Hillslope erosion in a grassland environment: Calibration and evaluation of the SIBERIA landscape evolution model. Issue 4 (17th January 2021)

• Record Type: Journal Article
• Authors: Hancock, G.R.; Gibson, Abraham; Wells, T.
• Is Part Of: Earth surface processes and landforms. Volume 46:Issue 4(2021)
• Page Start: 728
• Page End: 743
• Publication Date: 2021-01-17
• Subjects: 137Cs -- flume -- environmental tracer -- landscape evolution model -- SIBERIA -- soil erosion; Geomorphology -- Periodicals; 551.4
• DOI: 10.1002/esp.5060
• Languages: English
• ISSNs: 0197-9337

Abstract

Abstract: Field measurement and modelling of soil erosion provides insights into landscape systems as well as the potential for enhanced landscape management. There are a number of field and numerical methods by which soil erosion and deposition can be quantified. Here we examine the capability of the SIBERIA landscape evolution model to quantify short‐term erosion and deposition on a well‐managed cattle grazing landscape on the east coast of Australia. The model is calibrated by two methods (1) a geomorphological approach using a site digital elevation model (DEM) and soil data and (2) a laboratory‐scale flume. The two calibration processes resulted in similar model input parameters and estimated erosion rates of 3.1 t ha −1 year −1 and 4.4 t ha −1 year −1, respectively. These were found to closely match erosion rates estimated using the environmental tracer 137 Cs (2.7–4.8 t ha −1 year −1 ). However, erosion and deposition estimated at individual points along the hillslope was not well correlated with 137 Cs at the same position due to the temporal averaging of the model and microtopography. Sensitivity analysis showed the model was more sensitive to parameterisation than sub‐DEM‐scale topography. This places confidence in the model's ability to estimate erosion and deposition across an entire hillslope and catchment on decadal time scales. We also highlight the robustness and flexibility of the calibration methods. Abstract : Computer based landscape evolution models can provide reliable soil erosion estimates. They can also predict patterns of erosion and deposition.