Decadal (~10-years) scale flow projections in the; Colorado River Basin (CRB) are increasingly important for water; resources management and planning of its reservoir system. Physical; models – Ensemble Streamflow Prediction (ESP) – do not have skill; beyond interannual time scales. However, Global Climate Models have good; skill in projecting decadal temperatures. This, combined with the; sensitivity of CRB flows to temperature from recent studies, motivate; the research question - can skill in decadal temperature projections be; translated to operationally skillful flow projections and consequently,; water resources management? To explore this, we used temperature; projections from the Community Earth System Model – Decadal Prediction; Large Ensemble (CESM-DPLE) along with past basin runoff efficiency as; covariates in a Random Forest (RF) method to project ensembles of; multi-year mean flow at the key aggregate gauge of Lees Ferry, Arizona.; RF streamflow projections outperformed both ESP and climatology in a; 1982-2017 hindcast, as measured by ranked probability skill score. The; projections were disaggregated to monthly and sub-basin scales to drive; the Colorado River Mid-term Modeling System (CRMMS) to generate; ensembles of water management variables. The projections of pool; elevations in Lakes Powell and Mead – the two largest U.S. reservoirs; that are critical for water resources management in the basin – were; found to reduce the hindcast median root mean square error by up to -20; and -30% at lead times of 48- and 60-months, respectively, relative to; projections generated from ESP. This suggests opportunities for; enhancing water resources management in the CRB and potentially; elsewhere.
