Understanding soil spatial variability and
identifying soil parameters most determinant to soil organic carbon
stock is pivotal to precision in ecological modelling, prediction,
estimation and management of soil within a landscape. This study
investigates and describes field soil variability and its structural
pattern for agricultural management decisions. The main aim was
to relate variation in soil organic carbon stock to soil properties and
to estimate soil organic carbon stock from the soil properties. A
transect sampling of 100 points at 3 m intervals was carried out.
Soils were sampled and analyzed for soil organic carbon and other
selected soil properties along with determination of dry aggregate
and water-stable aggregate fractions. Principal component analysis,
geostatistics, and state-space analysis were conducted on the
analyzed soil properties. The first three principal components
explained 53.2% of the total variation; Principal Component 1 was
dominated by soil exchange complex and dry sieved macroaggregates
clusters. Exponential semivariogram model described the
structure of soil organic carbon stock with a strong dependence
indicating that soil organic carbon values were correlated up to
10.8m.Neighbouring values of soil organic carbon stock, all waterstable
aggregate fractions, and dithionite and pyrophosphate iron
gave reliable estimate of soil organic carbon stock by state-space.
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