Developing a Process-based Sediment Transport Model to Capture the Interplay between Particle-scale Dynamics, Geomorphic Evolution and Fluxes in Intensively Managed Landscapes

Prediction of hillslope erosion in Intensively Managed Landscapes is one of the most challenging problems in the area of sediment transport because it is governed by complex interactions between rainfall, flow, topography, roughness, and soil properties. Existing sediment transport models often oversimplify underlying mechanisms to obtain a solution at the expense of failing to represent the system. Typical model limitations include quasi-steady approximations, neglection of particle-scale dynamics, and fixed bed assumptions. These limitations hinder model performance, particularly at smaller scales where responses are highly nonlinear. The goal of this study is to gain fundamental understanding on the interactions between particle-scale dynamics, geomorphic evolution and fluxes, and develop a process-based modeling framework that can bypass existing limitations. To accomplish this goal, state-of-the-art rainfall simulation experiments were conducted on plots in US Midwest, that accommodated observations and data acquisition at high spatial and temporal resolution. Collected data include ultra-high-resolution digital laser scans of the bed prior to and after the experiment, flow depths, flow and bedload velocities, and runoff and sediment flux signals. Findings reveal the existence of two characteristic timescales, governed by the geomorphic evolution stages of the soil bed and characterized by the dominance of different entrainment mechanisms. A new process-based model is developed, informed, and verified using the unique experimental database of this study, that can capture the stochastic nature of entrainment mechanisms, encompasses dynamic two-dimensional algorithms for routing flow and sediemnt, and captures the geomorphic evolution of the bed. Comparisons of model results with observed data show very good model performance and highlight the model's advantage over existing deterministic models. This study sets the stage for the development of next-generation sediment transport models with the capability of incorporating complex particle-scale mechanisms for accurate prediction of runoff and sediment fluxes and aiding the optimal design of Best Management Practices.