Abstract

Changes in land use over time can induce spatial variability and these spatial variability patterns may be land use specific. Blanket nutrient management strategies that disregard spatial variability, not only cause economic losses but can impair soil and environmental quality and crop productivity. Geostatistical tools help better in capturing spatial variability than classical tools. This present study was conducted in three different land uses viz., berseem-based, rice–wheat, and poplar-wheat cropping systems prevalent in the northwestern part of India. A total of 144 geo-referenced surface soil samples were collected from these land uses and analyzed chemically to determine SOC and other physicochemical parameters. The highest amount of SOC was associated with poplar-based system, signifying thereby considerable potential for carbon sequestration. The experimental semivariograms models were computed to find the best fitted model for characterizing the spatial pattern of SOC. Gaussian model was found as the best fit for describing the spatial structure of SOC under berseem-based land use; on the other hand, spherical and exponential models were found suitable for rice–wheat and poplar-wheat systems, respectively. The nugget:sill ratio (NS ratio) of SOC was 0.21 for poplar-wheat based land use, suggesting strong spatial dependence, whereas the other land uses exhibited moderate spatial dependence (Berseem based=0.65; Rice-wheat=0.35). Spatial variability maps of SOC were generated using ordinary kriging (OK) technique which helped identify management zones within a field.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call