Environmental Science and Pollution Research

, Volume 21, Issue 17, pp 10045–10066 | Cite as

Assessment and rationalization of water quality monitoring network: a multivariate statistical approach to the Kabbini River (India)

  • Musthafa Odayooth Mavukkandy
  • Subhankar KarmakarEmail author
  • P. S. Harikumar
Research Article


The establishment of an efficient surface water quality monitoring (WQM) network is a critical component in the assessment, restoration and protection of river water quality. A periodic evaluation of monitoring network is mandatory to ensure effective data collection and possible redesigning of existing network in a river catchment. In this study, the efficacy and appropriateness of existing water quality monitoring network in the Kabbini River basin of Kerala, India is presented. Significant multivariate statistical techniques like principal component analysis (PCA) and principal factor analysis (PFA) have been employed to evaluate the efficiency of the surface water quality monitoring network with monitoring stations as the evaluated variables for the interpretation of complex data matrix of the river basin. The main objective is to identify significant monitoring stations that must essentially be included in assessing annual and seasonal variations of river water quality. Moreover, the significance of seasonal redesign of the monitoring network was also investigated to capture valuable information on water quality from the network. Results identified few monitoring stations as insignificant in explaining the annual variance of the dataset. Moreover, the seasonal redesign of the monitoring network through a multivariate statistical framework was found to capture valuable information from the system, thus making the network more efficient. Cluster analysis (CA) classified the sampling sites into different groups based on similarity in water quality characteristics. The PCA/PFA identified significant latent factors standing for different pollution sources such as organic pollution, industrial pollution, diffuse pollution and faecal contamination. Thus, the present study illustrates that various multivariate statistical techniques can be effectively employed in sustainable management of water resources.


• The effectiveness of existing river water quality monitoring network is assessed

• Significance of seasonal redesign of the monitoring network is demonstrated

• Rationalization of water quality parameters is performed in a statistical framework


Cluster analysis Factor analysis Kabbini River Multivariate statistics Principal component analysis Rationalization Water quality monitoring network 



The authors sincerely thank the editor and the anonymous reviewers for offering insightful comments, which has significantly improved work quality and readability of the manuscript. The research work presented in this paper was partially supported by the Seed Grant (Project code: 07IR053) of the second author, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Musthafa Odayooth Mavukkandy
    • 1
  • Subhankar Karmakar
    • 2
    • 3
    Email author
  • P. S. Harikumar
    • 4
  1. 1.Centre for Environmental Science and Engineering (CESE)Indian Institute of Technology BombayMumbaiIndia
  2. 2.Centre for Environmental Science and Engineering (CESE)Indian Institute of Technology BombayMumbaiIndia
  3. 3.Interdisciplinary Program in Climate StudiesIndian Institute of Technology BombayMumbaiIndia
  4. 4.Central Water Analysis LaboratoryCentre for Water Resources Development and Management (CWRDM)CalicutIndia

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