Data-Driven Geospatial Assessment of Soil Parameters for Precision Agriculture in Banda District Using Geostatistical Techniques

Abstract

Spatial heterogeneity in soil fertility is important and determination of soil fertility at the field and regional scale levels is vital for precision agriculture and sustainable nutrient management. The study aimed to assess the spatial variability and fertility status of the major soil chemical properties in Banda District of Uttar Pradesh with the help of Geostatistical techniques. One thousand samples of soil were taken at 0–20 cm depth in a systematic manner and analyzed. The soil pH, electrical conductivity (EC), organic carbon (OC), available nitrogen (N), phosphorus (P), and potassium (K) were measured in the usual laboratory manner. Soil properties were described and mapped using ordinary kriging (OK) and inverse distance weighting (IDW) methods. The mean values of pH, EC, OC, N, P and K were 7.555, 0.807 dS m⁻¹, 0.491%, 252.60, 16.18 and 315.80 kg ha⁻¹, respectively. The lowest variability (CV = 10.25%) was found in pH and the highest is found in EC (CV = 50.43%). The results of the semivariogram indicated that all the soil properties were highly spatial dependent. The spherical model was found most appropriate for pH and P and the exponential model for the rest of the soil properties; IDW showed better spatial predictions results for pH, EC, N and K while OK showed better results for OC and P. The soil fertility maps indicated that the soils were generally moderately alkaline, with low to moderate salinity, low to medium organic carbon, low to moderate nitrogen, medium to phosphorous and medium to high in potassium. The results indicate that GIS-based geostatistical approaches are useful in identifying nutrient deficient areas. The soil fertility maps generated can aid in site specific nutrient management, better utilization of fertilizer, enhance soil productivity and help in sustainable precision agriculture in Bundelkhand region.