Abstract

Snow is a critical storage component in the hydrologic cycle, but current measurement networks are sparse. In addition, the heterogeneity of snow requires surveying larger areas to measure the areal average. We present snow measurements using GPS interferometric reflectometry (GPS-IR). GPS-IR mea... Show moreSnow is a critical storage component in the hydrologic cycle, but current measurement networks are sparse. In addition, the heterogeneity of snow requires surveying larger areas to measure the areal average. We present snow measurements using GPS interferometric reflectometry (GPS-IR). GPS-IR measures a large area (∟ 100 m²), and existing GPS installations around the worlds have the potential to expand existing snow measurement networks. GPS-IR uses a standard, geodetic GPS installation to measure the snow surface via the reflected component of the signal. We report GPS-IR snow depth measurements made at Niwot Ridge, CO from October 2009 through June 2010. This site is in a topographic saddle at 3500 m elevation with a peak snow depth of 1.7 m near the GPS antenna. GPS-IR measurements are compared to bi-weekly snow surveys, a continuously-operating scanning laser system, and an airborne LIDAR measurement. The GPS-IR measurement of peak snow pack (1.36 to 1.76 m) matches manual measurements (0.95 m to 1.7 m) and the scanning laser (1.16 m). GPS-IR has root mean square error of 13 cm (bias=10 cm) compared to the laser, although differences between the measurement locations make comparison imprecise. Over the melt season, when the snowpack is more homogenous, the difference between GPS-IR and the laser is reduced (RMS=9 cm, bias=6 cm). In other locations, the GPS and LIDAR agree on which areas have more or less snow, but the GPS estimates more snow on the ground (1.58 and 1.02 33 m) than the LIDAR (1.15 and 0.71 m). Show less