Comparison of Spatial Interpolation Methods for Soil Available P in a Hilly Area

Three well-known spatial interpolation approaches, namely, kriging, inverse distance weighted, and slpine, were evaluated and used to identify hot-spots of soil available P in a hilly area. This study aims to evaluate different well-known spatial interpolation approaches for soil available P in a hilly area. Average Standard Error, Root Mean Square Error, Root Mean Square Standardized Error, and Mean Error were used to evaluate the performance of different methods. The krigingplus second trend effect model performed better than the inverse distance weighted and spline techniques in predicting soil available P spatial variability. The analyses of statistical and kriged map indicated that a general deficiency of soil available P in the study area.