Fuzzy-Based Regional Water Quality Index for Surface Water Quality Assessment

Abstract

Evaluation of the water quality index is highly complex and needs competent models to assess at global and regional scales. A fuzzy-based inference system (FIS) provides an effective tool for solving this type of complex problems. This study presents the development of a Mamdani-type fuzzy-based regional water quality index (FRWQI) consisting of 10 water quality parameters such as dissolved oxygen (DO), fecal coliforms (FC), biological oxygen demand (BOD), pH, nitrogen, suspended solids (SS), alkalinity, turbidity, chemical oxygen demand (COD), and electrical conductivity (EC). It can be used for the evaluation of the water quality index of various river basins across the world. The assessment of surface water quality was proposed with three classes using classifications from six countries in various geographic regions. The FRWQI is comparable to water quality models used in India, Malaysia, and the United States, despite its varied geographic origin, and can help in the self-assessment of regional water quality on a global scale.