Analyzing vegetation effects on snow depth variability in Alaska with airborne lidar

Authors: May, Lora D. University of Alaska Fairbanks; Stuefer, Svetlana L. University of Alaska Fairbanks; Goddard, Scott D. University of Alaska Fairbanks; Larsen, Christopher F. University of Alaska Fairbanks

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Abstract

Seasonal snowpack plays a critical role in hydrologic and ecologic processes, water budget estimation, weather prediction, and climate change studies. In boreal forest regions snow distribution is shaped by canopy-induced processes that are strongly controlled by the structure of the forest canopy at small spatial scales. Identifying the vegetation metrics responsible for snow depth spatial variability continues to be a challenge in boreal forests where land cover is highly heterogeneous and studies are limited. Airborne lidar has advanced our understanding of links between forest snow distribution and vegetation impacts. This study analyzes high resolution (0.5 m) lidar data sets acquired during NASA's SnowEx field campaign in Alaska and compares them statistically with the vegetation metrics of land cover class and canopy height. Airborne lidar data was collected for a boreal forest site during snow-off and peak snow-on accumulation in 2022 and 2023. Lidar snow depth (98 ± 15 cm) and canopy height maps were created from lidar data sets. A total of 85.9 million lidar snow depth and canopy height values were available for this study. Three subsets totaling 6.1 million of the total snow depths and canopy heights were used in the analysis. Extensive In Situ field snow depth measurements were collected concurrently with the peak snow- on lidar survey and were used to validate lidar accuracy. Results showed statistically significant differences in mean snow depths between all land cover and canopy height classes (p < 2.2e-16), with the greatest significant difference between shrub and deciduous forest (6-15 cm) and shrub and wetlands (7-14 cm). For canopy height classes, forest and treeless (12-14 cm) had the greatest significant mean snow depth difference. This presentation will further summarize results on quantifying snow depth variability between vegetation metrics within boreal forests using NASA SnowEx Alaska data.

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