Reservoir Operation during Drought by Applying Ensemble Streamflow Prediction and Stochastic Dynamic Programming

In Taiwan, utilization of water resources mainly relies on reservoir. Although the precipitation is abundant, lots of water is unavailable due to steep landform and spatio-temporally unequal distribution of rainfall. Especially in dry season, it is hard to satisfy the demand and conserve water. To allocate limited water resources effectively, inflow prediction has been developed and applied to reservoir operation for mitigating water shortage. National Science and Technology Center for Disaster Reduction (NCDR) produced ensemble streamflow prediction (ESP) for Shihmen Reservoir. It could be helpful information for determining release strategy in the following period with prediction. This study provides a framework for combining ESP with stochastic optimization, which contains implicit and explicit stochastic optimization (ISO and ESO), is applied to practical operation with for Shihmen Reservoir in 2009. Because of the characteristics of ISO and ESO, the release strategy decided by two models are presented as slight difference. While confronting drought, ISO tends to disperse the distribution of inflow in the predicted period and determine a conservative decision; on the contrary, ESO absorbs the traits of prediction and makes the policy with confidence. Therefore, ESO model could be adopted to the process of decision making if the precision of inflow prediction is promoted; on the other hand, ISO model could be used to deal with indefinite uncertainty if the reliability of prediction is insufficient.