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Appraisal of groundwater contamination and spatial variation using geostatistical modeling in Surguja district of Chhattisgarh, India
Appraisal of groundwater contamination and spatial variation using geostatistical modeling in Surguja district of Chhattisgarh, India
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Appraisal of groundwater contamination and spatial variation using geostatistical modeling in Surguja district of Chhattisgarh, India
Appraisal of groundwater contamination and spatial variation using geostatistical modeling in Surguja district of Chhattisgarh, India

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Appraisal of groundwater contamination and spatial variation using geostatistical modeling in Surguja district of Chhattisgarh, India
Appraisal of groundwater contamination and spatial variation using geostatistical modeling in Surguja district of Chhattisgarh, India
Journal Article

Appraisal of groundwater contamination and spatial variation using geostatistical modeling in Surguja district of Chhattisgarh, India

2021
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Overview
In several areas of Chhattisgarh, the disintegration of the content of groundwater by the anthropogenic activities is rising at an alarming pace. However, there is still limited information regarding groundwater quality. The present study develops a geostatistical-based water quality index (WQI) and analyzes the spatial variation of contamination zone within the study area. Water samples were collected and tested for different parameters from 55 different locations based on random sampling method. The physio-chemicals properties of water like pH, conductivity, total dissolved solids, calcium, magnesium, bicarbonate, carbonate, sulfate, chloride, nitrate, and fluoride were used for analysis. Pearson Correlation coefficient analysis showed strong and positive correlation between EC, HCO3−, and Cl−. Empirical Bayesian kriging (EBK) is used to interpolate the physio-chemical variables. In EBK interpolation, the lowest Root-Mean-Square Error (RMSE) and the standard error values were calculated for EC, HCO3−, SO4−, NO3−, Ca2+, Mg2+, and F− using K-Bessel model. The lowest RMSE value was calculated for pH (0.952), Cl−(1.016), Na+(0.905), and TH (0.979) using Whittle model of EBK interpolation technique. Results showed that north and north-east of the district are characterized by low groundwater quality and the north-west and central part of the district have very good groundwater quality. The very good WQI is covered by 1989.65 sq km (12.64%) of the study area.