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On the problem of the spatial distribution delineation of the groundwater quality indicators via multivariate statistical and geostatistical approaches

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Abstract

This paper highlights the advantages of multivariate statistical and geostatistical methods to compile the hydro-geochemical properties of groundwater. A total of 123 samples were collected from wells located in Saveh aquifer, in 2015. Seven parameters including total dissolved solids (TDS), sodium adsorption ratio( SAR), electrical conductivity (EC), sodium (Na+), total hardness (TH), chloride (Cl−), and sulfate (SO42−) were analyzed, compiled, and interpreted statistically and geostatistically. At first, factor analysis gave rise to produce a factor representing 94% of the variability. Also, variography was calculated and compiled to define spatial regression and experimental variograms were plotted by GS+ software, then, the best theoretical models were fitted on the variograms and an estimation map was prepared based on geostatistical relationship presented in the paper. Smoothing effect is one of the main drawbacks of forward geostatistical methods, on the contrary, inversed methods are subjected to no smoothing effect. Results showed that geostatistical inversed methods could reveal more reliable results than forward methods. Eventually, the map of the estimated factor, as well as error maps, was compiled. According to the evaluation of fractal dimensions, the estimated factor explained the variability of all hydrogeochemical parameters and groundwater quality was categorized as the safe, normal, and anomalous class, ranged from − 1.10 to 1.10, 1.11 to 3.1, and more than 3.1, respectively.

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Acknowledgments

The authors would like to thank Iran Water Resources Management Company for collecting, analyzing, and providing the data. Also, we fully appreciate the anonymous reviewers for their professional reviewing which their precious comments have definitely improved the scientific quality of the paper. Hereby, we thank the editorial board of Journal of Environmental Monitoring and Assessment for their consideration.

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Authors and Affiliations

  1. Department of Mining and Metallurgical Engineering, Amirkabir University of Technology (Tehran Polytechnic), 424. Hafez Ave., 15875-4413, Tehran, Iran

    Mohammad Jalali & Shawgar Karami

  2. Associate Professor in Soil Conservation & Watershed Management Research Institute (SCWMRI) & Islamic Azad University, Damavand Branch, 13445-1136, Tehran, Iran

    Ahmad Fatehi Marj

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  1. Mohammad Jalali
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  2. Shawgar Karami
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Correspondence to Shawgar Karami.

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Jalali, M., Karami, S. & Fatehi Marj, A. On the problem of the spatial distribution delineation of the groundwater quality indicators via multivariate statistical and geostatistical approaches. Environ Monit Assess 191 (Suppl 2), 323 (2019). https://doi.org/10.1007/s10661-019-7432-1

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  • DOI: https://doi.org/10.1007/s10661-019-7432-1

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