Abstract
This paper deals with bicriterion (irrigation & water quality) weekly operation of a water resource system during dry periods. Two ways of handling the problem are proposed and compared for a real case study:
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a stochastic dynamic programming model using system analysis language;
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a more “synthetic” model using direct hydrological and water resources concepts.
Numerical results based on historical series are derived in both cases The insight provided by the water resources engineering approach is pointed out and guidelines for model choice are suggested.
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Bibliography
Askew J.A. (1974), Optimum reservoir operating policies and the imposition of a reliability constraint. Water Resources Research 10, 1, p.51–56.
Bellman R.E. (1957), Dynamic programming. Princeton University Press,.
Bodo B.A., Unny T.E. (1990), Modeles linéaires stochastiques théoriques pour la reponse des petits bassins. Revue des sciences de ľeau 3, p.151–182.
Buras N. (1972), Scientific allocation of water resources. Elsevier, N. Y.
Colleter P., Delebecque F., Falgarone F. and Quadrat J.P. (1978), Application du controle stochastique a la gestion des moyens de production d’energie en nouvelle-Caledonie. “E.D.F. Boulletin de la direction des etudes et rechereche, Serie C. Mathematiques- Informatique” (E.D.F.), p. 1–28.
Dodu J.C., Goursat M., Hertz A., Quadrat J.P. and Viot M. (1981), Methodes de gradient stochastique pour l’optimisation des investissements dans un reseau electrique, E.D.F. 2, p.133–164.
Fang Z.X., Voron B., Bocquillon C. (1989), Programmation dynamique: Application a la gestion d’une retenue pour l’irrigation. Hydrolo. Sci. J. 34(4), p.415–424.
Hashimoto T., Stedinger J.R. and Loucks D.P. (1982), Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation. Water resources research 18, 1, p. 14–20.
Houghtalen R.J. and Loftis J.C. (1988), Irrigation water delivery system operation via aggregate state dynamic programming. Water resources bulletin 24, 2, p.427–434.
Klemes V. (1977), Discrete representation of storage for stochastic reservoir optimization. Water resources research 13, 1, p.149–158.
Klemes V. (1978), The unreliability of reliability estimates of storage reservoir performance based on short streamflow records. In “Water resource management, Water resources publications, Fort Collins, Colorado”, p. 193–205.
Krzysztofowicz R. (1982), Utility criterion for water supply: quantifying value of water and risk attitude. In “Decision-Making for hydrosystems-Forecasting and operation” (ED: T.Unny), 43–62.
Masse P. (1959), Le choix des investissements. Dunod.
Mergos G.J. (1987), Evaluation of irrigation projects under uncertainty: A symmetric quadratic programming approach. Water resources management 1, p.45–56.
Simonovic S.P. and Orlob T.G. (1984), Risk-reliability programming for optimal water quality control. Water resources research 20, 6, p.639–646.
Tapiero C.S. (1988), Applied stochastic models & control in management. In “Advanced series in management”. V12. North–Holland.
Turgeon A. (1981), Optimal operation of multireservoir power systems with stochastic inflows. Water resources research 16, 2, p.275–283.
Yakowitz S. (1982), Dynamic programming applications in water resources. Water resources research 18, 4, p.673–696.
Yeh W.W.G. (1985), Reservoir management and operations models: S state–of—the–art review. Water resources research 21, 12, p.1797–1818.
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© 1991 Springer-Verlag Berlin Heidelberg
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Parent, E., Lebdi, F., Hurand, P. (1991). Stochastic Modeling of a Water Resource System: Analytical Techniques Versus Synthetic Approaches. In: Ganoulis, J. (eds) Water Resources Engineering Risk Assessment. NATO ASI Series, vol 29. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-76971-9_22
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DOI: https://doi.org/10.1007/978-3-642-76971-9_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-76973-3
Online ISBN: 978-3-642-76971-9
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