DIKUL - logo
E-viri
Celotno besedilo
Recenzirano
  • Multivariate statistical an...
    Singh, Chander Kumar; Kumar, Anand; Shashtri, Satyanarayan; Kumar, Alok; Kumar, Pankaj; Mallick, Javed

    Journal of geochemical exploration, April 2017, 2017-04-00, Letnik: 175
    Journal Article

    Groundwater is the most important source of drinking waters supply in the National Capital Territory (NCT) of, New Delhi, India. A diverse geological and topographical set up along with the fast growing population and anthropogenic activities has created a need of groundwater quality assurance for drinking and domestic water supply in the region. The major hydro-geochemical process and impacts of anthropogenic activities can be deciphered using multivariate statistical analysis, conventional graphical plots and saturation indices. Groundwater samples were collected from 170 locations spread over entire region and were analysed for a total of 12 water quality physico-chemical parameters. It is observed that the groundwater is neutral to alkaline in nature with electrical conductivity (EC) value ranging from 460 to 8980μs/cm. Chemometric analysis was performed along with geochemical modeling. The 3 clusters obtained through HCA were clearly differentiated based on their chemical characteristics i.e. concentration of major ions. High concentration of nitrate (NO3−) and fluoride (F−) exceeding WHO standards was found in 29% and 27% of the water samples respectively. It is observed that semi-arid climatic conditions along with rock-water interaction, weathering and ion-exchange are the major factors controlling groundwater quality in the region. Oversaturation of fluorite and gypsum has resulted into high concentration of F− in study area. It is found that the results from statistical and geochemical models compliment the findings using conventional plots and are able to decipher comprehensive geochemistry of groundwater in the region. •PCA, HCA and DA performed of 170 groundwater samples spread in entire region.•PCA generated 4 principal components explaining 76% of variance in the data.•3 cluster were obtained on performing HCA based on electrical conductivity values.•The values of Wilk's Lambda and Chi square indicates DA is statistically significant.•Fluoride and nitrate contamination found in 27% and 29% of samples respectively.