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How can water resource agencies make smart investments to ensure long-term water reliability when the future is fraught with deep climate and economic uncertainty? This study helped SEDAPAL, the water utility serving Lima, Peru, answer this question by drawing on state of the art methods for decision making under deep uncertainty. These methods provide techniques for evaluating the performance of a water system over a wide range of plausible futures and then developing strategies that are robust across these futures. Rather than weighting futures probabilistically to define an optimal strategy, these methodologies identify the vulnerabilities of a system and then evaluate the key trade-offs among different adaptive strategies. Through extensive iteration and collaboration with SEDAPAL, the study used these methods to define an investment strategy that is robust, ensuring water reliability across as wide a range of future conditions as possible while also being economically efficient. First,on completion, the study helped SEDAPAL realize that not all projects included in the Master Plan were necessary to achieve water reliability, and the utility could save 25 percent (more than $600 million) in investment costs. Second, the study helped focus future efforts on demand-side management, pricing, and soft infrastructure, a refocusing that is difficult to achieve in traditional utility companies. Third, the study helped SEDAPAL gain the support of regulatory and budget agencies through the careful analysis of alternatives. Fourth, the study allowed the utility to postpone lower priority investments, and to analyze future options based on climate and demand information that simply is not available now.

Ho Chi Minh City faces significant and growing flood risk. Recent risk reduction efforts may be insufficient as climate and socio-economic conditions diverge from projections made when those efforts were initially planned. This study demonstrates how robust decision making can help Ho Chi Minh City develop integrated flood risk management strategies in the face of such deep uncertainty. Robust decision making is an iterative, quantitative, decision support methodology designed to help policy makers identify strategies that are robust, that is, satisfying decision makers'objectives in many plausible futures, rather than being optimal in any single estimate of the future. This project used robust decision making to analyze flood risk management in Ho Chi Minh City's Nhieu Loc-Thi Nghe canal catchment area. It found that the soon-to-be-completed infrastructure may reduce risk in best estimates of future conditions, but it may not keep risk low in many other plausible futures. Thus, the infrastructure may not be sufficiently robust. The analysis further suggests that adaptation and retreat measures, particularly when used adaptively, can play an important role in reducing this risk. The study examines the conditions under which robust decision making concepts and full robust decision making analyses may prove useful in developing countries. It finds that planning efforts in developing countries should at minimum use models and data to evaluate their decisions under a wide range of conditions. Full robust decision making analyses can also augment existing planning efforts in numerous ways.