Advertisement

Water Quality, Exposure and Health

, Volume 7, Issue 4, pp 567–581 | Cite as

Application of Multivariate Statistical Techniques in Determining the Spatial Temporal Water Quality Variation of Ganga and Yamuna Rivers Present in Uttarakhand State, India

  • Madhuben SharmaEmail author
  • Ankur Kansal
  • Suresh Jain
  • Prateek Sharma
Original Paper

Abstract

Primary monitoring of 18 water quality parameters for rivers Ganga and Yamuna of Uttarakhand State was carried out to study the seasonal variation of these parameters, identify potential sources of pollution, and clustering of monitoring stations with similar characteristics. Wilcoxon signed-rank test, Paired t test and multivariate statistical techniques—principal component analysis (PCA) and cluster analysis (CA) were used to analyse the collected data. Separate analyses were conducted for summer and winter periods. The Wilcoxon signed-rank test and paired t test revealed seasonal variability in the data set with high pollution levels during summer period as compared to winter period. The CA grouped 15 monitoring stations of river Ganga and 5 monitoring stations of river Yamuna into 2 clusters of similar characteristics. The PCA resulted in the identification of four major sources of pollution for river Ganga, and three for river Yamuna. The findings of the study provide useful information in interpretation of complex datasets and for water quality assessment, identification of pollution sources/factors and understanding of temporal and spatial variations of water quality for effective river water quality management.

Keywords

Water quality t test Wilcoxon signed-rank test Principal component analysis and cluster analysis 

Notes

Acknowledgments

The authors gratefully acknowledge the cooperation of Mr. Neeraj Sharma for editorial assistance. The editors and anonymous referees are gratefully acknowledged.

References

  1. Adbo MH (2004) Distribution of some chemical elements in the recent sediments of Damietta Branch, River Nile, Egypt. Egypt Acad Soc Environ Develop (D-Environmental Studies) 5(2):125–146Google Scholar
  2. APHA, AWWA, WEF (1998) Standard Methods for the Examination of Water and Wastewater, 20th edn. American Public Health Association/American Water Works Association/Water Environment Federation, WashingtonGoogle Scholar
  3. Bonansea M, Ledesma C, Rodriguez C, Pinotti L (2014) Water quality assessment using multivariate statistical techniques in Río Tercero Reservoir, Argentina. Hydrol Res. doi: 10.2166/nh.2014.1 Google Scholar
  4. Boughriet A, Ouddane B, Fischer JC, Wartel M, Leman G (1992) Variability of dissolved Mn and Zn in the Seine estuary and chemical speciation of these metals in suspended matter. Water Res 26(10):1359–1378CrossRefGoogle Scholar
  5. Das TM (1991) Some aspects of the biogeography of the Ganga. In: Krishna Murti CR, Bilgrami KS, Das TM, Mathur RP (eds) The Ganga a scientific study. The Ganga Project Directorate, New Delhi, pp 187–193Google Scholar
  6. Jain CK (2002) A hydro-chemical study of a mountainous watershed: the Ganga, India. Water Res 36:1262–1274CrossRefGoogle Scholar
  7. Johnson RA, Wichern DA (2002) Applied multivariate statistical analysis. Pearson Education Inc., Upper Saddle RiverGoogle Scholar
  8. Jolliffe IT (1986) Principal component analysis. Springer, University of Geneva, New YorkCrossRefGoogle Scholar
  9. Kaiser HF (1960) The application of electronic computers to factor analysis. Educ Psychol Meas 20:141–151CrossRefGoogle Scholar
  10. Kannel PR, Leea S, Leeb YS (2008) Assessment of spatial–temporal patterns of surface and ground water qualities and factors influencing management strategy of groundwater system in an urban river corridor of Nepal. J Environ Manag 86:595–604CrossRefGoogle Scholar
  11. Kumari M, Tripathi S, Pathak V, Tripathi BD (2012) Chemometric characterization of river water quality. Environ Monit Assess 185:3081–3092. doi: 10.1007/s10661-012-2774-y CrossRefGoogle Scholar
  12. Li Y, Xu L, Li S (2009) Water quality analysis of the Songhua River basin using multivariate techniques. J Water Resour Prot 2:110–121CrossRefGoogle Scholar
  13. Li H, Shi A, Li M, Zhang X (2013) Effect of pH, temperature, dissolved oxygen, and flow rate of overlying water on heavy metals release from storm sewer sediments. J Chem. doi: 10.1155/2013/434012 Google Scholar
  14. Liu CW, Lin KH, Kuo YM (2003) Application of factor analysis in the assessment of groundwater quality in a Blackfoot disease area in Taiwan. Sci Total Environ 313(1–3):77–89CrossRefGoogle Scholar
  15. Odoemelam SA, Okorie DO, Oko IO (2014) Physicochemical parameters and heavy metal content of water, fish and sediments from cross river at afikpo north local Government area of Ebonyi state, Nigeria. J Chem 3(1):1–11Google Scholar
  16. Oketola A, Adekolurejo SM, Osibanjo O (2013) Water quality assessment of River Ogun using multivariate statistical techniques. J Environ Protect 4(5):466–479. doi: 10.4236/jep.2013.45055 CrossRefGoogle Scholar
  17. Ouyang Y (2005) Evaluation of river water quality monitoring stations by principal component analysis. Water Res 39:2621–2635CrossRefGoogle Scholar
  18. Peng J, Chen S, Dong P (2010) Temporal variation of sediment load in the Yellow River basin, China, and its impacts on the lower reaches and the river delta. Catena 83(2–3):135–147CrossRefGoogle Scholar
  19. Razmkhah H, Abrishamchi A, Torkian A (2010) Evaluation of spatial and temporal variation in water quality by pattern recognition techniques: a case study on Jajrood River (Tehran, Iran). J Environ Manag 91:852–860CrossRefGoogle Scholar
  20. Reid MK, Spencer KL (2009) Use of principal components analysis (PCA) on estuarine sediment datasets: the effect of data pre-treatment. Environ Pollut 157:2275–2281CrossRefGoogle Scholar
  21. Sharma S (1996) Applied multivariate techniques. John Wiley & Sons Inc, HobokenGoogle Scholar
  22. Shrestha S, Kazama F (2007) Assessment of surface water quality using multivariate statistical techniques: a case study of the Fuji river basin, Japan. Environ Model Softw 22(4):464–475CrossRefGoogle Scholar
  23. Simeonov V, Stratis JA, Samara C, Zachariadis G, Voutsa D, Anthemidis A (2003) Assessment of the surface water quality in Northern Greece. Water Res 37(17):4119–4124CrossRefGoogle Scholar
  24. Singh KP, Malik A, Mohan D, Sinha S (2004) Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India): a case study. Water Res 38:3980–3992CrossRefGoogle Scholar
  25. Singh KP, Malik A, Sinha S (2005) Water quality assessment and apportionment of pollution sources of Gomti River (India) using multivariate statistical techniques: a case study. Anal Chim Acta 538:355–374CrossRefGoogle Scholar
  26. SPSS-10 (1999) Statistical package for the social sciences. Spss Inc, ChicagoGoogle Scholar
  27. Wunderlin DA, Diaz MP, Ame MV, Pesce SF, Hued AC, Bistoni MA (2001) Pattern recognition techniques for the evaluation of spatial and temporal variations in water quality. A case study: Suquia river basin (Cordoba, Argentina). Water Res 35(12):2881–2894CrossRefGoogle Scholar
  28. Zhao J, Fu G, Lei K, Li Y (2011) Multivariate analysis of surface water quality in the three Gorges area of China and implications for water management. J Environ Sci 23(9):1460–1471CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Madhuben Sharma
    • 1
    Email author
  • Ankur Kansal
    • 2
  • Suresh Jain
    • 1
  • Prateek Sharma
    • 1
  1. 1.Department of Natural ResourcesTERI UniversityNew DelhiIndia
  2. 2.Uttarakhand Environment Protection and Pollution Control BoardRoorkeeIndia

Personalised recommendations