Uncertainty Assessment for Delineating the Spatial Patterns of Soil Organic Carbon Using Sequential Gaussian Simulation

摘要

Sequential Gaussian simulation (SGS) and soil organic carbon (SOC) data of 175 soil profiles in Hebei Province of China were used in this study for evaluating the potential use of SGS in uncertainty assessment of SOC spatial pattern characterization. Results derived from 500 times of SGS indicated that the conditional variance is large in the northwest of Hebei Province where the SOC density (SOCD, to a depth of 1m) fluctuates the most and mountainous areas are the dominated relief;while the uncertainty of SOCD spatial characterization is much smaller in plain areas (southeast) where SOCD values are consistently small. The realizations generated by SGS presented the possible spatial patterns of SOCD without smoothing effect,thereby provided a visual and quantitative measure of uncertainties for delineating the spatial patterns of SOC.