Autoregressive Decision Rule in Aggregated Reservoir Operation
Publication: Journal of Water Resources Planning and Management
Volume 122, Issue 6
Abstract
Lag-1 correlation for inflow between consecutive periods is considered into reservoir model in many publications. This consideration greatly improves the reservoir models to incorporate the uncertainty of inflow. However, no publication was found to incorporate a correlation relationship for releases between consecutive periods to improve the operating policy for reservoir operations. This paper presents a methodology of autoregressive decision rule for an aggregated reservoir operation as a surrogate of a multireservoir system of the Upper Colorado River Basin. The method incorporates a lag-1 correlation for the releases between consecutive periods with the optimal operating policy solved by stochastic dynamic program. The decision rules with and without incorporation of the autoregressive correlation for the releases were then used in simulated operation of the reservoir with historical inflow records to evaluate their relative effectiveness. The results showed that the autoregressive decision rule yields more stable and higher reliability of annual water supply for the aggregated reservoir operations.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
Beik, S. E., and Yu, Y. S.(1984). “Optimal operation of multipurpose pool of Elk City Lake.”J. Water Resour. Plng. and Mgmt., ASCE, 110(1), 1–14.
2.
Beim, G. K., and Hobbs, B. F.(1988). “Analytical simulation of water system capacity reliability. II: A Markov chain approach and verification of the models.”Water Resour. Res., 24(9), 1445–1458.
3.
Booker, J. F.(1995). “Hydrologic and economic impacts of drought under alternative policy responses.”Water Resour. Bull., 31(5), 889–906.
4.
Harding, B. L., Sangoyomic, T. B., and Payton, E. A.(1995). “Impacts of a severe sustained drought on Colorado River water resources.”Water Resour. Bull., 31(5), 815–824.
5.
Karamouz, M., and Vasiliadis, H. V. (1992). “Bayesian stochastic optimization of reservoir operation using uncertain forecasts. Water Resour. Res., 28(5), 1221–1232.
6.
Liang, Q. (1988). “Reliability constrained Markov decision programming and its practical application to the optimization of multipurpose reservoir regulation.”Computational method in water resources, vol. 2: numerical methods for transport and hydrologic process, Elsevier Science Publishing Co., Inc., New York, N.Y., 417–422.
7.
Liang, Q. (1994). “Long-term optimal operation of multiple reservoir systems,” PhD dissertation, Univ. of Colorado at Boulder, Colo.
8.
Liang, Q., Johnson, L. E., and Yu, Y. S.(1996). “A comparison of two methods for multiobjective optimization for reservoir operation.”Water Resour. Bull., 32(2), 333–340.
9.
Nathanson, M. (1978). Updating the Hoover Dam documents . U.S. Government Printing Office, Denver, Colo.
10.
Schuster, R. J. (1987). “Colorado river simulation system documentation.”CRSM user manual, Bureau of Reclamation, U.S. Dept. of Interior, Denver, Colo.
11.
Su, S. Y., and Deininger, R. A.(1974). “Modeling the regulation of Lake Superior under uncertainty of future water supplies.”Water Resour. Res., 10(1), 11–25.
12.
Water Resources Service. (1981). “Project data.” U.S. Dept. of the Interior, Washington, D.C.
13.
Young, R. A.(1995). “Coping with a severe sustained drought on the Colorado River: introduction and overview.”Water Resour. Bull., 31(5), 779–788.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 122 • Issue 6 • November 1996
Pages: 438 - 440
Copyright
Copyright © 1996 American Society of Civil Engineers.
History
Published online: Nov 1, 1996
Published in print: Nov 1996
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.