Quantitative Evaluation of the Spatial Variation of Surface Soil Properties in Continuous Paddy Growing Fields

Abstract

Soil degradation caused by poor land management practices is a major impediment to optimal land productivity. Soil spatial variability is required for agricultural productivity, food safety and environmental modeling. Rice is one of the important food resources for most of the world’s population, especially in India and feeds more than 60 per cent population of the country. Telangana is on track to become India's rice bowl as rice production is expected to reach 1.3 crore tons in 2019–20.The present study was conducted in continuous paddy cultivated field of Machapur village of Siddipet district, Telangana, India to know the spatial variability of soil properties with a help of geostatistical model. For this, a total of 100 composite samples at 20*20 m grids in an area of 4 ha were collected. The pH of the soil, electrical conductivity (EC), organic carbon (OC), available nitrogen (N), phosphorus (P) and potassium (K) were all determined. The semivariogram model was used to create surface maps of soil properties using the ordinary kriging technique. The skewness values showed a normal distribution for all analyzed parameters except for Available K. Coefficient of variation ranged from 1.92% for pH to 34.08% for EC in topsoil indicating the heterogeneity of soil properties. Spherical model fits well with experimental semivariogram of pH, EC and AK. Exponential model better described the variation of soil OC and AN while the variation of AP was best described by Gaussian model. The soil pH, OC and available P were moderately spatially dependent whereas EC, available N and K were strongly spatially dependent. The cross validation results demonstrated the spatial prediction's smoothing effect. According to the findings of this study, a geostatistical model can directly reveal the spatial variability of lateritic soils and will assist farmers and decision makers in improving soil-water management.