Optimal Drought Management Using Sampling Stochastic Dynamic Programming with a Hedging Rule
Publication: Journal of Water Resources Planning and Management
Volume 137, Issue 1
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.
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Acknowledgments
This research was supported by a grant (Code No. UNSPECIFIED1-6-2) from the Sustainable Water Resources Research Center of 21st Century Frontier Research Program, the SNU SIR BK21 Research Program funded by the Ministry of Education and Human Resources Development and the Engineering Research Institute of Seoul National University, Korea.UNSPECIFIEDUNSPECIFIED
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 137 • Issue 1 • January 2011
Pages: 113 - 122
Copyright
© 2011 ASCE.
History
Received: Feb 23, 2010
Accepted: Apr 16, 2010
Published online: May 4, 2010
Published in print: Jan 2011
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