Partha Pratim Adhikary

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

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.

Pedotransfer functions for predicting the hydraulic properties of Indian soils

Most of the data pertaining to Indian soils are limited to the major soil separates, sand, silt, and clay. We examined the possibilities of using these parameters to describe the hydraulic characteristics of the soils of India. The final or steady-state infiltration rate, which is mainly profile-controlled, showed a power function relationship with the maximum and the average clay content in the soil profile. The saturated hydraulic conductivity also showed a similar relationship with the silt + clay content. The soil water content at a given suction could be satisfactorily predicted using the percentage of major soil separates, sand, silt, and clay. The coefficients in the soil water function ψ(θ) were linearly related to the sand content. Non-linear regression equations were developed to predict these coefficients using the percentages of sand and clay in soils. The equations proved to be quite satisfactory for a wide range of textures and provided reasonably accurate estimates of the soil water characteristic curve from a minimum of readily available data.

Statistical approaches for hydrogeochemical characterization of groundwater in West Delhi, India.

Parametric statistical approaches, correlations and multiple linear regressions were used to develop models for the interpretation of hydrogeochemical parameters in the Western part of Delhi sate, India. The hydrogeochemical parameters indicated that the groundwater quality is not safe for consumption. The water is moderately saline and the salinity level is increasing over time. There is also the problem of nitrate pollution. The correlation between electrical conductivity (EC) and other water quality parameters except potassium (K+), nitrate (NO3−) and bicarbonate (HCO3−) is significantly positive and Ca++ + Mg++/Na+ + K+ is significantly negative. In predicting EC, the multiple R2 values of 0.996 and 0.985 indicate that 99.6% and 98.5% variability in the observed EC could be ascribed to the combined effect of Na+, HCO3−, Cl−, SO4−−, NO3− and Ca++ + Mg++ for the year of 2005 and 2006 respectively. Out of 99.6% of the variability in EC in 2005, 51.2% was due to Cl− alone, and 8.5%, 12.5%, 6.1%, 14.7% and 6.7% were due to Na+, HCO3−, SO4−−, NO3− and Ca++ + Mg++. Similarly in 2006, out of 98.5% of the variability in EC, 48.5% was due to Cl− alone, and 10.4%, 12.7%, 5.3%, 17.2% and 4.4% were due to Na+, HCO3−, SO4−−, NO3− and Ca++ + Mg++. The analysis shows that a good correlation exists between EC, Cl− and SO4−− either individually or in combination with other ions and the multiple regression models can predict EC at 5% level of significance.

Indicator and probability kriging methods for delineating Cu, Fe, and Mn contamination in groundwater of Najafgarh Block, Delhi, India

Two non-parametric kriging methods such as indicator kriging and probability kriging were compared and used to estimate the probability of concentrations of Cu, Fe, and Mn higher than a threshold value in groundwater. In indicator kriging, experimental semivariogram values were fitted well in spherical model for Fe and Mn. Exponential model was found to be best for all the metals in probability kriging and for Cu in indicator kriging. The probability maps of all the metals exhibited an increasing risk of pollution over the entire study area. Probability kriging estimator incorporates the information about order relations which the indicator kriging does not, has improved the accuracy of estimating the probability of metal concentrations in groundwater being higher than a threshold value. Evaluation of these two spatial interpolation methods through mean error (ME), mean square error (MSE), kriged reduced mean error (KRME), and kriged reduced mean square error (KRMSE) showed 3.52% better performance of probability kriging over indicator kriging. The combined result of these two kriging method indicated that on an average 26.34%, 65.36%, and 99.55% area for Cu, Fe, and Mn, respectively, are coming under the risk zone with probability of exceedance from a cutoff value is 0.6 or more. The groundwater quality map pictorially represents groundwater zones as “desirable” or “undesirable” for drinking. Thus the geostatistical approach is very much helpful for the planners and decision makers to devise policy guidelines for efficient management of the groundwater resources so as to enhance groundwater recharge and minimize the pollution level.