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Research Article Open access CC BY 4.0

Mapping of Soil Micronutrients (Fe, Mn, Cu, Zn) in the Transition Zone of Northwestern Foothill of Shivaliks of Kathua District Using GIS

Vishaw Vikas, K. R. Sharma, Vikas Sharma, Vivak M. Arya, Rajeev Bharat

International Research Journal of Pure and Applied Chemistry · pp. 115–121 · Published 11 Aug 2020

10.9734/irjpac/2020/v21i1130228

Abstract

Aim: To analyze and map the soil micronutrient status in the transition zone of NW foothills of Shivaliks of Kathua Region using GIS. Methodology: Composite surface soil samples from two hundred and six (206) locations distributed randomly due to undulated topography across the whole of the district were collected at the depth of 0-15 cms using global positioning system (GPS). Inverse distance weighting (IDW) technique was adopted to generate prediction maps of the soil properties. The process of digitization and generation of maps was carried out with ArcGIS 10.3. Results: After soil sample analysis, the available copper content in the soil of hilly areas varies from 0.4 to 14.4 mg kg-1 with a mean value of 3.75 mg kg-1. Available Zinc content ranged from 0.25 to 5.60 mg/kg respectively. The available Manganese content of the surface soils varied between 5.60 to 78.10 mg kg-1 with a mean value of 23.97 mg kg-1. Available Iron content ranged from 11.30 to 92.00 mg/kg with a mean value of 38.57 mg kg-1. The available copper content in the soil of plain areas varies from 2.08 to 34.90 mg kg-1 with a mean value of 8.94 mg kg-1. The minimum and maximum values of available copper content lies in higher range. Available Zinc content ranged from 0.25 to 5.60 mg kg-1 respectively. According to the map, available zinc is visualized lowest in plains due to raised soil pH. The available manganese content of the surface soils varied between 2.500 to 57.40 mg/kg with a mean value of 27.03 mg kg-1. Available Iron content ranged from 0 to 66.10 mg kg-1 with a mean value of 41.68 mg kg-1. Conclusion: The mapping was done successfully with micronutrients varying from low to high range. The technique was found to be effective in identifying the micronutrients availability throughout the study region, thereby helping policy makers to frame fertilizer distribution and application policy for future.

Iron (Fe) manganese (Mn) copper (Cu) zinc (Zn) IDW GPS ArcGIS

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