Abstract
In recent years fuzzy set theory has emerged as a transcendental tool to deal with environmental engineering application having uncertainty, ambiguity and subjectivity. Analysis of surface water quality plays significant role in environmental impact assessment studies. For qualitative description of surface water quality, number of physical, chemical and biological parameters are taken into consideration, allotted a weightage factor and calculated into an index called water quality index
(WQI). Water quality index uses crisp set to analyse water contaminants and hence deals with standing boundary conditions. This paper illustrates use of fuzzy inference system for analysing physical and chemical parameters to assess surface water quality. A water quality index calculated with fuzzy inference system has been developed and discussed.
Introduction
Determination of status of water quality of a river or any other water sources is highly indeterminate.
The current method of determining water quality index which is in practice utilizes statistical approach and is not precise in most of the time. Nowadays environmental protection and water quality management has become an important issue in public policies throughout the world. Moreover, government is concerned about the quality of their environmental resources because of the complexity in water quality data sets. Many countries have introduced a scheme for river water quality monitoring and assessment, examining separate stretches of fresh water. Water Quality Index (WQI) is computed for classification of water wherein the integration of parametric information on water quality data and the expert’s knowledge base on their importance and weights are considered.
Considerable uncertainties are involved in the process of defining water quality for designated uses.
It is necessary to have a