Abstract
One of the major goals of water resource planning today is the development of a stochastic model for water resource system design. This study lays the groundwork for the development of such a procedure. An optimal planning procedure utilizing analytical techniques in conjunction with streamflow simulation models has been used in this research for the design of water resource systems which account for the stochastic variability of streamflow. Four different stochastic hydrologic models, two existing and two developed in this dissertation, were compared in the actual generation of synthetic data. The existing simulation routines are those developed by Young and Pisano and by L. R. Beard and currently in use by the Federal Water Pollution Control Administration (FWPCA) and the Corps of Engineers (COE). The models developed in this research are: (1) the extension of the FWCPA hydrologic data synthesis model based on standardized residuals to incorporate the lag-two serial correlations, and (2) a monthly dependence model. Critical examination and statistical evaluation of the relative advantages and disadvantages of all four streamflow synthesis models are also included in this dissertation. After the generation of data by all four models, two dynamic programming algorithms capable of eliminating some of the difficulties associated with intermediate stage inputs were used in sequence for the design of a reservoir system. These techniques were used, first, to determine the maximum storage requirements under different critical flow conditions, and second, to determine the optimum size of the physical structures to be built by making a compromise between the capital and OMR costs of the reservoirs and the shortage cost. From the results of the optimization phase, it was concluded that under simplifying assumptions embodied in this research, it did not make much difference which model was used for the generation of synthetic data..
Sharif, Mohammad Nawaz (1971). Stochastic planning procedure for water resource system design. Doctoral dissertation, Texas A&M University. Texas A&M University. Libraries. Available electronically from
https : / /hdl .handle .net /1969 .1 /DISSERTATIONS -181109.