The world today is facing the problem of ever-increasing level of pollution of water bodies. The seriousness of this problem calls for specialized attention to predict future trend. Data mining is the most popular technique for handling huge amount of geo-spatial data. The variety and size of information to be processed for proper trend analysis towards water quality management makes the use of data mining concepts all the more relevant. This paper summarizes the on-going researches involving data mining applications in this area. The applications have been observed to use the techniques of ANN, Fuzzy, or GIS modeling for featurewise classification of water pollutants. The parameters need to be clustered depending upon their area of application. The respective advantages of each model in classifying the parameters have been identified. The authors have arrived at a set of parameters best suited for analyzing the effect of pollutants on the river Churni, an effluent of the river Bhagirathi. Copyright 2012 ACM.