Comparison of Sequential Indicator Simulation and Transition Probability Indicator Simulation Used to Model Clay Content in Microscale Surface Soil

Quantitative study of the spatial distribution of soil clay content is crucial to soil microecological research, soil physical and chemical properties, and agricultural and environmental management. In this article, the distribution of clay content within a 1-m soil body was selected as the study object. The soil clay content was measured with a laser grain-size analyzer and classified into indicator data. The spatial variability of the data was then analyzed by indicator variogram and transiogram. The results of the indicator variogram showed that the spatial distribution of clay content in a horizontal direction is highly random. However, the results of the transiogram of clay content exhibited obvious spatial juxtapositional tendencies both vertically and horizontally. Subsequently, sequential indicator simulation (SIS) and transition probability indicator simulation (TPROGS) were applied to create conditional realizations of the 1-m soil body. Finally, the realizations were validated by reproduction of a histogram, connectivity, as well as mean absolute error of prediction. The results indicated that the major textural classes were overestimated, whereas the minor classes were underestimated in the SIS-generated histogram, whereas all classes were well reproduced in the TPROGS. In addition, compared with the measured data, the connectivity of SIS realizations was significantly reduced, whereas the connectivity of TPROGS was coherent with measured data, which indicated that the crucial spatial characteristics, which were neglected by SIS, can be captured by TPROGS, even if the accuracy of prediction is similar. Therefore, the TPROGS method is a suitable method for characterizing the distribution of clay content in soil. The results may provide useful information for soil research.