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Groundwater hydrogeochemical assessment using advanced spatial statistics methods: a case study of Tehran-Karaj plain aquifer, Iran

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Abstract

Geostatistical tools have been increasingly applied to compile spatial distribution maps of groundwater quality. Results of geostatistics can be helpful for decision-makers to carry out appropriate remedial actions to sustain the quality of groundwater sources. The main purpose of this paper is to assess the groundwater hydrogeochemistry of Tehran-Karaj plain aquifer, Iran, by a forward geostatistical method and an inverse geostatistical method called sequential Gaussian simulation. Seven important hydrogeochemical properties of the aquifer including total dissolved solids, sodium adsorption ratio, electrical conductivity, sodium, total hardness, chloride, and sulfate were analyzed and compiled geostatistically. Data were taken from 137 well samples in 2016. After data normalization, variography was compiled, and experimental variograms were plotted; then, the best theoretical model was fitted on each variogram based on the minimum residual sum of squares. Cross-validation was used to determine the accuracy of parameters related to the variograms. Estimation maps of the groundwater hydrogeochemistry were prepared, and the estimation variance map was drawn to assess the accuracy of estimation in each estimated point. Forward geostatistical methods are subjected to smoothing, while inverse geostatistical methods are not subjected to this problem. The results of this study revealed that the utilized inverse geostatistical methods called simulation algorithms are more accurate than forward methods. Eventually, estimation maps of each parameter, as well as error maps, were compiled, and critical regions have been proposed according to the simulated maps.

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Acknowledgments

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

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Authors and Affiliations

  1. Department of Mining Engineering, Amirkabir University of Technology (Tehran Polytechnic), P-O. Box: 15875-4413, 424. Hafez Ave., Tehran, Iran

    Shawgar Karami & Homayoon Katibeh

  2. Mining Exploration Engineering and Academic Researcher in Civil and Geoscience Institute, Department of Mining Engineering, Amirkabir University of Technology (Tehran Polytechnic), P-O. Box: 15875-4413, 424. Hafez Ave., Tehran, Iran

    Mohammad Jalali

  3. Soil Conservation & Watershed Management Research Institute (SCWMRI), & Damavand, Islamic Azad University, P-O. Box: 13445-1136, Tehran, Iran

    Ahmad Fatehi Marj

Authors
  1. Shawgar Karami
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  2. Mohammad Jalali
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  3. Homayoon Katibeh
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  4. Ahmad Fatehi Marj
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Corresponding author

Correspondence to Shawgar Karami.

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Responsible editor: Ozgur Kisi

Appendix

Appendix

Fig. 8
figure 8

shows the scatter plot of estimated values versus the actual ones.

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Fig. 9
figure 9

Histogram of the residuals calculated by Jackknife kriging illustrating that the utilized method is unbiased. This process can be used to check if the method is unbiased. The unbiased method should carry three criteria: (1) showing a normal distribution (2) having a mean close to zero (c) having a variance near one or less

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Karami, S., Jalali, M., Katibeh, H. et al. Groundwater hydrogeochemical assessment using advanced spatial statistics methods: a case study of Tehran-Karaj plain aquifer, Iran. Arab J Geosci 13, 84 (2020). https://doi.org/10.1007/s12517-019-5047-z

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