Assessing soil erosion on a rehabilitated landform using the CAESAR landscape evolution model ©
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Authors: Lowry, JBC; Coulthard, TJ; Hancock, GR; Jones, DR |
DOI https://doi.org/10.36487/ACG_rep/1152_64_Lowry
Cite As:
Lowry, JBC, Coulthard, TJ, Hancock, GR & Jones, DR 2011, 'Assessing soil erosion on a rehabilitated landform using the CAESAR landscape evolution model ©', in AB Fourie, M Tibbett & A Beersing (eds), Mine Closure 2011: Proceedings of the Sixth International Conference on Mine Closure, Australian Centre for Geomechanics, Perth, pp. 613-621, https://doi.org/10.36487/ACG_rep/1152_64_Lowry
Abstract:
The ability to predict the stability of post-mining landscapes through time scales ranging from decades to thousands of years is a critical element in the assessment of closure designs for uranium mines. Landscape Evolution Models (LEMs) can provide information on soil erosion rates at decadal or centennial temporal scales, over large spatial scales and evaluate the sensitivity of these processes to environmental changes. In this paper, the CAESAR LEM is tested for its ability to predict soil erosion from a series of 30 x 30 m experimental plots constructed on a trial rehabilitated landform at the Ranger Uranium Mine in the Northern Territory, Australia. Data inputs required by the model (particle size distribution and rainfall time series) were obtained from field measurements made during the 2009–10 wet season. A very high resolution (20cm) digital elevation model of each erosion plot was produced from a laser scan of the surface. The erosion rates predicted by the model were compared with time series field measurements of suspended sediment and bedload. This is the first time that predictions from an LEM have been assessed against field measurements at such high spatial and temporal resolution scales. Once the model had been calibrated for the specific site hydrological conditions, the predicted loads for both bedload and suspended sediment demonstrated excellent agreement with the field data. Erosion data collected through subsequent wet seasons will provide the opportunity to assess how well the model predicts the evolution of the surface erosion properties through time as the surface weathers and vegetation develops.
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