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Characterizing groundwater quality ranks for drinking purposes in Sylhet district, Bangladesh, using entropy method, spatial autocorrelation index, and geostatistics

Environmental Science and Pollution Research volume 24, pages 26350–26374 (2017)Cite this article

Abstract

Drinking water is susceptible to the poor quality of contaminated water affecting the health of humans. Thus, it is an essential study to investigate factors affecting groundwater quality and its suitability for drinking uses. In this paper, the entropy theory, multivariate statistics, spatial autocorrelation index, and geostatistics are applied to characterize groundwater quality and its spatial variability in the Sylhet district of Bangladesh. A total of 91samples have been collected from wells (e.g., shallow, intermediate, and deep tube wells at 15–300-m depth) from the study area. The results show that NO3 −, then SO4 2−, and As are the most contributed parameters influencing the groundwater quality according to the entropy theory. The principal component analysis (PCA) and correlation coefficient also confirm the results of the entropy theory. However, Na+ has the highest spatial autocorrelation and the most entropy, thus affecting the groundwater quality. Based on the entropy-weighted water quality index (EWQI) and groundwater quality index (GWQI) classifications, it is observed that 60.45 and 53.86% of water samples are classified as having an excellent to good qualities, while the remaining samples vary from medium to extremely poor quality domains for drinking purposes. Furthermore, the EWQI classification provides the more reasonable results than GWQIs due to its simplicity, accuracy, and ignoring of artificial weight. A Gaussian semivariogram model has been chosen to the best fit model, and groundwater quality indices have a weak spatial dependence, suggesting that both geogenic and anthropogenic factors play a pivotal role in spatial heterogeneity of groundwater quality oscillations.

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Acknowledgements

We appreciate the cooperation rendered by the Sylhet City Corporation (SCC) for giving access to the production wells and by the staff of the local Department of Public Health Engineering (DPHE) office in identifying the local deep and shallow hand tube wells for sampling. The logistic support for sampling was provided by Atomic Energy Research Establishment, Savar, Dhaka. We would like to thank the editor Dr. Marcus Schulz and three anonymous reviewers for improving the quality of the manuscript substantially.

Funding information

The study was performed under the framework of the IAEA Regional Cooperation Agreement (RCA) project RAS/7/022.

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Affiliations

  1. Department of Disaster Management, Begum Rokeya University, Rangpur, 5400, Bangladesh

    Abu Reza Md. Towfiqul Islam

  2. College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Abu Reza Md. Towfiqul Islam & Ronghao Chu

  3. Isotope Hydrology Division, Institute of Nuclear Science and Technology, Bangladesh Atomic Energy Commission, Savar, Dhaka 1349, Bangladesh

    Nasir Ahmed

  4. Department of Environmental Sciences, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh

    Md. Bodrud-Doza

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  1. Abu Reza Md. Towfiqul Islam
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  2. Nasir Ahmed
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Correspondence to Abu Reza Md. Towfiqul Islam.

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Islam, A.R.M.T., Ahmed, N., Bodrud-Doza, M. et al. Characterizing groundwater quality ranks for drinking purposes in Sylhet district, Bangladesh, using entropy method, spatial autocorrelation index, and geostatistics. Environ Sci Pollut Res 24, 26350–26374 (2017). https://doi.org/10.1007/s11356-017-0254-1

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Keywords

  • Entropy theory
  • Spatial autocorrelation index
  • Water quality index
  • Semivariogram model
  • Groundwater contamination
  • Geostatistics