International Journal of Environmental Monitoring and Analysis

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Assessment of Groundwater Quality Parameters Using Multivariate Statistics- A Case Study of Majmaah, KSA

Received: 11 December 2016    Accepted: 17 February 2017    Published: 15 March 2017
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Abstract

This paper aims at evaluating the groundwater quality parameters at part of Majmaah City, Saudi Arabia. The study uses multivariate statistics methods (Principal Component Analysis, PCA and/or Factor Analysis, FA) to determine the most important water quality parameters at the study area, aiming at introducing an environmental assessment of its current situation. Water quality parameters that showed levels above the standards would be spotted and reasons behind this contamination will be investigated. Real data are collected from 15 groundwater wells near farms part in Gewy area. The results of the water analysis data were subjected to intensive statistical tests and interpretations ware made in the highlight of physical factors. The paper also introduces a cost effective methodology to minimize the number of water quality parameters to the most important variables based on the multivariate statistical results. The interrelationship between different water quality parameters at the study area was also investigated. Moreover, Geostatistics techniques and GPS data, for the same wells, were utilized for characterization of some water quality parameters in 2D and results are introduced in the form of contour maps and 3D representation of these variables. The obtained results are presented as environmental maps for the water quality parameters at the study area and give, for the first time, a characterization of the water quality at the selected portion of Majmaah city.

DOI 10.11648/j.ijema.20170502.13
Published in International Journal of Environmental Monitoring and Analysis (Volume 5, Issue 2, April 2017)
Page(s) 32-40
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 Quality, Multivariate Statistics, Geostatistics, Majmaah, PCA

References
[1] EPA, (2001), “Parameters of Water Quality – Interpretation and Standards” Report, 133P, ISBN 1-84096-015-3.
[2] Mohammed Al-Saud et. al. (2011), “Challenges for an Integrated Groundwater Management in the Kingdom of Saudi Arabia” International Journal of Water Resources and Arid Environments 1 (1): 65-70, 2011.
[3] Walid Abdelrahamn (2006), “Groundwater Resources Management in Saudi Arabia” Special presentation at water conservation workshop, Khoper, KSA, December 2006.
[4] FAO, (2009), “Groundwater Management in Saudi Arabia”, A Report by FAO, 14P.
[5] "Mergeb Menikh Mountain at Majmaah Governorate", A heritage historical report issued by museums and heritage agency as a Book (in Arabic).
[6] Sameh S Ahmed and Mahmoud T. Azmi (2014), “A precise methodology integrates low-cost GPS data and GIS for monitoring groundwater quality parameters in Majmaah region, KSA". International Journal of Environmental Monitoring and Analysis, 2014: 2 (5): 279-288, November 2014. doi: 10.11648/j.ijema.20140205.18.
[7] Gregory T. French (1997), “Understanding the GPS, An Introduction to the Global Positioning System" First edition, April 1997.
[8] GPS Coordinate Converter, Maps and Info, http://boulter.com/gps/.
[9] Excel 2010, “Microsoft Office 2010".
[10] STATGRAPHICS plus, (1996): Statistical Graphics Corp.
[11] EPA, (2012), “Drinking Water Standards and Health Advisories”, 2012 Edition, EPA 822-s-12-001, Office of water, U.S Environmental Protection Agency. April 2012.
[12] World Health Organization, (2004), ”Guidelines for Drinking-water Quality”, Vol. 1, 3rd Edition, Geneva, ISBN: 9241546387.
[13] http://www.statsoft.com/Textbook/Principal-Components-Factor-Analysis.
[14] http://www.statisticssolutions.com/academic-solutions/resources/directory.
[15] SPSS 16.0 for windows, (Release 16.0.0, Sept 2007) http://www.winwarp.com.
[16] Issak, E. H. and Srivastava, R. M. (1989), “An Introduction to Applied Geostatistics”, Oxford Univ. Press, New York, 561 p.
[17] SURFER version 8.00, (2002), “Surface Mapping System”, Golden Surfer Inc.
Author Information
  • Mining and Metallurgical Engineering Department, Faculty of Engineering, Assiut University, Assiut, Egypt; Department of Civil and Environmental Engineering, College of Engineering, Majmaah University, Majmaah, KSA

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    Sameh S. Ahmed. (2017). Assessment of Groundwater Quality Parameters Using Multivariate Statistics- A Case Study of Majmaah, KSA. International Journal of Environmental Monitoring and Analysis, 5(2), 32-40. https://doi.org/10.11648/j.ijema.20170502.13

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    Sameh S. Ahmed. Assessment of Groundwater Quality Parameters Using Multivariate Statistics- A Case Study of Majmaah, KSA. Int. J. Environ. Monit. Anal. 2017, 5(2), 32-40. doi: 10.11648/j.ijema.20170502.13

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    AMA Style

    Sameh S. Ahmed. Assessment of Groundwater Quality Parameters Using Multivariate Statistics- A Case Study of Majmaah, KSA. Int J Environ Monit Anal. 2017;5(2):32-40. doi: 10.11648/j.ijema.20170502.13

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  • @article{10.11648/j.ijema.20170502.13,
      author = {Sameh S. Ahmed},
      title = {Assessment of Groundwater Quality Parameters Using Multivariate Statistics- A Case Study of Majmaah, KSA},
      journal = {International Journal of Environmental Monitoring and Analysis},
      volume = {5},
      number = {2},
      pages = {32-40},
      doi = {10.11648/j.ijema.20170502.13},
      url = {https://doi.org/10.11648/j.ijema.20170502.13},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijema.20170502.13},
      abstract = {This paper aims at evaluating the groundwater quality parameters at part of Majmaah City, Saudi Arabia. The study uses multivariate statistics methods (Principal Component Analysis, PCA and/or Factor Analysis, FA) to determine the most important water quality parameters at the study area, aiming at introducing an environmental assessment of its current situation. Water quality parameters that showed levels above the standards would be spotted and reasons behind this contamination will be investigated. Real data are collected from 15 groundwater wells near farms part in Gewy area. The results of the water analysis data were subjected to intensive statistical tests and interpretations ware made in the highlight of physical factors. The paper also introduces a cost effective methodology to minimize the number of water quality parameters to the most important variables based on the multivariate statistical results. The interrelationship between different water quality parameters at the study area was also investigated. Moreover, Geostatistics techniques and GPS data, for the same wells, were utilized for characterization of some water quality parameters in 2D and results are introduced in the form of contour maps and 3D representation of these variables. The obtained results are presented as environmental maps for the water quality parameters at the study area and give, for the first time, a characterization of the water quality at the selected portion of Majmaah city.},
     year = {2017}
    }
    

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    AB  - This paper aims at evaluating the groundwater quality parameters at part of Majmaah City, Saudi Arabia. The study uses multivariate statistics methods (Principal Component Analysis, PCA and/or Factor Analysis, FA) to determine the most important water quality parameters at the study area, aiming at introducing an environmental assessment of its current situation. Water quality parameters that showed levels above the standards would be spotted and reasons behind this contamination will be investigated. Real data are collected from 15 groundwater wells near farms part in Gewy area. The results of the water analysis data were subjected to intensive statistical tests and interpretations ware made in the highlight of physical factors. The paper also introduces a cost effective methodology to minimize the number of water quality parameters to the most important variables based on the multivariate statistical results. The interrelationship between different water quality parameters at the study area was also investigated. Moreover, Geostatistics techniques and GPS data, for the same wells, were utilized for characterization of some water quality parameters in 2D and results are introduced in the form of contour maps and 3D representation of these variables. The obtained results are presented as environmental maps for the water quality parameters at the study area and give, for the first time, a characterization of the water quality at the selected portion of Majmaah city.
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