You are here: Home
/ Publication Information
Title: Estimating snowpack density from Albedo measurement
Author: Smith, James L.; Halverson, Howard G.;
Source: Res. Pap. PSW-RP-136. Berkeley, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Forest and Range Experiment Station. 13 p
Publication Series: Research Paper (RP)
Description: Snow is a major source of water in Western United States. Data on snow depth and average snowpack density are used in mathematical models to predict water supply. In California, about 75 percent of the snow survey sites above 2750-meter elevation now used to collect data are in statutory wilderness areas. There is need for a method of estimating the water content of a snowpack in inaccessible locations by remote means. If snow albedo can be measured from aircraft and these measures correlated with snowpack density, we should be able to estimate density remotely. But a correlation must first be established from ground-based observations. This paper reports a study of albedo measured 1 meter above the snow and the correlation of these measurements with snowpack density. The study was done at the Forest Service's Central Sierra Snow Laboratory, Soda Springs, California. The findings have application for developing a method for remote sensing of snow density.
Keywords: snowpacks, density, depth, water content, measurements, remote sensing, albedo, runoff forecasting
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
XML: View XML
Smith, James L.; Halverson, Howard G. 1979. Estimating snowpack density from Albedo measurement. Res. Pap. PSW-RP-136. Berkeley, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Forest and Range Experiment Station. 13 p
Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility