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Interpretation of Ground and Surface Water Quality using Principal Component Analysis in Gohpur Sub-Division of Sonitpur District, Assam, India

Pranab Sabhapandit, Prasanta Saikia and Abani Kr. Mishra

Water is necessary for both; sustainable human development and healthy functioning of the planet’s eco-system. The modern civilization, industrialization, urbanization and increase in population have led fast degradation of water resources. According to W. H. O., about 80% of all the diseases of human beings are caused by water. Since it is directly related with human health, it is necessary to bring awareness among the present and future generation about consequences of water pollution. A total of 34 numbers of samples from different sources such as dug wells, bore wells, hand pumps and ponds, where no information is available, were collected during year 2008. Samples were analyzed for different physicochemical parameters like chloride, sulphate, nitrate, sodium, potassium, calcium, magnesium and iron using standard methods. The results indicated that chloride and nitrate concentration in all the sources were within the permissible limit and ponds contain higher amount of it than the other sources. The concentration of sulphate, sodium in dug well and bore well were very high and the concentration of sulphate, calcium were within the permissible limit. In case of calcium, its concentration in ponds was higher than the other sources. The iron concentration in all the sources exceeded the W.H.O. value and dug well and bore well contain higher amount of it. Magnesium content were greater than potassium and less than sodium in dug well and bore well, but in ponds, its concentration were greater than the other sources. In these investigations, the results indicate that TDS, EC, DO were found very high. The interpretation and evaluation, quality data, that was observed, were made very easier by utilizing the wide scope of spectacular statistical software, SPSS 17 through their principal component analysis. The main and ultimate aim of this study is to reveal and categorize the key parameters of the Gohpur sub-division for the pollution sources to ecosystem so that their inputs can be perceived. Box plots were derived from the PCA data and were graphically represented. The variance was observed to be above 67.28 % from the original data. Overall analysis reflected that 11 numbers of samples are fit for drinking purpose with respect to the parameters studied.