ALBERT

Description: Intrinsic and extrinsic forces on the catchment and stream channel network drive morphological change. Separating individual forcings is difficult given the complexity of such non-linear systems. Here a modelling approach is used to investigate the sensitivity of channel position and movement under a series of realistic rainfall scenarios for a catchment in South-Eastern Australia. The results demonstrate the sensitivity of the catchment to different rainfall patterns and how relatively small changes in rainfall can lead to much larger sediment outputs revealing sensitivity to subtle changes in climate. Channel movement occurs as an avulsion. This is the first time such a process has been observed and modelled in an ephemeral stream environment and demonstrates fluvial geomorphic change at human time scales. Human intervention by rock lining channels was demonstrated to prevent the movement of the main channel. Overall the CAESAR landscape evolution and erosion model used in this study is able to replicate both erosion rates and the variation in past channel movement. The modelling suggests that any landscape change is based on both internal and external forcing and that landscape history also plays a significant role. Here we demonstrate the potential to quantify many of the nonlinearities and thresholds in soil-mantled catchments using a landscape evolution model. Copyright © 2011 John Wiley & Sons, Ltd.

Description: We examine the capability of a landscape evolution model (LEM) to predict both soil erosion rate and pattern of erosion and deposition. The outputs from this numerical model (SIBERIA) was compared to field measured soil redistribution rates and patterns determined using the environmental tracer 137Cs. SIBERIA can approximate these independently quantified erosion and deposition patterns and rates suggesting that LEMs can be a reliable alternative to complex and time consuming methods such as that using environmental tracers for the determination of erosion rates. Abstract Excessive soil erosion and deposition is recognised as a significant land degradation issue. Quantifying soil erosion and deposition is a non‐trivial task. One of these methods has been the mathematical modelling of soil erosion and deposition patterns and the processes that drive them. Here we examine the capability of a landscape evolution model to predict both soil erosion rate and pattern of erosion and deposition. This numerical model (SIBERIA) uses a Digital Elevation Model (DEM) to represent the landscape and calculates erosion and deposition at each grid point in the DEM. To assess field soil redistribution rates (SRR) and patterns the distribution of the environmental tracer 137Cs has been analysed. Net hill slope SRR predicted by SIBERIA (a soil loss rate of 1.7 to 4.3 t ha‐1 yr‐1) were found to be in good agreement with 137Cs based estimates (2.1 – 3.4 t ha‐1 yr‐1) providing confidence in the predictive ability of the model at the hillslope scale. However some differences in predicted erosion/deposition patterns were noted due to historical changes in landscape form (i.e. the addition of a contour bank) and possible causes discussed, as is the finding that soil erosion rates are an order of magnitude higher than likely soil production rates. The finding that SIBERIA can approximate independently quantified erosion and deposition patterns and rates is encouraging, providing confidence in the employment of DEM based models to quantify hillslope erosion rates and demonstrating the potential to upscale for the prediction of whole catchment erosion and deposition. The findings of this study suggest that LEMs can be a reliable alternative to complex and time consuming methods such as that using environmental tracers for the determination of erosion rates. The model and approach demonstrates a new approach to assessing soil erosion that can be employed elsewhere. © 2018 John Wiley & Sons, Ltd.