A 50-node embedded sensor network was deployed across varying aspects, elevations, and canopy covers to capture spatial and temporal variations of snow depth, soil temperature and soil volumetric water content in the headwaters of Providence Creek, located at an elevation of 1,600-2,000 m in California’s Sierra Nevada. Three basin-wide, synoptic snow-depth surveys and two soil-moisture surveys conducted between March and September, 2010 were used to show that sensor network measurements capture the variability across the two main sub-catchments, as well as the full 2 km2 headwater catchment. Respective snow survey (sensor network) snow depths were 0-2.6 m (0.3-2.8 m) on March 14-15, 0-2.4 m (0.2-2.4 m) on March 20-21, and 0-2.4 m (0.1-2.2 m) on April 7-9. There were 123, 163, and 615 survey points in the three snow depth surveys, respectively. A regression analysis based on Gaussian Processes with kernel hyper-parameter optimization was used to develop estimates of snow depth and soil moisture at locations not measured. The physiographic inputs to the regression model were derived from a 30 m digital elevation model, and included elevation, slope, aspect, and potential solar radiation. The research site is part of the NSF-supported Southern Sierra Critical Zone Observatory, which is co-located within the Kings River Experimental Watersheds, a U.S. Forest Service integrated watershed research site in the Southern Sierra Nevada.
Meadows, M.W., Kerkez, B., Hartsough, P.C., Lucas, R.G., Bales, R.C., Hopmans, J.W., Glaser, S.D. (2010): Comparing plot-scale sensor measurements to the watershed level: a comprehensive case study of snow depth and soil moisture in the southern Sierra Nevada, California. Fall meeting, American Geophysical Union, December 2010. Abstract C13C-03..