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Optimal Wastewater Loading under Conflicting Goals and Technology Limitations in a Riverine System

This paper investigates a novel simulation‐optimization (S‐O) framework for identifying optimal treatment levels and treatment processes for multiple wastewater dischargers to rivers. A commonly used water quality simulation model, Qual2K, was linked to a Genetic Algorithm optimization model for exploration of relevant fuzzy objective‐function formulations for addressing imprecision and conflicting goals of pollution control agencies and various dischargers. Results showed a dynamic flow dependence of optimal wastewater loading with good convergence to near global optimum. Explicit considerations of real‐world technological limitations, which were developed here in a new S‐O framework, led to better compromise solutions between conflicting goals than those identified within traditional S‐O frameworks. The newly developed framework, in addition to being more technologically realistic, is also less complicated and converges on solutions more rapidly than traditional frameworks. This technique marks a significant step forward for development of holistic, riverscape‐based approaches that balance the conflicting needs of the stakeholders.