The development of management models for identification of optimal operating policies for reservoirs spans more than four decades of research. In an uncertain environment, where climatic factors such as streamflow are stochastic, the returns from reservoir releases defined by the optimal policy are uncertain. Furthermore, the consequences of release decisions cannot be fully realized until future unknown events occur. In the present study, Stochastic Dynamic Programming (SDP) model is developed to obtain optimal operating policy for Klang Gate reservoir, Malaysia.\nHistoric rainfall data is used to calculate the inflow which considers the stochastic nature of inflow in the form of inflow transition probability matrices.\nThe proposed (SDP) is developed to provide the optimal release policy on monthly basis from Klang Gate, Malaysia. Three different performance criterions have been examined by simulating the Klang gate with respect to the policy derived by SDP. The results showed that high level of reliability and reasonable level of resilience, vulnerability and accordingly minimizing the deviation between release and demand have been achieved.

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