Abstract
To improve predictive equations of the snowmelt process, we need to better understand the relative importance of various meteorological parameters. Factor analysis and regression analysis were used to determine the effectiveness of wind, air temperature, vapor pressure, and net radiation in predicting snowmelt. Analyses of meteorological and snowmelt data collected at a site near Boise, Idaho, in May 1973 showed that the standard error of daily snowmelt prediction could be decreased 13% by using vapor pressure, net radiation, and wind in predictive equations rather than just air temperature.
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