Application of multivariate statistical techniques such as one way and two way ANOVA, principal component analysis and cluster analysis are very common and appropriate in water quality analysis with large data set. Integration of geostatistical interpolation techniques such as kriging & IDW with PCA can be useful to reveal spatial distribution of water quality parameters variation in your study area, and estimate concentrations in un-sampled locations. About water quality index; I suggest you this book: "Water Quality Indices" by Tasneem Abbasi and S.A. Abbasi.

I will check it out. Thanks a lot Narany.

dear Tepe,

I had used the Canadian Council of Ministry Environment Water Quality Index.

Regards