A fuzzy industrial water quality index: case study of Zayandehrud river system

Abstract

Fuzzy logic provides an effective tool for classifying water quality in a river system based on limited observations. In this study, a fuzzy index (range of 0-100) is proposed for evaluation of water quality for industrial uses. Fuzzy inference system makes it possible to combine the certainty levels for the acceptability of water based on a prescribed limit of various regulatory bodies' quality classes and expert opinions. Application of the proposed fuzzy index is demonstrated with a case study for the Zayandehrud River, located in Isfahan province, Iran. A data set on nine sampling stations along this river was used. Water quality was evaluated for industrial purposes by means of six parameters (pH, TH, TA, SO42-, Cl- and TDS). The results showed that during the study period, the water quality of the river was suitable for some industrial purposes except in Varzaneh. In this station, Zayandehrud receives wastewater of some small industries and agricultural lands. The water quality degraded from Pole Kalleh (index value of 90) to Varzaneh (index value of 15) in the winter months. In the summer months, the index was variable for these two stations. The proposed approach exhibits a convenient tool for continuous monitoring of river water for industrial purposes