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The aim of the research is to compare spatial prediction methods: (RBF), (IDW), (OK), (UK), and (SK) for the production of the groundwater level map and the prediction error map in study area as well. Setting the foundations and criteria for choosing the most appropriate mathematical method for the construction of statistical surfaces in the representation of the level of groundwater in study area. These methods were used to predict the spatial distribution map of the groundwater level based on measured data from 764 wells in May 2016. The study reveals that comparing the spatial interpolation models and evaluating their accuracy, through some statistical indicators and cross-validation is the best way to choose the optimal model for the representation of data entered in any site. As a result of the statistical comparison between the five spatial interpolation models and validation of the results using (cross validation) it was found that the universal Kriging (UK) method is the best method to represent the level of groundwater in Salman district because this model has the lowest root mean square error (RMSE), the lowest mean error (ME), and the highest coefficient of determination (R2) value. The groundwater level and prediction standard error maps produced in the geographic information system (GIS) give additional data and information that describe the aquifer system in study area and will ultimately improve sustainable groundwater management.

Comparison and Evaluation of GIS-Based Spatial Interpolation Methods for Estimation Groundwater Level in AL-Salman District—Southwest Iraq