GEOSTATISTICAL ASSESSMENT OF SOIL FERTILITY IN A SEMI-ARID REGION USING SPATIAL INTERPOLATION TECHNIQUES

Abstract

The foundation of agricultural sustainability and productivity is soil, a crucial but limited natural resource. This study uses geostatistical analysis and spatial interpolation techniques to evaluate soil fertility, which is defined by both nutrient availability and management. The study, which was carried out in Jari Village, in the Badokhar Khurd block of Banda district in the Bundelkhand region, used secondary data on important soil characteristics, such as pH, electrical conductivity, organic carbon, and N, P, and K concentrations. To assess spatial variability throughout the study area, 300 soil samples were gathered at uniform depths and subjected to analysis. Discrete data points were transformed into continuous surface maps appropriate for Geographic Information System (GIS)-based analysis using spatial interpolation techniques like IDW and OK. To optimize IDW parameters and identify the best semi-variogram model for OK, cross-validation techniques were used. The findings showed that OK was better at mapping the distribution of potassium, but IDW was better at predicting the majority of soil parameters. While soil salinity was minimal and in line with the region's moderately alkaline pH, there was notable variation in pH, OC, N, P, and K levels throughout the region. The effectiveness of geostatistical tools in enhancing soil fertility assessments and assisting precision agriculture in areas with limited resources is demonstrated by this study.