Identification of Water Quality By Principal Component and Spatial Cluster Analysis Methods in Muttukadu Coastal Regions, Chennai of Southern India

Abstract

Multivariate statistical analysis such as principal component analysis and cluster analysis were employed to evaluate the water quality status for three monitoring stations in Muttukadu coastal regions. The present study was carried out to determine the sediment characteristics and physicochernical parameters of water of Muttukadu coast of southern India. Salinity, pH, dissolved oxygen, fecal coliform, sand and slit indicated correlation at p <0. 01. Seasonal variations of different water quality parameters investigated were as follows- salinity(16-35 psu), pH(7. 2-8. 4), dissolved oxygen(3. 345-6. 765 mg/ l), water temperature(25. 75-32 ~C), fecal coliform(170-3650 cfu/100ml), ssc(20. 7-143. 5 mg/ l), sand(87-99. 385 %), slit(0. 125-12. 385 %), cla y(0. 035-1. 37 % ). Principal component analysis identified the tern poral and spatial characteristics of coastal stations and showed that the water quality status was worse in stations 2 and 3 in the Muttukadu coastal regions. Cluster analysis grouped the four seasons (pre monsoon, monsoon, post monsoon, summer) and the sampling sites in to three groups.