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Assessment of groundwater pollution in West Delhi, India using geostatistical approach

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Abstract

The exploration, exploitation, and unscientific management of groundwater resources in the National Capital Territory (NCT) of Delhi, India have posed a serious threat of reduction in quantity and deterioration of quality. The objective of the study is to determine the groundwater quality and to assess the risk of groundwater pollution at Najafgarh, NCT of Delhi. The groundwater quality parameters were analyzed from the existing wells of the Najafgarh and the thematic maps were generated using geostatistical concepts. Ordinary kriging and indicator kriging methods were used as geostatistical approach for preparation of thematic maps of the groundwater quality parameters such as bicarbonate, calcium, chloride, electrical conductivity (EC), magnesium, nitrate, sodium, and sulphate with concentrations equal or greater than their respective groundwater pollution cutoff value. Experimental semivariogram values were fitted well in spherical model for the water quality parameters, such as bicarbonate, chloride, EC, magnesium, sodium, and sulphate and in exponential model for calcium and nitrate. The thematic maps of all the groundwater quality parameters exhibited an increasing trend of pollution from the northern and western part of the study area towards the southern and eastern part. The concentration was highest at the southernmost part of the study area but it could not reflect correctly the groundwater pollution status. The indicator kriging method is useful to assess the risk of groundwater pollution by giving the conditional probability of concentrations of different chemical parameters exceeding their cutoff values. Thus, risk assessment of groundwater pollution is useful for proper management of groundwater resources and minimizing the pollution threat.

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Correspondence to Partha Pratim Adhikary.

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Adhikary, P.P., Chandrasekharan, H., Chakraborty, D. et al. Assessment of groundwater pollution in West Delhi, India using geostatistical approach. Environ Monit Assess 167, 599–615 (2010). https://doi.org/10.1007/s10661-009-1076-5

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  • DOI: https://doi.org/10.1007/s10661-009-1076-5

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