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Developing and validating intrinsic groundwater vulnerability maps in regions with limited data: a case study from Datong City in China using DRASTIC and Nemerow pollution indices

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Abstract

An intrinsic vulnerability map for a groundwater protection area for Datong City in China was developed using DRASTIC method which had been adapted to deal with the limited availability of data in the region. The compiled vulnerability map was then validated using two sets of Nemerow pollution indices which both integrated eight pollution parameters in the groundwater (pH, chloride, sulfate, nitrate, nitrite, total dissolved solid, total hardness and chemical oxygen demand) but were calculated by different approaches to provide integrated water quality assessments rather than specific pollution assessments like nitrate. The intrinsic groundwater vulnerability is divided into four classes due to the DRASTIC index values which lie in the range of (4, 8) in this study: “low”, “moderate”, “high” and “very high”. The validation process showed that the DRASTIC index values have a close correspondence with both sets of Nemerow pollution indices in the study area. The approaches used in this study for obtaining net recharge and vadose zone media data and values of hydraulic conductivity of aquifer sediments could be utilized elsewhere in China where there is a limited availability of data, as could the process of validating vulnerability maps using Nemerow pollution indices.

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Acknowledgements

Massive thanks to the reviewer for the generous changes and helpful comments on the manuscript.

Funding

This study was funded by National Key Research and Development Program of China (Grant numbers 2016YFC0402808, 2016YFA0601703), National Natural Science Foundation of China (Grant numbers 51479222).

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Correspondence to Gaoxu Wang.

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Kong, M., Zhong, H., Wu, Y. et al. Developing and validating intrinsic groundwater vulnerability maps in regions with limited data: a case study from Datong City in China using DRASTIC and Nemerow pollution indices. Environ Earth Sci 78, 262 (2019). https://doi.org/10.1007/s12665-019-8255-7

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