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

TitleOptimal Drought Management Using Sampling Stochastic Dynamic Programming with a Hedging Rule
Publication TypeJournal Article
Year of Publication2011
AuthorsEum, Hyung-Il, Kim Young-Oh, and Palmer Richard N.
JournalJournal of Water Resources Planning and Management
Volume137
Pagination113
Date Published2011
Keywordsclimate 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.