Water quality assessment and prediction modelling of Nambiyar river basin, Tamil Nadu, India

Abstract

The management of river water quality is a major environmental challenge. Monitoring different sources of pollutant load contribution to the river basin is quite a difficult, laborious and expensive process which sometimes leads to analytical errors also. The main objective of the present study is to develop a model to assess and predict the water quality changes of the Nambiyar River Basin, in Tamil Nadu, India, using Neural Network and GIS techniques, and to compare the results through the statistical method. Hydro-geochemistry of groundwater in Nambiyar River basin was used to assess the quality of groundwater for determining its suitability for drinking and agricultural purposes. The cations such as Ca, Mg, Na, K and anions like HCO3, CO3, Cl, SO4 and NO3 were analysed in the laboratory. General statistical analyses of the bio-physico and chemical parameters of the basin s surface water quality have been carried out to find the interrelationships among them, which constitute the first phase of the present study. By this study it is found that a strong correlation exists between SO4 and COD. Maximum correlation is obtained between SO4 and COD (r = 0.9532). Regression equation has been derived for surface water quality parameters corresponding to the correlation coefficient value of more than 0.8. Similarly, a systematic correlation and regression study on ground water quality, in the second phase of work, shows the linear relationship among the different water quality parameters. High correlation coefficients have been observed from TDS with Cl, Ca, SO4 and Na; from Cl with Ca; and from SO4 with Ca. The regression equations can be used for the rapid monitoring of the water quality of the basin. In the third phase of the study, water quality indices of the basin have been determined. The physico-chemical parameters such as pH, DO, TDS, NO3, BOD, COD, Total Alkalinity, Total hardness, Ca, Mg, Cl, SO4 and F of the basin have been taken into account for deciding the quality characteristics of the basin.