GEOSTATISTICAL ANALYSIS OF SOIL MICRONUTRIENTS BASED ON GIS AND GEOSTATISTICS-A CASE STUDY

J.B. KAMBALE¹*, D. BASAVARAJA², K.A. HIREMATH³, N.H. SUNITHA^4
1Department of Soil and Water Engineering, College of Agriculture, Bheemarayanagudi-585287, Karnataka
²Department of Environmental Science, Collage of Agriculture, Bheemarayanagudi, 585287, Karnataka
³Department of Agronomy, Collage of Agriculture, Bheemarayanagudi, 585287, Karnataka
⁴Department of Home Science, Collage of Agriculture, Bheemarayanagudi, 585287, Karnataka
* Corresponding Author : jbkambale@gmail.com

Received : 10-09-2016     Accepted : 18-09-2016     Published : 30-10-2016
Volume : 8     Issue : 52       Pages : 2606 - 2609
Int J Agr Sci 8.52 (2016):2606-2609

Keywords : Geographic Information System (GIS), Geostatistical analysis, Inverse Distance Weighted (IDW), Soil Micronutrients
Academic Editor : Dr A Rajarathinam
Conflict of Interest : None declared
Acknowledgements/Funding : None declared
Author Contribution : None declared

Understanding of spatial variability in soil fertility status is vital for application of site specific nutrient management. For this a total 25 number of Soil samples collected from Vandurga Village, Yadgir District of Karnataka and analysed for Sulphur(S), Calcium Carbonate (CaCO3), Manganese (Mn), Zinc (Zn), and Iron (Fe). Here geostatistics used to execute conventional statistical analysis and ArcGIS and Geostatistical software GS+ to get the information about distribution and spatial variability of soil micronutrients. The S of collected soil samples varied from 23.98 ppm to 68.62 ppm with a mean of 42.48 ppm. The CaCO3 ranged from 6.61 ppm to 19.85 ppm with an average of 12.02 ppm. Available Mn ranged from 0.52 ppm to 9.48 ppm with mean of 4.09 ppm. The CV for CaCO3 was 34.28, while for Mg, Zn, and Fe it was 68.52, 104.35 and 96.60 respectively. Geostatistical analysis of study by GS+ (version 10.0) show the results based on the ratio of nugget and sill, soil micronutrient properties in study area, the exponential model is used well to show the spatial structure of Sulphur (S) and the ratio of nugget and sill is 97.2%. This shows the variability of S is weakly spatially dependent. Similarly for Ca and Fe fitted Semi variogram Spherical model and Mn and Zn fitted with Gaussian semivariogram model. For CaCO3 and Fe the ratio of nugget and sill is 51.6 % and 57.5% respectively and for Mn and Zn the ratio of nugget and sill is 84.2 % and 99.8% respectively. This study also show the usefulness of GS+ (version 10.0) and ArcGIS 9.2 to know the spatial variability of soil micronutrients in the study area as well as for spatial interpolation, mapping and geostatistical analysis.