°ä²¹±ô±ô¾±³ó²¹²ÔÌý, LoganÌý1Ìý;ÌýZagona, EdithÌý2Ìý;ÌýRajagopalan, BalajiÌý3
1ÌýCEAE and CADSWES, University of Colorado at Â鶹ӰԺ
2ÌýCEAE and CADSWES, University of Colorado at Â鶹ӰԺ
3ÌýCEAE and CIRES, University of Colorado at Â鶹ӰԺ
In light of the increased uncertainty of future water supplies and demands, water managers, stakeholder and policy makers must develop strategies to provide for future equitable and realistic water use. Climate change and natural variability inherently make supply projections highly uncertain, while future demands depend on different unknowns associated with population growth, advancements in technology, energy needs, and riparian ecosystems. In order to cope with these uncertainties, decision-makers should apply robust and adaptive strategies that perform over a range of future conditions. The aim of this research is to develop a methodology to measure policy performance over a range of future conditions and develop a search algorithm that selects the “best“ management strategy based on user-defined performance criteria.Furthermore, methodologies will expand upon bottom-up and decision scaling approaches. To illustrate the utility and importance of adaptive management, our methodology will be applied to a Gunnison River Basin and Upper Colorado River climate change study. This research is a follow on to a Reclamation WaterSMART project.
Brown, C., Y.Ghile, M.Laverty, and K.Li (2012), Decision scaling: Linking bottom-up vulnerability analysis with climate projections in the water sector, Water Resour. Res., 48, W09537, doi:10.1029/2011WR011212.