In recognition of hydrologic uncertainty and seasonality, reservoir inflows are described as periodic Markov processes. The optimization of reservoir operations involves determination of the optimal release voulmes in the continuous time periods so that the expected total rewards resulting from the operations are maximized. This paper develops stationary and non-strationary stochastic dynamic programming models for identifying efficient reservoir release polices employing the best forecast of the current period's and previous period's inflow volumes were developed. As a case study, SDP and NACSDP models were applied in the Baekgok reservoir, Jincheon of Chungbuk province, to maximize annual operating rewards. The results indicated that NACSDP model could achieve 29.8 and 56.1% higher annual operating rewards than SDP and conventional reservoir operation.