Fuzzy Waste Load Allocation Model: Application to a Case Study

Abstract

A fuzzy optimization model, developed earlier to address uncertainty due to imprecision in management goals in river water quality management problems is applied to a case study in this paper by addressing uncertainty due to randomness implicitly through Monte Carlo simulations. Municipal and industrial effluents, characterized by their Biochemical Oxygen Demand (BOD) loads are considered as point sources of pollution and the Dissolved Oxygen (DO) level at specified checkpoints in the river stretch is taken as the single water quality indicator. Conflicting goals related to water quality and fraction removal levels are expressed as fuzzy sets with appropriate membership functions in the model. The fuzzy optimization model is solved for a number of simulated sets of inputs to obtain optimal solutions, thus generating a large set of optimal objective function values and associated decisions. This information is used to obtain waste-load allocation decisions for a specified level of reliability.