Sagehen Creek Field Station

30 Dec, 05 AM - 30 Dec, 09 AM

Maximum snow interception through thick canopy cover results in almost a 50 percent decrease in snow water equivalence under canopy. Topographical (slope, aspect) and vegetative variation such as changes in predominant vegetative type, stand maturity and stand density can greatly vary this proportion. Manually collected snow courses do not allow for proper representation of the spatial variance of snow distribution. In order to properly represent water storage in the snow pack, it is imperative to properly model SWE (snow water equivalent) with accuracy greater than currently available due to the natural complexity and the increasing climactic variability in the Sierra Nevada Mountains. Furthermore, since topography and prevailing wind (to a lesser extent), are constant from year to year, snow tends to accumulate in similar areas. So if SWE variability is determined for a geographic unit, such as a watershed, and characterized by intense samplings both spatially and temporally, one could potentially make predictions in forthcoming years without the need for such a rigorous sampling regime. Due to the prohibitive cost involved in more traditional methods of monitoring SWE ( e.g. the NRCS?s SNOTEL systems, snow pillows, snow pit analysis, snow courses etc) on a finer resolution, alternative methods such as a wireless sensor network may provide useful information for aerially extensive estimates. Previous studies have begun to expand upon the limited scope of snow courses and SNOTEL sites and have started increasing densities of sensors by implementing wireless sensor networks in efforts to capture SWE and snow depth variability. In fact ultrasonic snow depth sensor arrays have already shown that while the SWE decreases almost %50 percent under thick canopy, the reverse also holds true; SWE increases ~57% in open areas. While these previous studies show interesting results, the door has just opened to increase the resolution and SWE accuracy of measurement, especially in large areas. Several questions arise from initial results of studies: (1) how do basin wide meteorological characteristics affect SWE distribution (such as prevailing wind speed and temperatures)? (2) Previous studies have shown the applicability of multiple sensor sites for characterizing the variability in open and canopied sites, but what happens in between and how many sensors would be needed to capture the optimum resolution? To begin the process of appropriately addressing the above questions, this study hopes to first ask and answer the following questions. 1. Can a wireless sensor network comprised of ultrasonic snow depth and temperature sensors properly catch or extrapolate SWE measurements if paired with a local SNOTEL site? 2. Are wireless sensor networks sufficiently robust to work in alpine environments where there is scant to little ground truthed data available? 3. Can wireless sensor network data be paired with ARCGIS products and spatial analysis tools such as universal kriging in order to represent the spatial heterogeneity of SWE within a pre-defined study area? 4. Finally, can interpolation accuracy be assessed between wireless sensor nodes in order to begin to answer the question of ?how many sensors are needed to characterize and account for the variability of SWE under canopy cover??

Visit #20037 @Sagehen Creek Field Station

Approved

Under Project # 20285 | Research

Quantifying Snow Water Equivalent Variations from Topographic and Vegetative Differences through Wireless Sensor Networks, LIDAR, GIS and SNOTEL Site Integration.

research_assistant - University of Nevada

Reservation Members(s)

David Moeser Dec 30, 2009 (1 days)

Reserve Resources(s) | Create Invoice

Day Use 1 Dec 30 (4 hours)