Parameter Calibration in a Process-Based Soil Depth Estimation Model Assuming Local Steady State

Soil thick ness is one of the fundamental components in many hydrological and slope stability models. Since landform critically influences many slope processes, soil thickness which is related to various slope processes is also highly affected by topography. In this study, a soil production function is also highly affected by topography. In this study, a soil production function is coupled with a simple diffusion model to form a soil-thickness prediction model. The Chiching Shan area in the Yuan-Ming-Shan National Park is chosen as a study area to test the validity of the model. It is assumed that the topography has not had any drastic change during the simulation time period, the soil is moving downhill according to simple creep law, which sets the transport flux equal to a linear function of local slope gradient, and its transport rate is in equilibrium with the soil production rate at ridge lines. Model parameters are calibrated under this local steady-state assumption, and used to estimate the soil thickness within the study area. The simulated soil depths in the study area range from 0 to 2 meters, and their spatial variations are controlled by topographic curvature. Field verification shows that the model performs well on the upper parts of hillslope where low gradient convex slope forms dominate. It is discovered that in area where slope processes other than diffusion prevail, significant disparity appears between model simulated and the measured soil depth. Generally speaking, the adoption of the local steady state assumption facilitates parameter calibration and model application. However, in order to further improve the model’s applicability, mechanisms involved in other hillslope processes must be incorporated in future model development.