Evaluation of groundwater quality parameters using GIS and Geostatistical (case study: Urmia plain)

In this research, the goal of evaluating the accuracy of interpolation methods is for prediction of spatial distribution of some of the quality indices of groundwater in Urmia plain. In the beginning, the qualitative data of 20 wells in the year 2001-2014 were analyzed. The Kolmogorov-Smirnov test showed that the data were not normal and therefore the conversion of the box-cox was used to normalize, Then, using the GIS software, the best semivariogram model was fitted to the spatial structure of the data. The results showed that for qualitative parameters, circular, spherical, and exponential models are the best model for semivariogram. Then, their variation was study with different interpolation methods such as Kriging and Inverse Distance Weight with power of one to three. Then, the zoning maps of qualitative parameters were drawing with the most appropriate method in the ArcGIS software. Plain aquifer was also examined for Wilcox and Schoeller standards for agricultural and drinking purposes. The results of the Wilecox standard showed that 40% of the wells in the plain had brine and available for use in agriculture, and the results of the Schoeller diagram showed the good and acceptable quality of the groundwater for drinking water.