Spatial variability of Soil Macronutrients on Basaltic landscape of Central India: A Geostatistical approach

Spatial Variability of Soil Macronutrients on Basaltic landscape of Central India: A Geostatistical Approach

Nisha Sahu*, G.P. Obi reddy, Nirmal Kumar, M.S.S. Nagaraju, Rajeev Srivastava and S.K. Singh

ICAR-National Bureau of Soil Survey and Land Use Planning, Amravati Road, Nagpur-440 033, India

Keywords: Spatial variability, Semivariogram, Cross-validation, Soil properties, GPS

https://doi.org/10.37273/chesci.cs172050121 • PDF

Abstract

A study was conducted to interpolate and to explore the analysis of spatial variability of major soil nutrients in Basaltic Terrain of Nagpur district, Maharashtra. A total of 235 soil samples (0-25 cm) were collected grid wise at an interval of 250 m using GPS. Soil chemical properties i.e. available nutrients (N, P and K) were measured in laboratory. After normalization, data were interpolated by Ordinary Kriging (Spherical, Exponential and Gaussian). The performance of methods was evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Goodness of prediction (G) obtained from a cross-validation procedure. The results showed that Ordinary Kriging (Spherical Model) was the best method to estimate available N and K whereas Gaussian Model fits well with highest precision for estimation of available P in this area. Available P and K have displayed moderate spatial dependence whereas Available N showed strong spatial dependence. Cross validation of kriged map showed that spatial prediction of soil nutrients using semi variogram parameters is better than assuming mean of observed value for any unsample location. Therefore, it is a suitable alternative method for accurate estimation of soil properties in unsampled positions as compared to direct measurement which has time and costs concerned.

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