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Optimal Drought Management Using Sampling Stochastic Dynamic Programming with a Hedging Rule

Authors:

Hyung-Il Eum

Young-Oh Kim

Richard Palmer

Publication Type:
Journal Article
Year of Publication:
2011
Secondary Title:
Journal of Water Resources Planning and Management
Pages:
113
Volume:
137
Year:
2011
Date:
2011

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.