V. Vidya and G. Prasad
Abstract
Cluster analysis and PCA were applied for the evaluation of water quality data of vembanad wetland adjacent to the seafood processing facilities. The water samples were collected from ten different stations for a period of two years (2010-2012) on a monthly basis. The stations, S1-S9 were closely associated with the seafood processing discharge outlets and the S10, was kept as a reference site, which is free from the seafood processing discharge. The physico-chemical parameters (atmospheric and water temperature, TDS, pH, EC, salinity, DO, BOD, alkalinity, COD, hardness and nutrients such as nitrate, phosphate, ammonia and silica) were studied. Hierarchical cluster analysis was performed and dendrogram was generated, which grouped all 10 sampling sites into three statistically significant clusters. Thus, the water quality around the site may be categorized as relatively less polluted, moderately polluted and highly polluted. PCA could extract 6 principal components and they account for 65.79% of the total variance of the original data. The parameters that contributed to the first component include alkalinity, free CO2, BOD, COD and nutrients. The organic pollution and dumping of waste from the seafood industry altered the water quality significantly. This study illustrates the benefit of multivariate statistical techniques for analyzing and interpretation of complex data sets, and to plan for future studies.