In order to handle the probabilistic nature of treated waste effluent characteristics, the reliability associated with a basin‐wide quality management goal has been included in the modeling process. Meanwhile, the quantitative and qualitative variations of the irrigation return flows and the urban runoff also exhibit a probabilistic nature in terms of both temporal and spatial measurements. Computer simulation has been utilized in analyzing the reliability and sensitivity of a river basin quality management. In this paper, a simulation‐optimization scheme for the determination of policies in regional water quality management was developed subject to specific water quality standards. Stochastic quadratic programming techniques have been used in the optimization analysis. A series of simulation models describing the statistical water quality control phenomena was developed. Meanwhile, a simulation analysis for the description of probabilistic nature of the stream quality was developed for the control strategies of the return flows in the regional management system. As an illustration of the applicability of this water quality control approach, the major wastewater treatment facilities in the San Antonio River Basin were analyzed. The sensitivity analysis was conducted to assess the most satisfying strategies for a regional water quality management system subject to probabilistic standards.

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The San Antonio River Walk is considered a unique tourist attraction as well as an urban rejuvenation catalyst for San Antonio, Texas. This utilization of the mile‐long horseshoe bend in the downtown area of San Antonio is as successful and imaginative as can be found in the United States. Testimony is very strong from San Antonio voters and outside visitors of the great social and economic value of the River Walk. This overwhelming success has led to plans for expansion of the present River Walk. The River Walk expansion decision should not be evaluated merely on a benefit‐cost ratio. It has become the recommendation of the Water Resources Council that intangible attributes such as recreational values and social impacts should be considered as well as tangible attributes such as cost. This prevailing attitude has highlighted the application of decision analysis techniques with multiattribute utility ratings. Decision analysis is a systematic solution procedure which can be used to crystallize a complicated decision problem into manageable subproblems by ranking the decision alternatives in accordance with cardinal utility values attached to their consequences. Recent advances in multiattribute utility theory allow a decision maker to weigh utility assessment over tangible and intangible attributes according to their relative importance. This insures that the intangible attributes will receive due consideration in the final decision‐making.