Uncertainty Assessment for Delineating the Spatial Patterns of Soil Organic Carbon Using Sequential Gaussian Simulation
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.
climate change soil organic carbon (SOC) spatial pattern uncertainty modelling
Xianghua Xu Yongcun Zhao
Nanjing University of Information Science and Technology, Nanjing 210044, China Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
国际会议
南京
英文
89-92
2010-05-08（万方平台首次上网日期，不代表论文的发表时间）