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Optimizing Operational Policies of a Korean Multireservoir System Using Sampling Stochastic Dynamic Programming with Ensemble Streamflow Prediction
Cited 61 time in
Web of Science
Cited 71 time in Scopus
- Authors
- Issue Date
- 2007
- Publisher
- American Society of Civil Engineers
- Citation
- Journal of Water Resources Planning and Management, 133(1), 4-14
- Keywords
- Optimization ; Forecasting ; Reservoir operation ; Korea ; Streamflow ; Predictions
- Abstract
- This study presents state-of-the-art optimization techniques for enhancing reservoir operations which use sampling stochastic
dynamic programming SSDP with ensemble streamflow prediction ESP . SSDP used with historical inflow scenarios SSDP/Hist
derives an off-line optimal operating policy through a backward-moving solution procedure. In contrast, SSDP used with monthly
forecasts of ESP SSSDP/ESP reoptimizes the off-line policy. These stochastic models are used to derive a monthly joint operating policy
during the drawdown period of the Geum River multireservoir system in Korea. A cross-validation test of 1,900 simulation runs
demonstrates that: 1 proposed stochastic models that explicitly include inflow uncertainty are superior to those that do not; 2 updating
policy with ESP forecasts is appropriate in this reservoir system; 3 the lower dam of the Geum River multireservoir system should
maintain elevation of 66.5 m during the beginning of the drawdown period to avoid significant increase in the downstream water
shortages; and 4 forecasting accuracy may result in considerable effects on joint reservoir operations.
- ISSN
- 0733-9496
- Language
- English
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