Comparison of Gis-Based Interpolation Methods to Predict Spatial Variation of Major Soil Chemical Properties in Mana District, Jimma Zone, Southwest Ethiopia

Abstract

Soil fertility mapping is essential for optimizing agricultural practices and management. This study was conducted in Mana district, southwestern Ethiopia. It aimed at evaluating and comparing three GIS-based spatial interpolation methods (Inverse Distance Weighting: IDW; Ordinary Kriging: OK; and Ordinary Cokriging: OCK) for estimating selected soil chemical properties, and producing a set of accurate maps of selected soil chemical properties. The study included 84 geo-referenced soil samples collected in April 2021 at 0 - 30 cm depth across the entire district, using the systematic sampling technique with 2.5 km × 2.5 km grid. The soil samples were analyzed for selected chemical properties. Descriptive statistics were first applied to the data to evaluate and validate the normal distribution required for geostatistical analysis. The performance of each interpolation method was assessed using cross-validation. The descriptive statistical analyses revealed that besides the topographic aspect which were highly variable, available phosphorus (AP) and available potassium (AK) were the most variable soil properties (CV > 35%); while pH, soil organic carbon (SOC) and total nitrogen (TN) contents were moderately variable (CV varying from 16.28% to 30.53%). Only pH and SOC were normally distributed among all the variables. When comparing the resulting values of the efficiency criteria of cross-validation (RMSE, MRE and RI) for each interpolation method, the OCK technique was best performed for all the five soil chemical properties with lower values of RMSE and MRE, and the best RI. However, for the TN, OK showed the same performance as OCK. Interpolated maps were generated based on OCK for each soil property and indicated their distribution throughout the study area of Mana.