Markov Models for Flow Regulation

by Moshe Gablinger, (A.M.ASCE), Grad. Student; School of Civ. Engrg., Cornell Univ., Ithaca, NY,
Daniel P. Loucks, (A.M.ASCE), Asst. Prof. of Civ. Engrg.; Cornell Univ., Ithaca, NY,

Serial Information: Journal of the Hydraulics Division, 1970, Vol. 96, Issue 1, Pg. 165-181

Document Type: Journal Paper


The problem of defining alternative operating policies for a single multipurpose reservoir was examined through the use of several pairs of discrete stochastic linear- and dynamic-programming models. The net flows into the reservoir were assumed to be serially correlated, their probabilistic sequence defined by first-order Markov chains. Each linear programming model was shown to correspond to a dynamic programming model. The solutions and computational efficiencies of each of the models were compared using a simplified numerical example based on an actual reservoir operating problem. Although the policies obtained from each pair of corresponding models were identical, the time required to solve the dynamic programming models was less than that required for the linear programming models.

Subject Headings: Dynamic models | Computer programming | Hydrologic models | Reservoirs | Markov process | Regulated flow | Computer models | Numerical models

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