Spatiotemporal evaluation of trace elements in river water using multivariate methods

The multivariate statistical methods (cluster analysis and discriminant analysis DA]) are used to evaluate the quality of water spatiotemporally in the Brahmani River basin. A total of 15 water quality indicators (pH, Chloramines, Sodium, Sulfate, Phosphate, Potassium, Boron, Fluoride, Cadmium, Copper, Lead, Nickel, Zinc, Iron, and Total Chromium) are collected for 13 years in two seasons (the dry and the wet season) from nine sampling stations. These stations are grouped into four clusters (Considerable Co], Low Pollution LP], Moderate Pollution MP], and Extreme Pollution (EP]) by hierarchical agglomerative cluster analysis based on the similarities of water quality characteristics. The nine important influencing discriminating water quality indicators are extracted by stepwise method of temporal DA,where as eight important influencing indicators for dry season and eight indicators (Potassium, Phosphate, Fluoride, Copper, Lead, Nickel, Iron, and Total Chromium) for wet season are found out by the spatial DA. The pollution status in the river basin was observed from overall trend in (Considerable) Co to (Extreme Pollution) EP regions. The study could be very useful in prioritizing the important sites for water resources and pollution management.