MODELING MEASUREMENT ERRORS WHEN ESTIMATING SNOW WATER EQUIVALENT

Recently the National Weather Service has developed a geostatistical model to generate areal estimates of snow water equivalent (the water content of snowpack) in various river basins throughout the Western USA. The areal snow water equivalent estimates are used to update the hydrologic simulation models used to produce extended streamflow forecasts in the USA. Currently, when the snow water equivalent estimates are obtained, it is assumed that the ground-based and airborne data used in the spatial model are measured without error. In this research, we illustrate how to modify the spatial prediction model to account for measurement errors in the observed airborne and ground-based snow data, derive the expressions necessary to model the measurement errors, and illustrate the modeling techniques on data collected in the Upper Colorado River basin.