Lowry, JBC, Saynor, MJ, Hancock, G & Coulthard, TJ 2022, 'A catchment-scale comparison of field observations of a constructed landform with erosion predictions from a landscape evolution model', in AB Fourie, M Tibbett & G Boggs (eds), Mine Closure 2022: Proceedings of the 15th International Conference on Mine Closure, Australian Centre for Geomechanics, Perth, pp. 1169-1178, https://doi.org/10.36487/ACG_repo/2215_86
(https://papers.acg.uwa.edu.au/p/2215_86_Lowry/)
Abstract: Rehabilitation has commenced at the Ranger uranium mine in the Northern Territory of Australia. The Ranger rehabilitated landform is required to contain tailings material for a period of at least 10,000 years, and to produce erosion rates that eventually correspond with those of the surrounding undisturbed landscape. Landscape evolution models (LEMs) provide a means of predicting how a rehabilitated landform may evolve over extended periods of time. In this study, we utilised optical imagery acquired from remotely piloted aircraft (RPA), and ground-based observations to identify gully/drainage line development on the newly constructed Pit 1 landform over the period from 2020 to 2021. The Pit 1 landform encompasses an area of approximately 40 hectares and is the first part of the Ranger landform to be rehabilitated. We compare these observations with predictions from the CAESAR-Lisflood LEM of gully development over the same 12-month period. This work builds on earlier work undertaken to calibrate the CAESAR-Lisflood model at an erosion plot scale on the Ranger mine and applies it at a larger spatial scale. Over the one-year period, the model was able to predict the development of drainage lines in similar places to those observed via imagery and on-ground observations on the constructed Pit 1 landform. While acknowledging the limitations of a study of only 12 months duration, the results here provide confidence that the parameters used in the model are appropriate for predicting gully erosion at the larger catchment scale of this study, and that the results are relevant for extended time periods.

Keywords: erosion, landform, modelling, drones