Spatial and temporal variability of the snow environment in the Western Canadian Arctic

• Main Author: Mann, Philip
• Format: Text
• Language: English
• Published: Scholars Commons @ Laurier 2018
• Subjects: snow; SWE; drift; UAS; spatial variability; Hydrology; Arctic; Trail Valley Creek; Valley Creek; taiga; Tundra
• Online Access: https://scholars.wlu.ca/etd/2011; https://scholars.wlu.ca/context/etd/article/3117/viewcontent/PhilipMann_Master_Thesis.pdf

Snow cover in the Western Canadian Arctic is a significant input to the hydrological mass balance, it produces shelter and habitat for animals and humans, and supports interactions with vegetation and climate. The Arctic-tundra snow cover is greatly impacted by wind erosion, redistribution and deposition of snow during high wind events over the winter months. As a result, the end of winter snow cover is characterised by significant small-scale (on the order of a few meters) spatial variations in snow cover depth, density, and thus snow water equivalent (SWE), and runoff. Future climate related changes to snow cover depth and density will have significant consequences to the hydrology, ecology and climatology of the Arctic. This thesis reviews a multi-year record of snow studies in Siksik Creek, a sub-catchment of Trail Valley Creek (TVC) located in the western Canadian Arctic. TVC is located in the taiga-tundra transition zone, dominated by tundra, but with shrub and forest patches. Wind speed, snow depth, temperature and snowfall were measured over the full annual cycle, while end of winter snow accumulation was measured through ground based snow surveys and aerial imagery from an unmanned aerial system (UAS). The snow cover of TVC is highly influenced by its vegetation, topography and climate. Therefore, as the climate and vegetation continues to change in the coming decades, it is expected that there will be great changes in snow cover and, consequently, impacts on water resources, animal habitats and vegetation. The results from this thesis will provide information on improved methods to measure the snow environment, and the data sets needed to test snow models required for understanding future changes in snow.