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Assessment of water quality using multivariate statistical techniques in the coastal region of Visakhapatnam, India

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Abstract

The present study was intended to develop a Water Quality Index (WQI) for the coastal water of Visakhapatnam, India from multiple measured water quality parameters using different multivariate statistical techniques. Cluster analysis was used to classify the data set into three major groups based on similar water quality characteristics. Discriminant analysis was used to generate a discriminant function for developing a WQI. Discriminant analysis gave the best result for analyzing the seasonal variation of water quality. It helped in data reduction and found the most discriminant parameters responsible for seasonal variation of water quality. Coastal water was classified into good, average, and poor quality considering WQI and the nutrient load. The predictive capacity of WQI was proved with random samples taken from coastal areas. High concentration of ammonia in surface water during winter was attributed to nitrogen fixation by the phytoplankton bloom which resulted due to East India Coastal Current. This study brings out the fact that water quality in the coastal region not only depends on the discharge from different pollution sources but also on the presence of different current patterns. It also illustrates the usefulness of WQI for analyzing the complex nutrient data for assessing the coastal water and identifying different pollution sources, considering reasons for seasonal variation of water quality.

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Abbreviations

WQI:

Water Quality Index

CA:

Cluster analysis

DA:

Discriminant analysis

PCA:

Principal component analysis

FA:

Factor analysis

DO:

Dissolve oxygen

NH3-N:

Ammonia nitrogen

NO3-N:

Nitrate nitrogen

PO4-P:

Phosphate phosphorus

BOD:

Biological oxygen demand

TSS:

Total suspended solids

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Acknowledgments

We are thankful to Central Marine Fisheries Research Institute (CMFRI), Visakhapatnam, India for supporting this research. We would also like to thank the National Institute of Oceanography (NIO) for providing the in situ observations. We also like to acknowledge the help and support provided by the Agricultural and Food Engineering Department and Oceans, Rivers, Atmosphere and Land Sciences Centre, Indian Institute of Technology, India for letting us avail the facility to conduct the research work. We thank two anonymous reviewers for their helpful comments and suggestions.

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Authors and Affiliations

  1. Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur, India

    Sangeeta Pati & C. K. Mukherjee

  2. Centre for Oceans, Rivers, Atmosphere and Land Sciences, Indian Institute of Technology, Kharagpur, India

    Mihir K. Dash

  3. Central Marine Fisheries Research Institute, Visakhapatnam, India

    B. Dash

  4. Indian Institute of Tropical Meteorology, Pune, India

    S. Pokhrel

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  1. Sangeeta Pati
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Correspondence to Sangeeta Pati.

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Pati, S., Dash, M.K., Mukherjee, C.K. et al. Assessment of water quality using multivariate statistical techniques in the coastal region of Visakhapatnam, India. Environ Monit Assess 186, 6385–6402 (2014). https://doi.org/10.1007/s10661-014-3862-y

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