Spatial distribution prediction for the ground water quality in Mosul City (Iraq) using variogram equations

Abstract

Spatial distribution prediction for the ground water quality in Mosul City (Iraq) using variogram equations. The GIS-aided spatial interpolation was applied on collected groundwater data to predict selected parameters (i.e., pH, electrical conductivity, and temperature) for the selected water wells distributed over Mosul City in Iraq. A descriptive statistical analysis was conducted on collected samples to explore the statistical indices. The skewness test was also employed to test the distribution of data sets around their mean values. The natural logarithms function achieved least skewness values and thus was applied to transfer data sets in order to adjust normality of the data sets distribution. Among all applied semivariogram models, the J-Bessel semivariogram model was optimal in terms of root mean square error (RMSE) values. The average standard errors were 0.2217, 740.5, and 1.209 for pH, EC, and temperature, respectively.