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    Author(s): Bruce J. McGurk; David L. Azuma
    Date: 1992
    Source: Res. Paper PSW-RP-211. Berkeley, CA: Pacific Southwest Research Station, Forest Service, U.S. Department of Agriculture; 13 p
    Publication Series: Research Paper (RP)
    Station: Pacific Southwest Research Station
    PDF: View PDF  (850 KB)


    Since 1982, under an agreement between the California Department of Water Resources and the USDA Forest Service, snow sensors have been installed and operated in Forest Service-administered wilderness areas in the Sierra Nevada of California. The sensors are to be removed by 2005 because of the premise that sufficient data will have been collected to allow "correlation" and, by implication, prediction of wilderness snow data by nonwilderness sensors that are typically at a lower elevation. Because analysis of snow water equivalent (SWE) data from these wilderness sensors would not be possible until just before they are due to be removed, "surrogate pairs" of high- and low-elevation snow sensors were selected to determine whether correlation and prediction might be achieved. Surrogate pairs of sensors with between 5 and 15 years of concurrent data were selected, and correlation and regression were used to examine the statistical feasibility of SWE prediction after "removal" of the wilderness sensors. Of the 10 pairs analyzed, two pairs achieved a correlation coefficient of 0.95 or greater. Four more had a correlation of 0.94 for the accumulation period after the snow season was split into accumulation and melt periods. Standard errors of estimate for the better fits ranged from 15 to 25 percent of the mean April 1 snow water equivalent at the high-elevation sensor. With the best sensor pairs, standard errors of 10 percent were achieved. If this prediction error is acceptable to water supply forecasters, sensor operation through 2005 in the wilderness may produce predictive relationships that are useful after the wilderness sensors are removed.

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    McGurk, Bruce J.; Azuma, David L. 1992. Correlation and prediction of snow water equivalent from snow sensors. Res. Paper PSW-RP-211. Berkeley, CA: Pacific Southwest Research Station, Forest Service, U.S. Department of Agriculture; 13 p


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    snow sensor, water supply forecasting, snow water equivalent prediction, snow pillow

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