Assessment of Surface Water Quality Using Principal Component Analysis in the Yamuna River: A Case Study

Present work studies of surface water quality using principal component analysis (PCA). Yamuna river is situated in North India. Its water has important role in irrigation and domestic uses. Yamuna river water is highly polluted from Gautam Budha Nagar to Agra. The reason is being rapid economic development, urbanization, industrialization and agriculture waste and fertilizers. So, water samples were monitored from Gautam Budha Nagar to Agra for three years (2014, 2015 and 2016). Water sample collection has been done on the basis of past research analysis and self-survey. These water quality parameters include pH, temperature, electrical conductivity, dissolved oxygen, turbidity, total dissolved solid, salinity, chloride, acidity, total alkalinity, total hardness, nitrate ions, biochemical oxygen demand, chemical oxygen demand and total coliform. PCA technique has been applied in analysis dataset. Four factors were identified for the data structure explaining of the total variance (83.73%) of the dataset, in which nutrient factor (41.79%), domestic sewage contamination (22.41%), physicochemical variability (11.92%) and wastewater from industrial (7.61%) in total variance. Result clearly shows that PCA technique is useful tool for water pollution resources identification and management. Anthropogenic activities are responsible for deterioration the river water quality. So, its needs to spread the awareness for the pollution status of river water publicly.