Testing a low-complexity model to decompose the multitemporal dynamics of soil erosion and sediment delivery in agricultural catchments

Abstract

Testing and improving the capacity of soil erosion and sediment delivery models to simulate the response of soil erosion to the intra-annual dynamics of climatic drivers and disturbances (e.g., vegetation clearcutting, tillage events, wildfires) is critical to understand intolerable soil loss and catchment sediment yields. Here, we approach the trade-off between the need for model simplicity and temporally dynamic predictions by testing the ability of a low-complexity, spatially distributed model (WaTEM/SEDEM), to decompose the 15-day dynamics of soil erosion and sediment yield. A standardised RUSLE parameterisation and model implementation routine was applied to four arable-dominated catchments in North-West Europe with open-access validation data. We firstly show that when applied to simulate the multitemporal dynamics of sediment delivery, a standard assumption of a temporally static transport capacity within the model structure mostly cannot adequately replicate the multitemporal variability of sediment delivery. Instead, optimising a 5-parameter splines curve to determine the temporal profile of the transport capacity coefficient (ktc) based on the monthly average sediment yield improved the model performance and revealed clear seasonality in the sediment transport efficacy. Despite simulating similar temporally aggregated sediment yields, the introduction of seasonal dynamics into the transport capacity further caused a net reduction in the magnitudes of the spatially distributed sediment fluxes, compared to a temporally lumped approach. Published catchment observations infer this seasonality in sediment transport efficiency to attribute abundant vegetative boundaries in summer and increased soil crusting and runoff promotion in winter. Models operating at temporally aggregated timescales should account for the possibility of decoupling in time and space between gross erosion and sediment delivery related to these alternations between transport- and detachment-limited sediment transport capacity states. Despite the complexities and uncertainties involved in the temporal downscaling of WaTEM/SEDEM, we show the utility of this approach to: 1) link optimised multitemporal parameters to key missing model information components which may reduce error in gross erosion predictions (e.g. more consideration of antecedent soil conditions), 2) form a basis for strategically adding physical process-representation, with a focus on maintaining low model complexity while improving predictive skill, and 3) better understand the interdependencies between spatial fluxes and multitemporal dynamics when undertaking model predictions at large spatial and temporal scales.