Estimating the mean squared prediction error of the areal snow water equivalent estimate for a river basin

With the increased demand for water in the United States, particularly in the West, it is essential that water resources be accurately monitored. Consequently, the National Weather Service maintains a set of conceptual, continuous, hydrologic simulation models used to generate extended streamflow predictions, water supply outlooks, and flood forecasts. A vital component of the hydrologic simulation models is a snow accumulation and ablation model that uses observed temperature and precipitation data to simulate snow cover conditions. The simulated model states are updated throughout the snow season using snow water equivalent estimates obtained from airborne and ground-based snow water equivalent data. The National Weather Service has developed a spatial geostatistical model to estimate the areal snow water equivalent in a river basin. The estimates, which are obtained for various river basins in the West, are used to update the snow model. To facilitate updating of the simulated snow water equivalent estimates generated by the snow model, it is necessary to have estimates of the mean squared prediction errors of the areal snow water equivalent estimates. In this research, we derive an expression for the mean squared prediction error of the areal snow water equivalent estimate for a river basin.