Abstract Submission: The Colorado River Basin (CRB) provides water to over 40 million people and 5.5 million acres of irrigable land, defining the western United States as we know it today. However, this crucial water supply is currently threatened by a multi-decade drought and cascading demands. These climate driven water scarcity risks are intensified by rapid urban growth in the region; enhanced or alternative supply and demand management practices are desperately needed. Season-ahead reservoir inflow forecasts, coupled with infrastructure management, can inform decisions at lead times of months to seasons or longer. Such forecasts may also provide impetus to shift water use toward high priority sectors and activities. In the CRB, forecasts from the River Forecast Center (RFC) are used to inform the Bureau of Reclamation’s reservoir modeling system. RFC utilizes an ensemble streamflow prediction approach, which performs very well once the streamflow season starts (typically April), however, longer-lead forecasts, prior to snowpack being established, tend to be less reliable. Alternatively, incorporating large scale climate variables and teleconnections provides opportunities to improve forecast performance, especially at longer lead times. We present a complementary forecast model framework to the CRB that explicitly captures asymmetric relationships between climate indices and hydrologic variables. We apply this framework to five locations throughout the upper basin to assess spatial variation in performance and predictor selection. Parallel research focuses on coupling seasonal forecasts with large-scale CRB water allocation models to explore management strategies and economic impacts related to long-term drought conditions.