International Journal of Energy and Environmental Science

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Sensitivity Analysis of Groundwater Quality around Peat Swamp Forest Region to Examine Trend Analysis of Physicochemical Parameters

Received: 25 October 2016    Accepted: 4 November 2016    Published: 25 November 2016
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Abstract

The aim of this study was examine sensitivity analysis of groundwater quality around peat swamp forest region to determine trend analysis of physicochemical parameters. In order to achieve this goal, samples were taken from Ziarat spring, the nearest hydrometric station around Suteh PSF from 1998 to 2015. The parameters such as TDS, EC, pH and major ions including SO4, Mg, HCO3, Ca, Na, Cl, and K of the Ziarat spring were analyzed. To examine the trend analysis of physiochemical parameters, the winter’s model of time series analysis has been used. The order of abundance of ions are HCO3> Cl> Na> SO4> Ca> Mg> K. The trend analysis of pH demonstrates a decreasing trend (from alkaline to acidic) but EC and TDS trends show a rising trend. According to sensitivity analysis by using the response analysis of factorial analysis and Pareto charts, the most important factor for pH was Na×HCO3 and then a combination of Ca, Mg and HCO3. For EC, the most important factor was calcium and then the K×SO4 factor and for TDS, it was the K × SO4 and then the K × Ca factor. Determinative ions based on the singular sensitivity analysis pH are in the following order Ca > HCO3> Mg> SO4> K> Na > Cl. Meanwhile, for EC, the determinant ions are in the following order Ca > Mg> SO4> HCO3> Na >K> Cl and the determinant ions for TDS are followed by K> Cl > HCO3> Ca > Mg> SO4> Na.

DOI 10.11648/j.ijees.20160101.11
Published in International Journal of Energy and Environmental Science (Volume 1, Issue 1, November 2016)
Page(s) 1-6
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Keywords

Groundwater Quality, Physiochemical Parameters, Sensitivity Analysis, Trend Analysis, Ziarat Spring

References
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[4] Páez-Osuna, F. Camaronicultura y medio ambiente. Instituto de Ciencias Del Mary, 2001.
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[6] Lu, W. X., Zhao, Y., Chu, H. B., & Yang, L. L. The analysis of groundwater levels influenced by dual factors in western Jilin Province by using time series analysis method. Applied Water Science, 2014, 4(3), 251-260.
[7] Feng, L., & Zhou, J. Trend predictions in water resources using rescaled range (R/S) analysis. Environmental earth sciences, 2013, 68(8), 2359-2363.
[8] ZHAO, J., BU, Y. M., & ZHOU, X. J. Application of time series analysis method in groundwater level dynamic forecast of Shenyang City [J]. Water Resources & Hydropower of Northeast China, 2007, 8, 014.
[9] Yang, Z. P., Lu, W. X., Long, Y. Q., & Li, P. Application and comparison of two prediction models for groundwater levels: A case study in Western Jilin Province, China. Journal of arid environments, 2009, 73(4), 487-492.
[10] Liang, Y. H. Analyzing and forecasting the reliability for repairable systems using the time series decomposition method. International Journal of Quality & Reliability Management, 2011, 28(3), 317-327.
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[14] Chapman, D. V. (Ed.). Water quality assessments: a guide to the use of biota, sediments and water in environmental monitoring (p. 626). London: E & Fn Spon. 1996.
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    Milad Kurdi, Taymour Eslamkish. (2016). Sensitivity Analysis of Groundwater Quality around Peat Swamp Forest Region to Examine Trend Analysis of Physicochemical Parameters. International Journal of Energy and Environmental Science, 1(1), 1-6. https://doi.org/10.11648/j.ijees.20160101.11

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    ACS Style

    Milad Kurdi; Taymour Eslamkish. Sensitivity Analysis of Groundwater Quality around Peat Swamp Forest Region to Examine Trend Analysis of Physicochemical Parameters. Int. J. Energy Environ. Sci. 2016, 1(1), 1-6. doi: 10.11648/j.ijees.20160101.11

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    AMA Style

    Milad Kurdi, Taymour Eslamkish. Sensitivity Analysis of Groundwater Quality around Peat Swamp Forest Region to Examine Trend Analysis of Physicochemical Parameters. Int J Energy Environ Sci. 2016;1(1):1-6. doi: 10.11648/j.ijees.20160101.11

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  • @article{10.11648/j.ijees.20160101.11,
      author = {Milad Kurdi and Taymour Eslamkish},
      title = {Sensitivity Analysis of Groundwater Quality around Peat Swamp Forest Region to Examine Trend Analysis of Physicochemical Parameters},
      journal = {International Journal of Energy and Environmental Science},
      volume = {1},
      number = {1},
      pages = {1-6},
      doi = {10.11648/j.ijees.20160101.11},
      url = {https://doi.org/10.11648/j.ijees.20160101.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijees.20160101.11},
      abstract = {The aim of this study was examine sensitivity analysis of groundwater quality around peat swamp forest region to determine trend analysis of physicochemical parameters. In order to achieve this goal, samples were taken from Ziarat spring, the nearest hydrometric station around Suteh PSF from 1998 to 2015. The parameters such as TDS, EC, pH and major ions including SO4, Mg, HCO3, Ca, Na, Cl, and K of the Ziarat spring were analyzed. To examine the trend analysis of physiochemical parameters, the winter’s model of time series analysis has been used. The order of abundance of ions are HCO3> Cl> Na> SO4> Ca> Mg> K. The trend analysis of pH demonstrates a decreasing trend (from alkaline to acidic) but EC and TDS trends show a rising trend. According to sensitivity analysis by using the response analysis of factorial analysis and Pareto charts, the most important factor for pH was Na×HCO3 and then a combination of Ca, Mg and HCO3. For EC, the most important factor was calcium and then the K×SO4 factor and for TDS, it was the K × SO4 and then the K × Ca factor. Determinative ions based on the singular sensitivity analysis pH are in the following order Ca > HCO3> Mg> SO4> K> Na > Cl. Meanwhile, for EC, the determinant ions are in the following order Ca > Mg> SO4> HCO3> Na >K> Cl and the determinant ions for TDS are followed by K> Cl > HCO3> Ca > Mg> SO4> Na.},
     year = {2016}
    }
    

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  • TY  - JOUR
    T1  - Sensitivity Analysis of Groundwater Quality around Peat Swamp Forest Region to Examine Trend Analysis of Physicochemical Parameters
    AU  - Milad Kurdi
    AU  - Taymour Eslamkish
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    T2  - International Journal of Energy and Environmental Science
    JF  - International Journal of Energy and Environmental Science
    JO  - International Journal of Energy and Environmental Science
    SP  - 1
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    PB  - Science Publishing Group
    SN  - 2578-9546
    UR  - https://doi.org/10.11648/j.ijees.20160101.11
    AB  - The aim of this study was examine sensitivity analysis of groundwater quality around peat swamp forest region to determine trend analysis of physicochemical parameters. In order to achieve this goal, samples were taken from Ziarat spring, the nearest hydrometric station around Suteh PSF from 1998 to 2015. The parameters such as TDS, EC, pH and major ions including SO4, Mg, HCO3, Ca, Na, Cl, and K of the Ziarat spring were analyzed. To examine the trend analysis of physiochemical parameters, the winter’s model of time series analysis has been used. The order of abundance of ions are HCO3> Cl> Na> SO4> Ca> Mg> K. The trend analysis of pH demonstrates a decreasing trend (from alkaline to acidic) but EC and TDS trends show a rising trend. According to sensitivity analysis by using the response analysis of factorial analysis and Pareto charts, the most important factor for pH was Na×HCO3 and then a combination of Ca, Mg and HCO3. For EC, the most important factor was calcium and then the K×SO4 factor and for TDS, it was the K × SO4 and then the K × Ca factor. Determinative ions based on the singular sensitivity analysis pH are in the following order Ca > HCO3> Mg> SO4> K> Na > Cl. Meanwhile, for EC, the determinant ions are in the following order Ca > Mg> SO4> HCO3> Na >K> Cl and the determinant ions for TDS are followed by K> Cl > HCO3> Ca > Mg> SO4> Na.
    VL  - 1
    IS  - 1
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Author Information
  • Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran, Iran

  • Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran, Iran

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