Chance Constrained Model for River Water Quality Management

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Abstract
A chance constrained model is proposed, in which the main stream, tributaries, and storm water are considered as random variables to determine the most economical level of wastewater treatment at each discharge city or industry along a river basin. The model considers the risk of violation of the stream‐water quality explicitly and therefore, provides a more rational approach than the traditional design value or safety factor approach, e.g., the lowest 7‐day moving average of daily flow rate over a 10‐yr period. The model is shown to be equivalent to a linearly constrained program, thus enabling the application of simple solution techniques.

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