Comparison of two deterministic interpolation methods for predicting ground water level in Baghdad

Abstract EN

Surface interpolation techniques are commonly employed for creating continuous data (raster data) from a distributed set of data points over a geographical region.

In this paper, the comparison between two spatial interpolation techniques (Natural Neighbouring (NN) and Inverse Distance Weighting (IDW)) is done.

The goal is to determine which method creates the best real representation of measured ground water levels in Baghdad Governorate.

Raster surface generation (ground water prediction map) is obtained for each method by using average ground water level measured at 206 wells in the study area.

These maps show spatial variation in the ground water level and they are quite different.

IDW method results a smoother map and lesser error than NN method.

Thus, the analysis shows that IDW creates a better representation of reality for measuring ground water levels in Baghdad Governorate.