Spatial Heterogeneity of Soil Metal Cations in the Plains of Humid Subtropical Northeastern India View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2016-12

AUTHORS

S. K. Reza, Utpal Baruah, S. K. Singh, R. Srinivasan

ABSTRACT

Analysis and interpolation of soil micronutrients are very important for site-specific management. The objective of this study was to determine the spatial distribution of iron (Fe), manganese (Mn), zinc (Zn) and copper (Cu) in the forest covered area of Chirang district, Assam, using statistics and geostatistics. A total of 607 soil samples from a depth of 0–25 cm at an approximate interval of 1 km were collected over the entire study area. The concentration of Fe, Mn, Zn and Cu ranged between 0.10–263.5, 0.50–149.5, 0.01–3.4 and 0.64–14.6 mg/kg, respectively, with mean values of 45.3, 19.6, 0.4 and 5.0 mg/kg, respectively. Analysis of semivariogram indicated that the Fe and Mn were well described with the spherical model, with the distance of spatial dependence being 5.83 and 1.95 km, respectively, while the Zn and Cu were well described with exponential model, with the distance of spatial dependence being 5.24 and 3.95 km, respectively. To define different classes of spatial dependence for the soil variables, the ratio of nugget and sill was used. Cu was strongly spatially dependent, with the nugget/sill being 0.202 in this given region, while Fe, Mn and Zn were moderately spatially dependent, with the nugget/sill being 0.347, 0.299 and 0.426, respectively. With the kriging analysis, the spatial distribution maps of contents of these four micronutrients in the study area were drawn with the ArcGIS software. It was found that the soils with higher content of Fe, Mn and Zn were mainly distributed in the upper area of the northern part of the study area, while the soils with higher content of Cu were mainly distributed in the center, decreasing toward the south, east and west. More... »

PAGES

346-352

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s40003-016-0217-7

DOI

http://dx.doi.org/10.1007/s40003-016-0217-7

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https://app.dimensions.ai/details/publication/pub.1003704596


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