Title | Optimal Drought Management Using Sampling Stochastic Dynamic Programming with a Hedging Rule |
Publication Type | Journal Article |
Year of Publication | 2011 |
Authors | Eum, Hyung-Il, Kim Young-Oh, and Palmer Richard N. |
Journal | Journal of Water Resources Planning and Management |
Volume | 137 |
Pagination | 113 |
Date Published | 2011 |
Keywords | climate science center, droughts, dynamic programming, Korea, Reservoir operation |
Abstract | This study develops procedures that calculate optimal water release curtailments during droughts using a future value function derived with a sampling stochastic dynamic programming model. Triggers that switch between a normal operating policy and an emergency operating policy (EOP) are based on initial reservoir storage values representing a 95% water supply reliability and an aggregate drought index that employs 6-month cumulative rainfall and 4-month cumulative streamflow. To verify the effectiveness of the method, a cross-validation scheme (using 2,100 combination sets) is employed to simulate the Geum River basin system in Korea. The simulation results demonstrate that the EOP approach: (1) reduces the maximum water shortage; (2) is most valuable when the initial storages of the drawdown period are low; and (3) is superior to other approaches when explicitly considering forecast uncertainty. |
Optimal Drought Management Using Sampling Stochastic Dynamic Programming with a Hedging Rule
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