||Water availability is one of the most pressing scientific and societal issues facing the western United States. By 2060, population within the Colorado River Basin is expected to grow 19-48% relative to the 2010 population, significantly increasing the demand for water. Simultaneously, streamflow in the Colorado River is projected to decrease between 5-20%, putting further strain on an already over-allocated system. The highelevation snowpack of the Upper Colorado River Basin (UCRB) contributes the majority of runoff to the Colorado River through winter snow accumulation and springtime snowmelt. Recent studies have shown however, that dust from the Colorado Plateau shortens snowcover duration in the southeastern portion of the UCRB by 25-51 days. By accelerating snowmelt and extending the snow-free season, this impact appears to have shifted peak normalized runoff at Lee's Ferry, AZ 3-6 weeks earlier and reduced the total annual runoff of the Colorado River by 5-6% relative to the cleaner-snow conditions that existed prior to the western expansion of the United States in the mid-1800s. The agency charged with monitoring and forecasting streamflow in the UCRB is the Colorado Basin River Forecast Center (CBRFC). The CBRFC predicts snowmelt runoff using the temperature-index based SNOW-17 model that assumes an empirical relationship between temperature and snowmelt. The melt factor used in SNOW-17 is effectively a calibrated index of the relative proportions of snow surface energy balance components over the model's calibration period. If energy balance components deviate from the calibration-period mean, however, the fraction of radiation absorbed by the snowpack can also shift, influencing snowmelt timing and runoff and rendering the melt index less representative. Based on observations and in situ measurements, we know that dust deposition varies annually and spatially throughout the UCRB. The work described herein is directed at improving our understanding of the spatial and temporal variability of dust radiative forcing in snow and ultimately how that variability impacts streamflow forecasting in the UCRB.