Dynamic programming is applied to the general class of water‐resources problems to permit optimum development with respect to all possible benefits. Since physical alternatives which are to be compared must be expressed in common units of value, the equations are written in terms of dollar benefits, cost, etc. The relationship of the physical quantities involved should be kept in mind throughout, since in hydrologic planning these physical quantities must be reconciled. In water‐resources development the purpose of the hydrologist or hydraulic engineer is to determine the manner in which the natural stream systems can be modified to best serve all the competing demands for water, power, protection, etc. In this paper dynamic programming is applied to the optimizing process to permit determination of the ‘optimum policy’ over a very broad range of alternatives, a determination not remotely possible by conventional analysis.

Abstract. The management of storage facilities (reservoirs, lakes, and ponds) is an important element of the utilization of a surface water resources system. Dynamic programming (DP) techniques have been used extensively in the analysis and resolution of reservoir systems operation. A major drawback of DP for a multireservoir system is the "curse of dimensionality." To overcome this problem, this study developed a nonlinear programming (NLP) solution scheme which also integrated the objectives of several stakeholders, objectives which were noncommensurate. The NLP model employed a time series model to generate synthetic inflows into the storage facilities in order to simulate future operations of the system. Two sets of simulations were run, and a statistical test was used to terminate them. The expected values of the decision variables were tabulated and plotted, as well as their standard deviations and probability distributions. The model allows decision makers to adjust operation targets for different alternative operation scenarios.

No abstract

No abstract

No abstract