Bayesian Inferencing Applied to Real‐Time Reservoir Operations
Publication: Journal of Water Resources Planning and Management
Volume 116, Issue 1
Abstract
A significant amount of research during the past few years has focused on the application of expert systems technology to problems of water resources management. While these investigations have led to speculation as to the benefits of intelligent reasoning applied to real‐time reservoir operation, working systems are nonexistent or in the preliminary stages of development and testing. This research presents a novel perspective on the use of knowledge‐based inferencing techniques applied to real‐time reservoir operation. A hybrid reasoning structure using both Bayesian and rules‐based inferencing is presented. Rules are used to achieve a real‐time simulation that is comparable to other rule‐based systems reflecting expert operations as proposed in the literature. The Bayesian mechanism then provides a judgment about the quality of recommended releases based on prior information and present conditions. An additional feature of this system is its learning capabilities that can be used for further refinement of system recommendations.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
Akhound, K., and Karamouz, M. (1988). “A rule based expert system for reservoir operation.” Proc., ASCE Nat. Specialty Conf. on Critical Water Issues and Computer Applications, ASCE, 72–76.
2.
Engman, E. T., Rango, A., and Martinec, J. (1986). “An expert system for snowmelt runoff modeling and forecasting.” Water Forum '86, ASCE, 174–180.
3.
Fayegh, D., and Russell, S. O. (1986). “An expert system for flood estimation.” Expert systems in civil engineering, ASCE, New York, N.Y., 174–181.
4.
Guariso, G., et al. (1985). “Decision support system for water management: The Lake Como case study.” Eur. J. Oper. Res., 21(3), 295–306.
5.
Hammond, K. R. “Toward a unified approach to the study of expert judgement.” Expert judgement and expert systems, Springer‐Verlag, New York, N.Y., 1–16.
6.
Houck, M. H. (1985). “Designing an expert system for real‐time reservoir system operation.” Civ. Engrg. Syst., 2, Mar., 30–37.
7.
Johnson, L. (1986). “Water resource management decision support systems.” J. Water Resour. Plng Mgmt., ASCE, 112, 308–325.
8.
Kangari, R., et al. (1986). “Expert systems in reservoir management and planning.” Water Forum '86, ASCE, 1, 187–194.
9.
Knowledge base author's manual, (1987). Software Architecture & Engineering, Inc., Washington, D.C.
10.
Krzysztofowicz, R. (1983). “Why should a forecaster and a decision maker use Bayes theorem?.” Water Resour. Res., 19, Apr., 327–336.
11.
Labadie, J. W., and Sullivan, C. H. (1986). “Computerized decision support systems for water managers.” J. Water Resour. Plng. Mgmt., 112(3), 299–307.
12.
Mathew, S., and Cheeseman, P. (1987). “Bayesian prediction for artificial intelligence.” Uncertainty in artificial intelligence (Proc. 3rd AAAI Workshop on Uncertainty in Artificial Intelligence), Univ. of Washington, 61–69.
13.
Morris, H. M., and Wiggert, J. M. (1972). Applied hydraulics in engineering. John Wiley and Sons, Inc., New York, N.Y.
14.
Newell, A., and Simon, H. A. (1972). Human problem solving. Prentice‐Hall, Englewood Cliffs, N.J.
15.
Unver, O., Mays, L., and Lansey, K. (1987). “Real time flood management model for Highland Lake system.” J. Water Resour. Plng. Mgmt., ASCE, 113(5), 620–638.
16.
Wunderlich, W. (1985). “Computer‐aided real‐time reservoir operation methods.” Comput. Appl. Water Resour., (Proc. of the Specialty Conf., Water Resour. Plng. and Mgmt. Div.), H.C. Torno, ed., ASCE, 649–657.
17.
Yazicigil, H., Houck, M. H., and Toebes, G. H. (1983). “Daily operation of a complex reservoir system.” Water Resour. Res., 19(1), 1–13.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 116 • Issue 1 • January 1990
Pages: 38 - 51
Copyright
Copyright © 1990 ASCE.
History
Published online: Jan 1, 1990
Published in print: Jan 1990
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.