Skip to main content
SpringerLink
Log in

Chemometric characterization of river water quality

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Various industrial facilities in the city of Varanasi discharge their effluent mixed with municipal sewage into the River Ganges at different discharge points. In this study, chemometric tools such as cluster analysis and box–whisker plots were applied to interpret data obtained during examination of River Ganges water quality. Specifically, we investigated the temperature (T), pH, total alkalinity, total acidity, electrical conductivity (EC), biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), nitrate nitrogen (N), phosphate (PO 2−4 ), copper (Cu), cadmium (Cd), chromium (Cr), nickel (Ni), iron (Fe), lead (Pb), and zinc (Zn) in water samples collected from six sampling stations. Hierarchical agglomerative cluster analysis was conducted using Ward’s method. Proximity distance between EC and Cr was the smallest revealing a relationship between these parameters, which was confirmed by Pearson’s correlation. Based on proximity distances, EC, Cr, Ni, Fe, N, COD, temperature, BOD, and total acidity comprised one group; Zn, Pb, Cd, total alkalinity, Cu, and phosphate (PO 2−4 ) were in another group; and DO and pH formed a separate group. These groups were confirmed by Pearson’s correlation (r) values that indicated significant and positive correlation between variables in the same group. Box–whisker plots revealed that as we go downstream, the pollutant concentration increases and maximum at the downstream station Raj Ghat and minimum at the upstream station Samane Ghat. Seasonal variations in water quality parameters signified that total alkalinity, total acidity, DO, BOD, COD, N, phosphate (PO 2−4 ), Cu, Cd, Cr, Ni, Fe, Pb, and Zn were the highest in summer (March–June) and the lowest during monsoon season (July–October). Temperature was the highest in summer and the lowest in winter (November–February). DO was the highest in winter and the lowest in summer season. pH was observed to be the highest in monsoon and the lowest in summer season.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig.1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • APHA, AWWA, WEF. (2005). Standard methods for the examination of water and wastewater (21st ed.). USA: American Public Health Association/American Water works Association/Water Environment Federation.

    Google Scholar 

  • Chen, G. N. (1993). Assessment of environmental water with fuzzy cluster analysis and fuzzy recognition. Analytica Chimica Acta, 271, 115–124.

    Article  Google Scholar 

  • Cieszynska, M., Wesolowski, M., Bartoszewicz, M., Michalska, M., & Nowacki, J. (2012). Application of physicochemical data for water-quality assessment of watercourses in the Gdansk municipality (South Baltic coast). Environmental Monitoring and Assessment, 184, 2017–2029. doi:10.1007/s10661-011-2096-5.

    Article  CAS  Google Scholar 

  • Deming, S. N., Michotte, Y., Massart, D. L., Kaufman, L., & Vandeginste, B. G. M. (1988). Chemometrics: a textbook. Amsterdam: Elsevier.

    Google Scholar 

  • Giridharan, L., Venugopal, T., & Jayaprakash, M. (2009). Assessment of water quality using chemometric tools: a case study of river Cooum, South India. Archives of Environmental Contamination and Toxicology, 56, 654–669.

    Article  CAS  Google Scholar 

  • Hill, T., & Lewicki, P. (2007). Statistics: methods and applications: a comprehensive reference for science, industry and data mining. Tulsa: StatSoft.

    Google Scholar 

  • Johnson, R. A., & Wichern, D. W. (2007). Applied multivariate statistical analysis (6th ed.). USA: Pearson Prentice Hall International.

    Google Scholar 

  • Kar, D., Saur, P., Mandal, S. K., Saha, T., & Kole, R. K. (2008). Assessment of heavy metal pollution in surface water. International journal of Environmental Science and Technology, 5(1), 119–124.

    CAS  Google Scholar 

  • Massart, D. L., & Kaufman, L. (1983). The interpretation of analytical chemical data by the use of cluster analysis. New York: Wiley.

    Google Scholar 

  • Mishra, A., Mukherjee, A., & Tripathi, B. D. (2009). Seasonal and temporal variations in physico-chemical and bacteriological characteristics of River Ganga in Varanasi. International Journal of Environmental Research, 3, 395–402.

    CAS  Google Scholar 

  • Otto, M. (2007). Chemometrics: statistics and computer application in analytical chemistry (2nd ed.). Germany: Wiley.

    Google Scholar 

  • Singh, K. P., Malik, A., Mohan, D., & Sinha, S. (2004). Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomati River (India)—a case study. Water Research, 38, 3980–3992.

    Article  CAS  Google Scholar 

  • Singh, K. P., Malik, A., & Sinha, S. (2005). Water quality assessment and apportionment of pollution sources of Gomti River (India) using multivariate statistical techniques—a case study. Analytica Chimica Acta, 538, 355–374.

    Article  CAS  Google Scholar 

  • Tripathi, B. D., Sikandar, M., & Shukla, S. C. (1991). Physicochemical characterization of city sewage discharged into river Ganga at Varanasi, India. Environment International, 17, 469–478.

    Article  CAS  Google Scholar 

  • Vega, M., Pardo, R., Barrado, E., & Deban, L. (1998). Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis. Water Research, 32, 3581–3592.

    Article  CAS  Google Scholar 

  • Willet, P. (1987). Similarity and clustering in chemical information systems. New York: Wiley.

    Google Scholar 

  • Xu, H., Yang, L. Z., Zhao, G. M., Jiao, J. G., Yin, S. X., & Liu, Z. P. (2009). Anthropogenic impact on surface water quality in Taihu lake region, China. Pedosphere, 19, 765–778.

    Article  CAS  Google Scholar 

  • Zhou, F., Liu, Y., & Guo, H. (2007). Application of multivariate statistical methods to the water quality assessment of the watercourses in Northwestern New Territories, Hong Kong. Environmental Monitoring and Assessment, 132, 1–13.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The authors are thankful to the University Grants Commission for financial support, the head (Prof. B.R. Chaudhray) of the Department of Botany for providing laboratory facilities, and the Institute of Agriculture and Soil Sciences for conducting heavy metal analysis using AAS.

Author information

Authors and Affiliations

  1. Pollution Ecology Research Laboratory, Banaras Hindu University, Varanasi, 221005, India

    Menka Kumari, Smriti Tripathi & Vinita Pathak

  2. Centre for Environmental Science and Technology, Banaras Hindu University, Varanasi, 221005, India

    B. D. Tripathi

Authors
  1. Menka Kumari
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Smriti Tripathi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vinita Pathak
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. B. D. Tripathi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to B. D. Tripathi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kumari, M., Tripathi, S., Pathak, V. et al. Chemometric characterization of river water quality. Environ Monit Assess 185, 3081–3092 (2013). https://doi.org/10.1007/s10661-012-2774-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10661-012-2774-y

Keywords

Search

Navigation