Predicting the spatial distribution of sulfate concentration in groundwater of Jampur-Pakistan using geostatistical methods

Abstract

In this study, we investigate the spatial distribution of sulfate concentration in groundwater of tehsil Jampur, Pakistan using geostatistical techniques. Sulfate concentration in drinking water causes chronic diseases like stomach disorder, diarrhea, laxative effects, and food poisoning in human beings, particularly in infants. First, 30 water samples were collected with their spatial coordinates to evaluate the spatial variation and distribution of sulfate concentration in groundwater of tehsil Jampur. Then, we evaluated the assumptions of normality and autocorrelation in the spatial data and used Matern covariance model to assess the correlation structure of response variable (random field). Furthermore, we applied ordinary least square and weighted least square to estimate the variogram parameters. Two interpolation methods, Ordinary Kriging and Bayesian Kriging were used to predict the unmonitored locations within the studied domain. Performance of the interpolation methods was assessed through leave-one-out cross validation. The predictive maps showing results of both the methods are expected to be helpful to the administrative policy-makers in providing safe drinking water.

Keywords:

• Spatial mapping
• Variogram
• Health effects
• Isotropy
• Bayesian Kriging

Acknowledgments

The authors acknowledge the editor and two anonymous reviewers for detailed review and suggestions to improve the article.