputs, with epilimnion temperatures increasing by up to approximately 3 °C. Total phosphorus and total nitrogen are predicted to increase, while dissolved oxygen will decrease in response to the warming conditions. Approximately 6–7 weeks less ice cover is predicted by 2100.

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.

Large multi-purpose reservoirs serve not only to generate hydropower but to supply water for agricultural irrigation, animal and human consumption and to provide flood control. One of the key factors affecting physical functioning and deteriorating aquatic ecosystems in reservoirs is climate change. For instance, increases in water temperature accelerate chemical reaction rates, decomposition rates and oxygen demand at the water-sediment interface. Earlier thermal stratification onset, and longer and more intense reservoir thermal stratification are all consequences of global warming. Such disruptions in thermal stratification have been associated with reductions in hypolimnion dissolved oxygen, increasing anoxia events and enhancing reservoir eutrophication. In this research paper, we implement the 2 D hydrodynamics and water quality model, CE-QUAL-W2, to investigate the effects of climate change and streamflow scenarios on the thermal structure of Lake Diefenbaker, a large, multipurpose reservoir, located in Saskatchewan, Canada. Model results indicate that meteorological variability will dictate a nonlinear increase in reservoir water temperature in the coming decades, where larger increases in water temperature will occur during summer and fall in the upper layers. Also, decreases in reservoir streamflows will reduce water temperature at intermediate layers during summer and fall. Our model can be used as a tool to mitigate and manage the effects of climate change on the reservoir water quality.

This study looks into sedimentation and erosion rates in Lake Diefenbaker, a prairie reservoir, in Saskatchewan, Canada, which has been in operation since 1968. First, we looked at the historical data in all different formats over the last 70 years, which includes data from more than 20 years before the formation of the lake. The field observations indicate high rates of shoreline erosion, especially in the upstream portion as a potential region for shoreline retreat. Because of the great importance of this waterbody to the province, monitoring sedimentation and erosion rates is necessary for maintaining the quality of water especially after severe floods which are more common due to climate change effects. Second, we used Google Maps Elevation API, a new tool from Google that provides elevation data for cross sections drawn between two points, by drawing 24 cross sections in the upstream area extending 250 m from each bank. This feature from Google can be used as an easy and fast monitoring tool, is free of charge, and provides excellent control capabilities for monitoring changes in cross-sectional profiles.

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.

Dissolved oxygen is an influential factor of aquatic ecosystem health. Future predictions of oxygen deficits are paramount for maintaining water quality. Oxygen demands depend greatly on a waterbody’s attributes. A large sediment–water interface relative to volume means sediment oxygen demand has greater influence in shallow systems. In shallow, ice-covered waterbodies the potential for winter anoxia is high. Water quality models offer two options for modelling sediment oxygen demand: a zero-order constant rate, or a sediment diagenesis model. The constant rate is unrepresentative of a real system, yet a diagenesis model is difficult to parameterise and calibrate without data. We use the water quality model CE-QUAL-W2 to increase the complexity of a zero-order sediment compartment with limited data. We model summer and winter conditions individually to capture decay rates under-ice. Using a semi-automated calibration method, we find an annual pattern in sediment oxygen demand that follows the trend of chlorophyll-a concentrations in a shallow, eutrophic Prairie reservoir. We use chlorophyll-a as a proxy for estimation of summer oxygen demand and winter decay. We show that winter sediment oxygen demand is dependent on the previous summer’s maximum chlorophyll-a concentrations.