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An Application of Geostatistics to Analysis of Water Quality Parameters in Rivers and Streams in Niger State, Nigeria

Received: 3 August 2015     Accepted: 17 August 2015     Published: 26 August 2015
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Abstract

Assessment of surface water quality using multivariate statistical techniques does not incorporate the spatial locations of data into their defining computations. Information on spatial continuity of surface water concentrations can help in identifying the magnitude of contamination by runoff and anthropogenic pollutions. In the present study, spatial behavior of five (5) surface water quality parameters of some rivers/streams in Niger State of Nigeria was studied using R geostatistical package gstat, in conjunction with packages sp, rgdal, spatstat and maptools. The variograms and ordinary krigged spatial maps were generated for rainy and dry seasons. The characteristics of the best variable models; range; sill and nugget effects of each parameter were obtained. The variogram analysis indicated a high spatial coherence for E.co, Mg and TDS, whereas TCo and TH indicated a low spatial coherence. The nugget to sill ratios of experimental and linear fitted variogram models in all cases were less than 0.25 indicating that the rivers/streams water level has strong spatial coherence in both seasons. This result shows that linear model is the best for both seasons. Krigged spatial variability maps revealed that an average range of 48km variograms for dry season changes more rapidly than it does in rainy season with an average range of 4.3 km and R2 values of 0.80 to 0.92.

Published in American Journal of Theoretical and Applied Statistics (Volume 4, Issue 5)
DOI 10.11648/j.ajtas.20150405.18
Page(s) 373-388
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), 2015. Published by Science Publishing Group

Keywords

Kriging, Predictions, Experimental Variogram, Nugget, Water Parameters

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  • APA Style

    Isah Audu, Abdullahi Usman. (2015). An Application of Geostatistics to Analysis of Water Quality Parameters in Rivers and Streams in Niger State, Nigeria. American Journal of Theoretical and Applied Statistics, 4(5), 373-388. https://doi.org/10.11648/j.ajtas.20150405.18

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    ACS Style

    Isah Audu; Abdullahi Usman. An Application of Geostatistics to Analysis of Water Quality Parameters in Rivers and Streams in Niger State, Nigeria. Am. J. Theor. Appl. Stat. 2015, 4(5), 373-388. doi: 10.11648/j.ajtas.20150405.18

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    AMA Style

    Isah Audu, Abdullahi Usman. An Application of Geostatistics to Analysis of Water Quality Parameters in Rivers and Streams in Niger State, Nigeria. Am J Theor Appl Stat. 2015;4(5):373-388. doi: 10.11648/j.ajtas.20150405.18

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  • @article{10.11648/j.ajtas.20150405.18,
      author = {Isah Audu and Abdullahi Usman},
      title = {An Application of Geostatistics to Analysis of Water Quality Parameters in Rivers and Streams in Niger State, Nigeria},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {4},
      number = {5},
      pages = {373-388},
      doi = {10.11648/j.ajtas.20150405.18},
      url = {https://doi.org/10.11648/j.ajtas.20150405.18},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150405.18},
      abstract = {Assessment of surface water quality using multivariate statistical techniques does not incorporate the spatial locations of data into their defining computations. Information on spatial continuity of surface water concentrations can help in identifying the magnitude of contamination by runoff and anthropogenic pollutions. In the present study, spatial behavior of five (5) surface water quality parameters of some rivers/streams in Niger State of Nigeria was studied using R geostatistical package gstat, in conjunction with packages sp, rgdal, spatstat and maptools. The variograms and ordinary krigged spatial maps were generated for rainy and dry seasons. The characteristics of the best variable models; range; sill and nugget effects of each parameter were obtained. The variogram analysis indicated a high spatial coherence for E.co, Mg and TDS, whereas TCo and TH indicated a low spatial coherence. The nugget to sill ratios of experimental and linear fitted variogram models in all cases were less than 0.25 indicating that the rivers/streams water level has strong spatial coherence in both seasons. This result shows that linear model is the best for both seasons. Krigged spatial variability maps revealed that an average range of 48km variograms for dry season changes more rapidly than it does in rainy season with an average range of 4.3 km and R2 values of 0.80 to 0.92.},
     year = {2015}
    }
    

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    AU  - Isah Audu
    AU  - Abdullahi Usman
    Y1  - 2015/08/26
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    N1  - https://doi.org/10.11648/j.ajtas.20150405.18
    DO  - 10.11648/j.ajtas.20150405.18
    T2  - American Journal of Theoretical and Applied Statistics
    JF  - American Journal of Theoretical and Applied Statistics
    JO  - American Journal of Theoretical and Applied Statistics
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    UR  - https://doi.org/10.11648/j.ajtas.20150405.18
    AB  - Assessment of surface water quality using multivariate statistical techniques does not incorporate the spatial locations of data into their defining computations. Information on spatial continuity of surface water concentrations can help in identifying the magnitude of contamination by runoff and anthropogenic pollutions. In the present study, spatial behavior of five (5) surface water quality parameters of some rivers/streams in Niger State of Nigeria was studied using R geostatistical package gstat, in conjunction with packages sp, rgdal, spatstat and maptools. The variograms and ordinary krigged spatial maps were generated for rainy and dry seasons. The characteristics of the best variable models; range; sill and nugget effects of each parameter were obtained. The variogram analysis indicated a high spatial coherence for E.co, Mg and TDS, whereas TCo and TH indicated a low spatial coherence. The nugget to sill ratios of experimental and linear fitted variogram models in all cases were less than 0.25 indicating that the rivers/streams water level has strong spatial coherence in both seasons. This result shows that linear model is the best for both seasons. Krigged spatial variability maps revealed that an average range of 48km variograms for dry season changes more rapidly than it does in rainy season with an average range of 4.3 km and R2 values of 0.80 to 0.92.
    VL  - 4
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Author Information
  • Department of Mathematics & Statistics, School of Physical Sciences, Federal University of Technology, Minna, Nigeria

  • Academic Planning Unit, Vice Chancellor’s Office, Federal University of Technology, Minna, Nigeria

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