- Rising global temperatures are having lasting effects on mountain snow environments in the form of diminishing snowpacks, shorter accumulation seasons, and shifts in meltwater timing. Seasonal snowpack is a vital source of water for natural and human systems. In the forested mountain landscapes of the Pacific Northwest seasonal snowmelt feeds river systems, replenishes groundwater stores, provides the fuel source for hydropower, and is a principal water supply source for agriculture, recreation, and municipal needs. Knowledge of snow water storage and extent over large spatial areas is critical for regional water resource managers. Forest cover modifies snow accumulation and ablation rates via canopy interception and changes in sub-canopy energy balance processes. However, the ways in which snowpacks are affected by forest canopy processes vary depending on climatic, topographic and forest characteristics. Hydrologic models remain a useful tool to estimate snow cover extent and snow water equivalent, however, they are limited in forested environments by relying on imperfect assumptions or on poorly understood process-based relationships. Maritime snowpacks accumulate and reside at temperatures near freezing where changes in the sub-canopy energy balance can experience disproportionate effects of climate warming or forest cover change. Basic understanding of these competing processes is limited to case studies without an emphasis on identifying physically based relationships between the fundamental variables that control maritime sub-canopy snow-forest dynamics. Furthermore, without physical descriptions of appropriate forest characterization that can be easily obtained over a large spatial scale, snow-forest model applications remain tenuous.
This research examined and evaluated the combined effects of forest cover, climate variability, and elevation on snow accumulation and ablation in a maritime montane environment through results from a 6-year study of snow-forest interactions in the Oregon Cascades. A network of paired open and forested snow monitoring stations in the Oregon Cascades was designed for and maintained throughout this research. We continuously monitored snow and meteorological variables at paired forested and open sites at three elevations representing the Low, Mid, and High seasonal snow zones in the study region. Airborne lidar was flown over the network delivering high resolution forest structure data. The resulting dataset of micro-meteorological measurements, spatial snow water content data under various forest cover, and fully characterized forest environment provided the foundational basis of the dissertation. These data were used for inferences into the controls on sub-canopy snow surface energy balance, to identify key drivers of canopy interception, assess the scale effects of key forest structure parameterizations, and finally to develop, evaluate and validate a canopy snow interception model. The results address fundamental understanding of the sub-canopy energy environment and process controls on canopy snow interception in a maritime environment.
Sub-canopy longwave radiation was the dominant source of energy at all three elevations forested sites. Within the Low and Mid-elevations (1150m and 1325m, respectively) longwave accounted for 93% and 92%, of total energy inputs to the snowpack. The open sites at both locations preserved snowpack later into the spring melt season than within the forested areas by 4-26 days (Low-elevation) and 11-33 days (Mid-elevation). Conversely, at the High-elevation (1465m) the forested location had deeper and longer duration snowpacks than the adjacent Open site by 15-29 days. Snow canopy interception was found to be strongly associated with event size and event air temperature at all elevations. Snowfall events were classified based on the mean daily air temperature into three separate bins, Warm (T_air > 0.2 °C), Mild (-2.4 °C ≤ T_air ≤ 0.2 °C), and Cold (T_air < -2.4 °C). Warm temperature events show a higher canopy interception efficiency (CIE) for all sites across the study period, while colder T_air events demonstrated a lower corresponding CIE. Pairing T_air and event size with a novel 3-dimensional forest structure parameter in a simple modeling framework improved canopy interception prediction by a 27 mm SWE reduction in the seasonal average root mean squared error when compared to two contemporary models. The Tasseled Cap transformation is an orthogonal transformation of that weighs Landsat spectral bands to highlight certain component features of a spectral image along three axes: Brightness, Greenness and Wetness. The satellite-derived Wetness data structure had strong correlation with seasonal peak snow water equivalent as well as with key forest structure metrics. Implementing the satellite-derived forest structure parameter into a canopy snow interception modeling framework was evaluated and verified by modeling seasonal canopy snow interception magnitude at sites located in the Oregon Cascades and in the Canadian Rockies.
Collectively, the results presented here provide the hydrologic and forest management communities with a detailed quantitative assessment of sub-canopy snow-forest energy balance, identification of key snow-forest process-based relationships for canopy snow interception and the development of an interception model that is easily accessible through the use of a satellite-derived forest structure parameter readily transferable across model domains.