Snow Depth Variations from Storm Trajectory and Mountain Topography in the Tuolumne River Basin

TitleSnow Depth Variations from Storm Trajectory and Mountain Topography in the Tuolumne River Basin
Publication TypeConference Proceedings
Year of Conference2017
AuthorsSaldivar, Jeremy, and S. Skiles McKenzie
Conference Name85th Annual Western Snow Conference
Date Published2017
Conference LocationBoise, Idaho
Abstract

The Western United States relies heavily on water from snowmelt to sustain water demand through summer
months. Understanding the snow water equivalent (SWE), the product of depth and density, of a snowpack is crucial
for budgeting water appropriately. The varied topography of mountainous regions makes measuring snowpack depth
difficult. It has recently been demonstrated by the Airborne Snow Observatory (ASO; NASA-JPL) that differential
mapping of snow depth with an airborne scanning lidar is an efficient and accurate way to monitor snow depth at the
watershed scale. Snow depth time series from ASO in the Tuolumne Basin, CA show that snow does not accumulate
evenly. Factors such as the trajectory of a storm, snow accumulation rates, and aspect/elevation can affect snow
deposition patterns. Here, we use ASO measured snow depth on April 2014, April 2015, and March 2017 and two
acquisitions before and after a precipitation event (April 8, 2015) to assess variation in snow depth across the basin.
Results show that the most snow is present on northerly aspects and at elevations from 10,000 - 12,000 feet.
Potential for future research includes looking at a different storm event and more basins as LiDAR generated snow
depths become available.

URL/files/PDFs/2017Saldivar.pdf