The feasibility of predicting the spatial pattern of soil particle-size distribution using a pedogenesis model

Abstract

Particle-size distribution (PSD) plays an important role in influencing a number of soil physical, chemical, and biological properties. Currently, digital soil mapping (DSM) methods based on empirical observations have been widely used in mapping PSD. However, DSM methods rarely consider soil genetic processes. This paper investigated the use of a mechanistic soil evolution model, State Space Soil Production and Assessment Model (SSSPAM), to simulate the spatiotemporal evolution of PSD in the Hunter Valley, NSW, Australia. SSSPAM simulates the spatial and temporal variation of PSD within a landscape based on erosion due to overland flow, deposition, and physical weathering within the soil profile. We conducted a simulation over the 144 km2 area using a 30 m digital elevation model (DEM) as an input. The model simulated soil evolution over 70,000 years to ensure that the PSD had reached steady-state. To validate and analyze the influence of different process parameters on particle size dynamics, we carried out a parametric study in a field within the study area and found a strong relationship between runoff excess generation, exponential weathering rate, and soil particle-size distribution. As expected, higher discharge rates produced coarser particles and larger weathering rates produced finer PSD. We further explored the feasibility of combining the mechanistic SSSPAM and empirical DSM approaches by comparing simulation results with observed sand content. We found limitations of the SSSPAM model to predict sand fraction accurately in the study area due to incomplete process coverage. The output of SSSPAM can be improved by integrating it with DSM techniques. Overall, SSSPAM can explore how particle size will change through time and identify areas with risks of erosion and deposition. Such a model can be used to inform large-scale management to ensure our soil is secured in the future.