Metcalfe, Robert A

Understanding snowpack variability is important as it plays an imperative role in environmental, hydrologic, and atmospheric systems. Research questions related to three linked areas were investigated in this thesis: 1) scaling issues in snow hydrology, 2) forest-snowpack relationships, and 3) methods of integrating snow water equivalent (SWE) into a hydrologic model for a large, forested drainage basin in central Ontario. The first study evaluated differences in SWE across process, measurement, and model scales. Point scale snowpack measurements could be bias corrected using scaling factors derived from a limited number of transect measurements and appropriately stratified point scale measurements may be suitable for replacing transect scale mean SWE when transect data are not possible to collect. Comparison of modelled products to measurements highlighted the importance of understanding the spatial representativeness of in-situ measurements and the processes those measurements represent when validating snow products or assimilating data into models.The second study investigated the efficacy of field-based, and remotely sensed datasets to describe forest structure and resolve forest-snowpack relationships. Canopy cover was highly correlated with melt rate and timing at the site scale however, significant correlations were present in 2016 but not 2017, which was attributed to interannual differences in climate. Peak SWE metrics did not correlate well with forest metrics. This was likely due to mid-winter melt events throughout both study years, where a mix of accumulation and melt processes confounded forest-snowpack relationships. The third study evaluated the accuracy of the Copernicus SWE product and assessed the impact of calibrating and assimilating SWE data on model performance. The bias corrected Copernicus product agreed with measured data and provided a good estimate of mean basin SWE. Calibration of a hydrologic model to subbasin SWE substantially improved modelled SWE performance. Modelled SWE skill was not improved by assimilating SWE into the calibrated model. All models evaluated had similar streamflow performance, indicating streamflow in the study basin can be accurately estimated using a model with a poor representation of SWE. The findings from this work improved knowledge and understanding of snow processes in the hydrologically significant Great Lakes-St Lawrence Forest region of central Ontario.

Author Keywords: data assimilation, hydrologic model, multi-objective calibration, remote sensing, scale, snow

In this study, we attempt to enhance current knowledge of ecological responses to riverine alterations from waterpower by using a bottom-up food up approach. A series of extensive and intensive study components were performed across northern Ontario, Canada, where biological (nutrients, dissolved organic matter (DOM) and periphyton) and physical (water level and thermal regimes) ecological indicators were examined in regards to alterations from dams and waterpower facilities. Overall, we found that the water levels and thermal regimes deviated from their reference condition at sites below the dams, whereas the biological indicators were more resilient to river alterations. Our results suggest that the characteristics of the watershed were influential in controlling the variability of nutrients and DOM resources in rivers within the boreal watersheds of northern Ontario, as well as the for the downstream recovery patterns of the physical indicators. The recovery of the periphyton communities downstream of the dams were also predicted to be cumulatively related to the physical alterations, nutrient availability and the possible displacement of invertebrate communities. Therefore, our bottom-up food web approach was not effective for better understanding how ecological responses from waterpower cascade through aquatic food webs, and instead multiple indicators should be used for examining the ecological responses in these particular river systems.

Author Keywords: dissolved organic matter, ecological indicators, river alteration, waterpower facilities

Water balance models calculate water storage and movement within drainage basins, a primary concern for many hydrologists. A Thornthwaite water balance model (H2OBAAS) has shown poor accuracy in predicting low flows in the Petawawa River basin in Ontario, so lake storage and winter snow processes were investigated to improve the accuracy of the model. Lake storage coefficients, represented by the slopes of lake stage vs. lake runoff relationships, were estimated for 19 lakes in the Petawawa River basin and compared on a seasonal and inter-lake basis to determine the factors controlling lake runoff behaviour. Storage coefficients varied between seasons, with spring having the highest coefficients, summer and fall having equal magnitude, and winter having the lowest coefficients. Storage coefficients showed positive correlation with lake watershed area, and negative correlation with lake surface area during summer, fall, and winter. Lake storage was integrated into the H2OBAAS and improved model accuracy, especially in late summer, with large increases in LogNSE, a statistical measure sensitive to low flows. However, varying storage coefficients with respect to seasonal lake storage, watershed area, and surface area did not improve runoff predictions in the model. Modified precipitation partitioning and snowmelt methods using monthly minimum and maximum temperatures were incorporated into the H2OBAAS and compared to the original methods, which used only average temperatures. Methods using temperature extremes greatly improved simulations of winter runoff and snow water equivalent, with the precipitation partitioning threshold being the most important model parameter. This study provides methods for improving low flow accuracy in a monthly water balance model through the incorporation of simple snow processes and lake storages.

Author Keywords: Lake Storage, Model Calibration, Monthly Water Balance, Petawawa River, Precipitation Partitioning, Snow Melt

Stream solutes are strongly linked to hydrology, and as such, we sought to better understand how hydrology, particularly flooding, influences nitrogen (N) and phosphorus (P) levels. We used a long-term dataset of monthly water quality samples for many Ontario, Canada, catchments to assess the effects of landscape variables, such as land use and physiography, on the export of nutrients during floods, and to characterize overall concentration-discharge patterns. In general, we found that landscape variables could partially explain the export variation in flood waters, but that the importance of specific variables depended on flood characteristics. We also found that overall concentration-discharge relationships for N and P C were positive, but non-linear, with greater concentrations on the rising limb of the hydrograph depending on the nutrient. With these results, we have identified general patterns between nutrients and hydrology, which will be helpful for managing the ecological effects of flooding.

Author Keywords: C-Q relationships, Discharge, Export, Flooding, Nutrients, Thresholds

Increases in flooding due to anthropogenic influences such as climate change and reservoir creation will undoubtedly impact aquatic ecosystems, affecting physical, chemical, and biological processes. We used two approaches to study these impacts: a whole-ecosystem reservoir flooding experiment and a systematic literature review. In the whole-ecosystem experiment, we analyzed the impact of flooding on nutrient release from stored organic matter in an upland forest. We found that flooded organic matter produced N (nitrogen) and P (phosphorus), but that more N was released relative to P, increasing the N:P ratio over time. In the systematic literature review, we linked small (<10 year recurrence interval) and extreme (>100 year recurrence interval) floods to changes in 10 aquatic ecosystem services. Generally, extreme floods negatively impacted aquatic ecosystem service provisioning, while small floods contributed positively. Overall, we found that flood impacts vary depending on ecosystem properties (organic matter content) and flood characteristics (magnitude).

Author Keywords: ecosystem services, flooding, nutrients, reservoirs, rivers