Climate change presents a significant planning challenge for water management agencies in the western United States. Changing precipitation and temperature patterns will disrupt their supply and extensive distribution systems over the coming decades, but the precise timing and extent of these impacts remain deeply uncertain, complicating decisions on needed investments in infrastructure and other system improvements. Adaptive strategies represent an obvious solution in principle, but are often difficult to develop and implement in practice. This paper describes work helping the Inland Empire Utilities Agency (IEUA) explicitly develop adaptive policies to respond to climate change and integrating these policies into the organizations' long-range planning processes. The analysis employs Robust Decision Making (RDM), a quantitative decision-analytic approach for supporting decisions under conditions of deep uncertainty. RDM studies use simulation models to assess the performance of agency plans over thousands of plausible futures, use statistical "scenario discovery" algorithms to concisely summarize those futures where the plans fail to perform adequately, and use these resulting scenarios to help decisionmakers understand the vulnerabilities of their plans and assess the options for ameliorating these vulnerabilities. This paper demonstrates the particular value of RDM in helping decisionmakers to design and evaluate adaptive strategies. For IEUA, the RDM analysis suggests the agency's current plan could perform poorly and lead to high shortage and water provisioning costs under conditions of: (1) large declines in precipitation, (2) larger-than-expected impacts of climate change on the availability of imported supplies, and (3) reductions in percolation of precipitation into the region's groundwater basin. Including adaptivity in the current plan eliminates 72% of the high-cost outcomes. Accelerating efforts in expanding the size of one of the agency's groundwater banking programs and implementing its recycling program, while monitoring the region's supply and demand balance and making additional investments in efficiency and storm-water capture if shortages are projected provides one promising robust adaptive strategy it eliminates more than 80% of the initially-identified high-cost outcomes. (C) 2010 Elsevier Inc. All rights reserved.
