Snowpack information is used make management and planning decisions by many organizations in the West, including the Salt River Project, New Mexico and Colorado state engineers, and the California Department of Water Resources. Originally, data from national Snow Telemetry (SNOTEL) stations provided a simple index of spring runoff. The relatively long historical record of such data has been used to develop empirical models that generate springtime runoff forecasts based on wintertime SNOTEL snow water equivalent (SWE) values. However, since the skill of these models decreases substantially during extreme climatic conditions—such as droughts and floods, which are anticipated to increase due to global climate change—SNOTEL data may become less useful. Therefore, this research focuses on deriving forecasts using hydrologic models that consider the spatial variability of snowpack. The use of these models is especially important for forecasting runoff during unusual climatic conditions and for simulating streamflow under different climate change scenarios.
To provide data for current and future stakeholder needs, CLIMAS researchers developed spatially distributed SWE products that can give estimates of future runoff almost as quickly as snow cover conditions change. The researchers also developed snow-covered area products using remotely sensed data such as aerial photographs and satellite images taken at different wavelengths. By applying a statistical model to the snow water equivalent point measurements from SNOTEL sites, they obtained spatially distributed snow water equivalent estimates for the region. After correcting the results by "masking," or removing from the analysis, areas identified by remote sensing as having no snow, researchers incorporated the estimates of snow water equivalent into hydrologic models to demonstrate the use of the products to stakeholders.