Research that addresses climate change response recommendsmitigation or adaptation measures. Climate mitigation is defined as any action taken to permanently eliminate or reduce the long-termand hazards of climate change to human life and property. Climate adaptation refers to the ability of a system to adjust to climate change in order to modulate potential damage, to take advantage of opportunities, or to cope with the consequences. Climate mitigation and adaptation should not be seen as alternatives to each other, but rather as a combined set of actions in an overall strategy. However, existing research related to climate change in water resources tend to only concentrate on mitigation field, or rainfall forecasting and change assessment. In this condition, researches of climate change decision making is needed to realize adaptation planning. Climate change is regarded as deep uncertainty which is defined as poor knowledge about probability of the future states in UKCIP (2003). Robust Decision Making (RDM) is a particular set of methods and tools developed over the last decade, primarily by researchers associated with the RAND Corporation, designed to support decision making and policy analysis under conditions of deep uncertainty. It is an iterative decision analytic framework that helps identify potential robust strategies, characterize the vulnerabilities of such strategies, and evaluate the tradeoffs among them.In this context, this study tests applicability of RDM over Optimal Decision Making (ODM) by comparing to the results for water supply planning in a Korean dam case. Both RDM and ODM were conducted for estimating same alternatives of Andongdam and Imhadam by simulating various futures states, 25 scenarios combining twelve GCMs with A1B, A2, and B1 emission scenarios which were used to estimate various performances indices. abcd hydrologic model was utilized to generate the inflow for each dams and Hec-ResSim as the reservoir operation model was used to estimate dam release. There are six alternatives which are set to increase dam effective storage for preparation during the drought period. As a result, the rank of alternatives between ODM and RDM method shows that average rank differences is 0.33 ∼ 1.33. Furthermore this study analyzes the effectiveness of RDM under climate change condition. Assumingcases in which a planner should choose 5, 10, 15, 20 scenarios in 25 scenarios, standard deviations of ranks with ODM and RDM are estimated. In the results, the standard deviation of ranks with RDM is less than with ODM. This means that the ranks with RDM is less effected by what scenarios to be selected than ODM. Decision making under climate change uncertainty is proper to be dealt with ;;Robust’ rather than ;;Optimal’ because the climate change scenarios are vast and the knowledge of probability of event is very poor. In this context, the research tests applicability of RDM were compared to ODMs by applying the results to the water supply planning. The results show that there are rank differences between ODM and RDM even though both tests used the same scenarios and alternatives. In addition, RDM has efficiencies over ODM when required to determine some scenarios in existing scenarios. This study is significant in order to attempt a new decision making method for climate change in Korea.
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