Groundwater quality assessment using geospatial and statistical approaches over Faridabad and Gurgaon districts of National Capital Region, India

This study presents an assessment of groundwater quality over the two constituent districts (Faridabad and Gurgaon) of the National Capital Region (NCR), India, using geospatial and statistical approaches. These districts have been subjected to rapid urbanization and industrialization in recent year...

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Veröffentlicht in:Applied water science 2022-04, Vol.12 (4), p.1-14, Article 75
Hauptverfasser: Swain, Sabyasachi, Sahoo, Sashikanta, Taloor, Ajay Kumar
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Sprache:eng
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Zusammenfassung:This study presents an assessment of groundwater quality over the two constituent districts (Faridabad and Gurgaon) of the National Capital Region (NCR), India, using geospatial and statistical approaches. These districts have been subjected to rapid urbanization and industrialization in recent years. The groundwater quality parameters viz., pH, electrical conductivity (EC), carbonate (CO 3 2− ), bicarbonate (HCO 3 − ), chloride (Cl − ), sulphate (SO 4 2− ), nitrate (NO 3 − ), fluoride (F − ), calcium (Ca 2+ ), magnesium (Mg 2+ ), sodium (Na + ), potassium (K + ), silica (SiO 2 ), and total hardness (TH) are obtained for the year of 2017 from 28 sites over the study area. The suitability for human drinking purposes is assessed by comparing the concentration of parameters at each site with respect to their permissible limits recommended by the Bureau of Indian Standards (IS 10500: 2012). The geospatial mapping of the water quality parameters is carried out to visualize their variations, whereas their risk assessment is accomplished by the statistical approaches viz., water quality index (WQI), correlation, and principal component analysis (PCA). The number of sites exceeding the permissible limits of pH, EC, Cl − , SO 4 2− , NO 3 − , F − , Ca 2+ , Mg 2+ , Na + , K + , and TH is obtained to be 7, 15, 5, 6, 8, 3, 5, 7, 18, 3, and 8, respectively. The WQI analysis revealed 10 out of the 28 sites to be unsuitable for drinking purposes. The parameters mostly exhibited positive correlations except for pH that showed a negative correlation with other parameters. The results of PCA revealed the first principal component (PC1) to explain more than 95% of the total variance, thereby significantly reducing the dimensionality. The deteriorated water quality may be mainly attributed to anthropogenic activities, i.e., reckless industrial growth, population explosion, and rapid urbanization. This study emphasizes the need for regular water quality monitoring, and the information reported will certainly help for water resources planning and management, especially over the industrial regions of NCR, India.
ISSN:2190-5487
2190-5495
DOI:10.1007/s13201-022-01604-8