Variability modeling and mapping of soil properties for improved management in Ethiopia

Abstract Managing soils for improved agricultural production requires information on soil fertility status. Our objective was to map better management in Ethiopia and determine their spatial correlation at a separation distance of 29 m. We collected 82 samples (0–20 cm depth) 560 ha land determined pH, Olsen extractable phosphorus (Olsen‐P), organic carbon (OC). then interpolated between sample points (ordinary kriging‐OK weighting‐IDW [inverse weighting]) evaluate dependence. Olsen‐P ranged from 2.68–42 mg/kg exhibited high variability with coefficient variation (CV) ≥35%. Conversely, pH showed low (CV ≤ 15%) ranging 4.84 6.81. Soil OC content varied 0.81% 3.17%. The IDW ( R 2 = 0.86; RMSE 0.019) outperformed the OK. semivariogram results indicate strong dependence spherical, exponential, Gaussian models, while moderately spatially auto correlated all models. OK predict (moderately acidic), (low), (very low) contents. maps may help improve alternatives, increase crop productivity, secure environmental quality.