A reconstructed landscape may exert long-term influences on its surrounds and behave in ways that may not be predictable given uncertainties regarding climate, soil and vegetation interactions (Evans, 2000). In recent years, computer-based landscape evolution models (LEM) have been used to assess potential and existing mining landscapes and their long-term geomorphic behaviour (Hancock et al, 2007; Hancock, Lowry and Coulthard, 2015; Tucker and Hancock, 2010).In this paper, we focus on the evolution of post-mining landforms, which are designed to include burial or encapsulation of mine-impacted areas and materials, including tailings, drains, spoil tips and other industrial architecture (Figure1). At the Ranger Uranium mine in the Northern Territory of Australia, low-grade uranium ore, tailings, brines and other mine wastes will be buried at depth in the areas of the former pits and tailings storage facilities.The use of LEMs to predict long-term landscape evolution has several issues. These include that model predictions are based on the calibration and parameterisation of the model carried out using values determined from present day, or recent surface conditions. Furthermore, there is also the question as to how subtle perturbations or roughness on the DEM surface can produce alternative model results by randomly varying the elevations of the DEM surface.In this study we examine the effect on sediment transport rates and geomorphology for a proposed rehabilitated landform using multiple landscape realisations with increasing magnitudes of random changes in the DEM using the SIBERIA LEM (Willgoose, Bras and Rodriguez-Iturbe, 1991).CITATION:Hancock, G R, Coulthard, T J and Lowry, J B C, 2016. Use of landform evolution models to assess uncertainty in long-term evolution of post-mining landscapes, in Proceedings Life-of-Mine 2016 Conference, pp67-70 (The Australasian Institute of Mining and Metallurgy: Melbourne).