Asphalt emulsions as an alternative for stabilizing base layers can be cost effective especially in cold regions where supplying hot mix is not economical. However, at low temperatures, Emulsion Aggregate Mixtures (EAM) show low strength at early ages and require a longer curing time for asphalt emulsions to break. In this study, a proposed dense-graded gravel base was treated with SS-1 emulsion. In order to evaluate early curing, one set of samples was cured at 5◦C and another at 24◦C. In addition, another set of samples was fully cured at 49◦C. Dynamic resilient modulus and permanent deformation tests were performed, and the durability of EAM was assessed through 10 freeze-thaw cycles. Furthermore, low-volume roads were designed with fully and partially cured EAMs. The achieved results from resistance tests, durability assessment and low volume road design identified that EAMs can be more appropriate for cold regions and that early low-strength can be compensated by aging asphalt binder. / October 2015

MSc thesis focusing on stream temperature research in a subarctic catchment. / Water temperature is an important stream characteristic that has a significant impact on the biological and chemical processes within an aquatic ecosystem, and it is sensitive to changes in climate and hydrologic regimes. Stream temperature dynamics are driven by heat exchange processes with the atmosphere and the interaction between surface water and groundwater, and it is uncertain how thermal regimes in northern environments will change under a warming climate. The objective of this thesis is to evaluate summer stream temperature variability in the Wolf Creek Research Basin (WCRB), and investigate relationships between stream temperature and hydrometeorological variables. Long-term stream temperature data for the WCRB in Yukon Territory, Canada was collected from 2002 to 2019 at both the outlet of Wolf Creek (WC), and for one of its high-elevation tributaries, Granger Creek (GC). Linear regression models were developed to explore relationships between stream temperature and various predictor variables at monthly and seasonal scales. The incorporation of an autoregressive term into regression models determined the importance of accounting for the autocorrelation structure of daily measurements, when considering annual regression coefficients. Model selection identified air temperature as the primary predictor variable for daily stream temperature, with streamflow and precipitation having variable inter-annual influences. Monthly stream temperatures at Granger Creek were related to air temperature, date of snow disappearance and antecedent stream temperature, whereas Wolf Creek monthly stream temperatures were most strongly related to antecedent stream temperature. These results suggest that the timing of snowmelt, streamflow, catchment thermal memory (as represented by antecedent stream temperature), and seasonal meteorology interact to influence interannual variability in summer stream temperature at the Wolf Creek Research Basin. / Thesis / Master of Science (MSc) / Water temperature plays an important role in determining the quality of an aquatic environment. There are many factors that control stream temperature, and it is uncertain how temperatures in northern environments will respond in the future. The objective of this thesis is to evaluate influences on summer stream temperature in the Wolf Creek Research Basin (WCRB). Stream temperature data was collected for the WCRB in Yukon Territory, from 2002 to 2019 for both Wolf Creek (WC) and Granger Creek (GC). Air temperature had the strongest relationship with daily stream temperature; streamflow and rain had inconsistent relationships through time. Monthly stream temperatures at Granger Creek were related to air temperature, date of snow disappearance and prior month’s stream temperature. Wolf Creek monthly stream temperatures were most strongly related to prior month’s stream temperature. These results highlight underlying influences on stream temperature, which may not be captured by a stream temperature models.

Soil moisture plays a major role in the hydrologic water balance and is the basis for most hydrological models. It influences the partitioning of energy and moisture inputs at the land surface. Because of its importance, it has been used as a key variable for many hydrological studies such as flood forecasting, drought studies and the determination of groundwater recharge. Therefore, spatially distributed soil moisture with reasonable temporal resolution is considered a valuable source of information for hydrological model parameterization and validation. Unfortunately, soil moisture is difficult to measure and remains essentially unmeasured over spatial and temporal scales needed for a number of hydrological model applications. In 2002, the Gravity Recovery And Climate Experiment (GRACE) satellite platform was launched to measure, among other things, the gravitational field of the earth. Over its life span, these orbiting satellites have produced time series of mass changes of the earth-atmosphere system. The subsequent outcome of this, after integration over a number of years, is a time series of highly refined images of the earth's mass distribution. In addition to quantifying the static distribution of mass, the month-to-month variation in the earth's gravitational field are indicative of the integrated value of the subsurface total water storage for specific catchments. Utilization of these natural changes in the earth's gravitational field entails the transformation of the derived GRACE geopotential spherical harmonic coefficients into spatially varying time series estimates of total water storage. These remotely sensed basin total water storage estimates can be routinely validated against independent estimates of total water storage from an atmospheric-based water balance approach or from well calibrated macroscale hydrologic models. The hydrological relevance and implications of remotely estimated GRACE total water storage over poorly gauged, wetland-dominated watershed as well as over a deltaic region underlain by a thick sand aquifer in Western Canada are the focus of this thesis. The domain of the first case study was the Mackenzie River Basin wherein the GRACE total water storage estimates were successfully inter-compared and validated with the atmospheric based water balance. These were then used to assess the WATCLASS hydrological model estimates of total water storage. The outcome of this inter-comparison revealed the potential application of the GRACE-based approach for the closure of the hydrological water balance of the Mackenzie River Basin as well as a dependable source of data for the calibration of traditional hydrological models. The Mackenzie River Basin result led to a second case study where the GRACE-based total water storage was validated using storage estimated from the atmospheric-based water balance P-E computations in conjunction with the measured streamflow records for the Saskatchewan River Basin at its Grand Rapids outlet in Manitoba. The fallout from this comparison was then applied to the characterization of the Prairie-wide 2002/2003 drought enabling the development of a new drought index now known as the Total Storage Deficit Index (TSDI). This study demonstrated the potential application of the GRACE-based technique as a tool for drought characterization in the Canadian Prairies. Finally, the hydroinformatic approach based on the artificial neural network (ANN) enabled the downscaling of the groundwater component from the total water storage estimate from the remote sensing satellite, GRACE. This was subsequently explored as an alternate source of calibration and validation for a hydrological modeling application over the Assiniboine Delta Aquifer in Manitoba. Interestingly, a high correlation exists between the simulated groundwater storage from the coupled hydrological model, CLM-PF and the downscaled groundwater time series storage from the remote sensing satellite GRACE over this 4,000 km2 deltaic basin in Canada.

Soil moisture plays a major role in the hydrologic water balance and is the basis for most hydrological models. It influences the partitioning of energy and moisture inputs at the land surface. Because of its importance, it has been used as a key variable for many hydrological studies such as flood forecasting, drought studies and the determination of groundwater recharge. Therefore, spatially distributed soil moisture with reasonable temporal resolution is considered a valuable source of information for hydrological model parameterization and validation. Unfortunately, soil moisture is difficult to measure and remains essentially unmeasured over spatial and temporal scales needed for a number of hydrological model applications. In 2002, the Gravity Recovery And Climate Experiment (GRACE) satellite platform was launched to measure, among other things, the gravitational field of the earth. Over its life span, these orbiting satellites have produced time series of mass changes of the earth-atmosphere system. The subsequent outcome of this, after integration over a number of years, is a time series of highly refined images of the earth's mass distribution. In addition to quantifying the static distribution of mass, the month-to-month variation in the earth's gravitational field are indicative of the integrated value of the subsurface total water storage for specific catchments. Utilization of these natural changes in the earth's gravitational field entails the transformation of the derived GRACE geopotential spherical harmonic coefficients into spatially varying time series estimates of total water storage. These remotely sensed basin total water storage estimates can be routinely validated against independent estimates of total water storage from an atmospheric-based water balance approach or from well calibrated macroscale hydrologic models. The hydrological relevance and implications of remotely estimated GRACE total water storage over poorly gauged, wetland-dominated watershed as well as over a deltaic region underlain by a thick sand aquifer in Western Canada are the focus of this thesis. The domain of the first case study was the Mackenzie River Basin wherein the GRACE total water storage estimates were successfully inter-compared and validated with the atmospheric based water balance. These were then used to assess the WATCLASS hydrological model estimates of total water storage. The outcome of this inter-comparison revealed the potential application of the GRACE-based approach for the closure of the hydrological water balance of the Mackenzie River Basin as well as a dependable source of data for the calibration of traditional hydrological models. The Mackenzie River Basin result led to a second case study where the GRACE-based total water storage was validated using storage estimated from the atmospheric-based water balance P-E computations in conjunction with the measured streamflow records for the Saskatchewan River Basin at its Grand Rapids outlet in Manitoba. The fallout from this comparison was then applied to the characterization of the Prairie-wide 2002/2003 drought enabling the development of a new drought index now known as the Total Storage Deficit Index (TSDI). This study demonstrated the potential application of the GRACE-based technique as a tool for drought characterization in the Canadian Prairies. Finally, the hydroinformatic approach based on the artificial neural network (ANN) enabled the downscaling of the groundwater component from the total water storage estimate from the remote sensing satellite, GRACE. This was subsequently explored as an alternate source of calibration and validation for a hydrological modeling application over the Assiniboine Delta Aquifer in Manitoba. Interestingly, a high correlation exists between the simulated groundwater storage from the coupled hydrological model, CLM-PF and the downscaled groundwater time series storage from the remote sensing satellite GRACE over this 4,000 km2 deltaic basin in Canada.