Water quality assessment in agricultural drains using PCA techniques

In this study, Principal component analysis was carried out in order to interpret a large data set that is obtained during water quality analysis of agriculture drainage water collected at different sites in Guntur district. Principal component analysis is used to extract the parameters which are most important in assessing water quality variation. In the present study, five principal factors were identified as responsible for the data structure explaining 80.165% of the total variance of the data set. From this study, it was observed that most of the pollution is due to salts and nutrients present in the water (represents 52% of the total variability in the dataset) and pollution due to organic load is less.