Comparison Between Deterministic and Stochastic Interpolation Methods for Predicting Ground Water Level in Baghdad

Abstract

Surface interpolation techniques are usually used to create continuous data (i.e. raster data) from distributed set of point data over a geographical region. There are deterministic and stochastic (geostatistical) interpolation techniques can be used to create spatial raster surface. In this paper, the comparison between the Inverse Distance Weight (IDW) interpolation method as deterministic method and the Kriging interpolation method as stochastic method is done to determine the best performance for measuring levels of ground water in Baghdad Governorate. Spatial raster surface surfaces as ground water prediction maps are generated from each method by using average ground water level measured at 206 wells in the study area. These maps are shown spatial variation in the ground water levels and they have complete different. The IDW method results a refined map and lesser error than the Kriging method. Thus, the analysis shows that the IDW gives better real performance of measuring levels of ground water in Baghdad Governorate.