Assessment of water quality using principal component analysis--a case study of the Mangalore coastal region, India

Miscellanies of statistical approaches were employed to illustrate the real picture of quality environmental variables observed in a nationalized monitoring programme. The interpretation and evaluation of the quality data, that was observed, were made very easier by utilizing the wide scope of spectacular statistical software, SPSS 11.0 through the Principal Component Analysis (PCA). The whole data for the study period, which was classified in to three distinct seasons, has been factorized using the PCA. The main and ultimate aim of this study is to reveal and categorize the key parameters of the Mangalore coast for the pollution sources to the ecosystem and their inputs can be perceived if there any point sources of pollution exist. Box plots were derived from the PCA data and were graphically represented. The variance was observed to be above 75% from the original data for all seasons. The major parameter affecting the ecological health of the coastal water was nitrate-nitrogen brought by the rivers in this region, which finally ends up in the estuary. Water quality data observed in the Mangalore coast during the three seasons, viz. pre-monsoon, monsoon and post-monsoon (February to October 2006), has been used and endeavors were made to determine and quantify the factors that caused fluctuations in the hydrology of this region.