American Journal of Biological and Environmental Statistics

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Water Quality Analysis of Drinking Water by Identification of Their Distribution and Process Capability

Received: 27 November 2017    Accepted: 12 December 2017    Published: 08 February 2018
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Abstract

The present study deals with the water quality management using Water Quality Index (WQI) and Distribution Identification model. The drinking water quality in Jaipur city has been used for the various physio-chemical parameters such as temperature, pH, turbidity, conductance, total hardness, alkalinity, magnesium, calcium, nitrate, chloride, fluoride, sodium, potassium. Drinking water suitability for domestic purposes was examined by WHO and BIS standards, which indicate the drinking water in almost all the areas, were not much suitable for drinking purpose. It is observed that Water Quality Index (WQI) is very high in Sanganer and VKI areas and Gamma distribution model fits on all the parameters for different sites of water data. Thus it was observed that potable water quality has degraded with respect to all the parameters and almost in all the Sites parameters.

DOI 10.11648/j.ajbes.20180401.14
Published in American Journal of Biological and Environmental Statistics (Volume 4, Issue 1, March 2018)
Page(s) 20-30
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Water Physio-Chemical Parameters, WQI, Distribution Identification Model, Process Capability and Health Effects

References
[1] Imo TS, Oomori T, Toshihiko M, Tamaki F (2007) the comparative study of trihalomethanes in drinking waters. Int J Environ Sci Tech 4 (4): 421–426.
[2] Kumar A, Dua A (2009) Water quality index for assessment of water quality of river Ravi at Modhopur (India). G J Env Sci 8 (1): 49–57.
[3] Cheng, Bing, and D. M. Titterington. “Neural Networks: A Review from a Statistical Perspective.” Statistical Science 9, no. 1 (1994): 2-30.
[4] Frew, James E., and Jeff Dozier. “Environmental Informatics.” Annual Review of Environment and Resources 37 (2012): pp. 449-472.
[5] Lebanon, Guy. Bias, Variance, and MSE of Estimators. Technical Notes, Georgia: Georgia Institute of Technology, 2010.
[6] Shkurin, Aleksei, and Alfredo Vellido. “Random Forests for quality control in G-Protein Coupled Receptor databases.” 2016.
[7] Starkweather, Jon. Cross Validation techniques in R: A brief overview of some methods, packages, and functions for assessing prediction models.. Review, University of North Texas, 2011.
[8] Alam Md JB, Muyen Z, Islam MR, Islam S, Mamun M (2007) Water quality parameters along rivers. Int J Environ Sci Tech 4 (1): 159–167.
[9] Bhardwaj R, Parmar KS (2013b) Wavelet and statistical analysis of river water quality parameters. App Math Comput 219 (20): 10172–10182.
[10] Damodhar U, Reddy MV (2013) Impact of pharmaceutical industry treated effluents on the water quality of river Uppanar, South east coast of India: a case study. Appl Water Sci 3: 501–514.
Author Information
  • Department of Mathematics, Jaipur Engineering College and Research Centre, Jaipur, India

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  • APA Style

    Smita Jain. (2018). Water Quality Analysis of Drinking Water by Identification of Their Distribution and Process Capability. American Journal of Biological and Environmental Statistics, 4(1), 20-30. https://doi.org/10.11648/j.ajbes.20180401.14

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    ACS Style

    Smita Jain. Water Quality Analysis of Drinking Water by Identification of Their Distribution and Process Capability. Am. J. Biol. Environ. Stat. 2018, 4(1), 20-30. doi: 10.11648/j.ajbes.20180401.14

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    AMA Style

    Smita Jain. Water Quality Analysis of Drinking Water by Identification of Their Distribution and Process Capability. Am J Biol Environ Stat. 2018;4(1):20-30. doi: 10.11648/j.ajbes.20180401.14

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  • @article{10.11648/j.ajbes.20180401.14,
      author = {Smita Jain},
      title = {Water Quality Analysis of Drinking Water by Identification of Their Distribution and Process Capability},
      journal = {American Journal of Biological and Environmental Statistics},
      volume = {4},
      number = {1},
      pages = {20-30},
      doi = {10.11648/j.ajbes.20180401.14},
      url = {https://doi.org/10.11648/j.ajbes.20180401.14},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajbes.20180401.14},
      abstract = {The present study deals with the water quality management using Water Quality Index (WQI) and Distribution Identification model. The drinking water quality in Jaipur city has been used for the various physio-chemical parameters such as temperature, pH, turbidity, conductance, total hardness, alkalinity, magnesium, calcium, nitrate, chloride, fluoride, sodium, potassium. Drinking water suitability for domestic purposes was examined by WHO and BIS standards, which indicate the drinking water in almost all the areas, were not much suitable for drinking purpose. It is observed that Water Quality Index (WQI) is very high in Sanganer and VKI areas and Gamma distribution model fits on all the parameters for different sites of water data. Thus it was observed that potable water quality has degraded with respect to all the parameters and almost in all the Sites parameters.},
     year = {2018}
    }
    

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    AB  - The present study deals with the water quality management using Water Quality Index (WQI) and Distribution Identification model. The drinking water quality in Jaipur city has been used for the various physio-chemical parameters such as temperature, pH, turbidity, conductance, total hardness, alkalinity, magnesium, calcium, nitrate, chloride, fluoride, sodium, potassium. Drinking water suitability for domestic purposes was examined by WHO and BIS standards, which indicate the drinking water in almost all the areas, were not much suitable for drinking purpose. It is observed that Water Quality Index (WQI) is very high in Sanganer and VKI areas and Gamma distribution model fits on all the parameters for different sites of water data. Thus it was observed that potable water quality has degraded with respect to all the parameters and almost in all the Sites parameters.
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