Evaluation of geochemical data of Yamuna River using WQI and multivariate statistical analyses: a case study. Issue 2 (3rd April 2019) - Kumar, Balwant; Singh, Umesh Kumar; Ojha, Sri Narayan
ABSTRACT: This study is focused on the character and classification of Yamuna River water quality using secondary data. The application of water quality index (WQI), cluster analysis (CA), principal component analysis (PCA), multiple regression analysis (MRA) and discriminant analysis (DA) was investigated to assess the water quality status and evaluate the critical parameters with identification of most prominent polluted sites. During investigation of WQI, 67% of the total monitoring area falls under bad and very bad categories. CA classified 19 monitoring sites into 3 groups based on the properties of water quality. PCA obtained two principle components which suggest that domestic, industrial, municipal effluent and agricultural runoff are important pollution sources of Yamuna River. DA result indicates pH, COD, DO as most significant parameters, and are responsible for discriminating the groups. MRA obtained that TC, FC, NH4, COD, BOD and pH are dependable factors for controlling the river water quality. The trend line of Yamuna River water quality through simple regression indicated that the trend values of COD, BOD, NH4, TKN, TC and FC are continuously increasing in the river system while the negative trend line of DO suggested that the water quality of Yamuna could be under hypoxic condition in near future.