Statistical Approach in Assessing Dynamic Variations of Estuarine Water Quality of Dhamra,Bay of Bengal

Multivariate statistical techniques such as cluster analysis (CA), principal component analysis (PCA) and factor analysis (FA) were applied for the evaluation of dynamic variations in water quality of Dhamra estuarine region from 2009 to 2010. The concentrations of salinity, conductivity, turbidity and inorganic nutrients varied significantly in different seasons from estuarine region to deep marine region. The intensity of microbial activities and the influx of organic sewage are reflected in high BOD content. A strong positive correlation of salinity with conductance, chlorophyll-a with total phytoplankton, phytoplankton with inorganic phosphate and total viable count (TVC) with temperature have been established. Further, TVC was having negative correlation with salinity. Hierarchical cluster analysis, grouping 14 parameters into two significant clusters based on their similarity and their interrelationship identified phosphate as the major nutritional requirement for phytoplankton growth. The factor loading further indicates the influence of salinity gradient and nutrient availability for the distribution plankton. FA generates six latent factors explaining 82.67% of the total variance illustrating various interrelationships of biotic and abiotic factors.