Skip to main content

Advertisement

SpringerLink
Log in

Groundwater quality assessment of Birjand plain aquifer using kriging estimation and sequential Gaussian simulation methods

  • Original Article
  • Published:
Environmental Earth Sciences Aims and scope Submit manuscript

Abstract

The performance of geostatistical estimation methods of ordinary kriging and sequential Gaussian simulation have been investigated in this study to evaluate the qualitative characteristics of groundwater in Birjand plain. For that purpose, 81 water samples were collected from groundwater wells and thirteen hydro-chemical parameters of calcium (Ca), chlorine (Cl), electrical conductivity (EC), bicarbonate (HCO3−), magnesium (Mg), sodium percent (Na%), sodium (Na), sodium absorption ratio (SAR), sulfate (SO42−), total dissolved solids (TDS) and total hardness (TH) were analyzed and interpreted. Variography of the variables was performed after the normalization and experimental variograms were plotted in GS+. The best theoretical models were then fitted to the experimental variograms. Validation of variograms was performed by two methods of cross-validation and residual analysis. Geostatistical estimation maps were then prepared for each groundwater variable. Since the smoothing effect is one of the major drawbacks of ordinary kriging estimations, the sequential Gaussian simulation method was also used to prepare the simulation maps of variables. The simulation results were more reliable than those obtained by ordinary kriging.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Adhikary PP, Dash CJ, Chandrasekharan H, Rajput TBS, Dubey SK (2012) Evaluation of groundwater quality for irrigation and drinking using GIS and geostatistics in a peri-urban area of Delhi. India Arab J Geosci 5(6):1423–1434

    Article  Google Scholar 

  • Asghari O, Soltni F, Hassan BA (2009) The comparison between sequential Gaussian simulation (SGS) of Choghart ore deposit and geostatistical estimation through ordinary kriging. Aust J Appl Sci 3(1):330–341

    Google Scholar 

  • De Marsily M (1986) Quantitative hydrogeology; groundwater hydrology for engineers. Academic Press, New York

    Google Scholar 

  • Desbarats AJ, Logan CE, Hinton MJ, Sharpe DR (2002) On the Kriging of water table elevations using collateral information from a digital elevation model. J HYDROL 255(1):25–38

    Article  Google Scholar 

  • Deutsch CV, Journel AG (1998) GSLIB: geostatistical software library and user’s guide. Oxford University Press, New York

    Google Scholar 

  • Dungan JLA, van der Meer F, Gorte B (1999) Spatial statistics for remote sensing. Springer, Dordrecht

    Google Scholar 

  • Finke PA, Brus DJ, Bierkens MFP, Hoogland T, Knotters M, De Vries F (2004) Mapping groundwater dynamics using multiple sources of exhaustive high resolution data. Geoderma 123(1):23–39

    Article  Google Scholar 

  • Gaus I, Kinniburgh DG, Talbot JC, Webster R (2003) Geostatistical analysis of arsenic concentration in groundwater in Bangladesh using disjunctive Kriging. J Environ Geol 44(8):939–948

    Article  Google Scholar 

  • Glacken IM, Snowden DV, Edwards AC (2001) Mineral resource estimation. Mineral resource and ore reserve estimation—the AusIMM guide to good practice. AusIMM Bull 4:189–198

    Google Scholar 

  • Jalali M, Karami S, Marj AF (2019) on the problem of the spatial distribution delineation of the groundwater quality indicators via multivariate statistical and geostatistical approaches. Environ Monit Assess 191(2):323

    Article  Google Scholar 

  • Jalali M, Karami S, Marj AF (2016) Geostatistical Evaluation of Spatial Variation Related to Groundwater Quality Database: Case Study for Arak Plain Aquifer. Iran Environ Model Assess 21(6):707–719

    Article  Google Scholar 

  • Karami S, Madani H, Katibeh H, Marj AF (2018) Assessment and modeling of the groundwater hydrogeochemical quality parameters via geostatistical approaches. Appl Water Sci 8(1):23

    Article  Google Scholar 

  • Matheron G (1971) The theory of regionalized variables and its applications. Les Cahiers du Centre de Morphologie Mathématique de Fontainebleau, Paris

    Google Scholar 

  • Mehrjardi RT, Jahromi MZ, Mahmodi S, Heidari A (2008) Spatial distribution of groundwater quality with geostatistics (case study: Yazd-Ardakan plain). World Appl Sci J 4(1):9–17

    Google Scholar 

  • Rossi ME, Deutsche CV (2014) Mineral resource estimation. Springer, Dordrecht

    Book  Google Scholar 

  • Theodossiou N, Latinopoulos P (2006) Evaluation and optimization of groundwater observation networks using the Kriging methodology. Environ Model Softw 21(7):991–1000

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mining, Faculty of Engineering, University of Birjand, Birjand, Iran

    Ahmad Aryafar & Vahid Khosravi

  2. Department of Mining and Metallurgy, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran

    Shawgar Karami

Authors
  1. Ahmad Aryafar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vahid Khosravi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shawgar Karami
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ahmad Aryafar.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aryafar, A., Khosravi, V. & Karami, S. Groundwater quality assessment of Birjand plain aquifer using kriging estimation and sequential Gaussian simulation methods. Environ Earth Sci 79, 210 (2020). https://doi.org/10.1007/s12665-020-08905-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12665-020-08905-8

Keywords

Search

Navigation