Traditionally, historical streamflow data have been used to develop synthetic streamflow scenarios for water resources planning and management. This paper investigates the incorporation of climatic data in such scenarios to improve their predictive ability for use in a decision support system for the Highland Lakes system in central Texas. Specifically, trends associated with the El Niņo-Southern Oscillation (ENSO), an interannual climatic anomaly, are considered in generating the scenarios. For central Texas, this teleconnective pattern is predictive of streamflow in advance of approximately a year, allowing for improved water management decisions. Both parametric and non-parametric scenario generation methods are considered for use in the decision support system, and cross-validation of the scenarios provides an estimate of their predictive skill.