Assessing the Spatial Variability of Soil Quality Index of Ganjigatti Sub-Watershed Using GIS-Based Geostatistical Modeling

The present study was conducted to appraise the soil quality and its spatial variability from 393 surface soil samples of the Ganjigatti sub-watershed of Karnataka by using geospatial techniques. Principal component analysis was applied to identify the MDS from a set of fourteen soil quality indicators. The major factors that influence soil quality include pH, OC, available N, Zn, B, P and Mn. Six leading PCs were significant based on an eigenvalue of '>1' and explained 74.71% of the variance in soil parameters. SQI (Soil Quality Index) and RSQI (Relative Soil Quality Index) values ranged from 0.41 to 0.81 and 0.51 to 1.00 respectively. The geo-database was subjected to ordinary kriging through the best-fit experimental semivariogram based on the lowest root mean square error. The study concluded that the measured SQI (range 720.82 m) in regular gird sampling at a given scale was enough to capture spatial dependence using the ordinary kriging technique and to derive thematic maps for efficient soil management strategies at the sub-watershed level. The higher nugget: sill ratio (0.81) indicates that the spatial variability or dependency is primarily caused by stochastic factors. The SQI map of the Ganjigatti sub-watershed showed that about 9.69% of the sub-watershed had medium SQI (0.35-0.55), whereas 80.87% of the area had higher SQI (0.55-0.75).