Understanding the links between remote conditions, such as tropical sea surface temperatures, and regional climate has provided the potential to improve land surface hydrologic predictability, with associated economic benefits. Better definition of the land surface moisture state provides an additional opportunity for improved hydrologic forecasting. We investigated the value of long-lead predictive skill added by knowledge of climate signals and land surface moisture state in the Missouri River basin. Forecasted flows were generated to represent the levels of predictability obtainable with knowledge of climate, snow and soil moisture states. The current Missouri River main stem reservoir system, due to its large storage capacity relative to annual inflow, showed little sensitivity to streamflow predictability at lead times of 12 months - only a 1.3% difference in system hydropower benefits between the perfect and no forecast skill scenarios. To evaluate the effects of hydrologic predictability on a smaller system, a hypothetical system was specified with a reduced storage volume. This smaller system showed a much larger difference of 5.3% benefit for perfect 12-month forecasts, representing $19.3 million in annual hydropower benefits above a no forecast skill alternative. Using the predictability due to climate, snow and soil moisture knowledge to produce long-lead hydrologic forecasts, $4.1 million of the $19.3 million of potential benefits could be were realized. Among the predictive indicators considered (two each for climate and hydrologic initial conditions), soil moisture added the greatest value, $2.3 million in excess of that already obtainable with knowledge of climate and snow state alone. As a baseline, a forecast method that uses only information present in past streamflows, and no knowledge of climate or initial moisture state was evaluated. For this technique, benefits of $1.4 million were obtained, substantially lower than the $4.1 million derived from knowledge of the climate and basin moisture state. This result indicates that incorporating climate information and better definition of the basin moisture state add modest but valuable predictability of runoff.