A Review of Process-Based Landform Evolution Models for Evaluating the Erosional Stability of Constructed Post-Mining Landscapes

Understanding landform evolution is essential for assessing how terrain responds to geomorphic drivers such as weathering, fluvial erosion, hillslope processes, and tectonic uplift. This is particularly important in applications such as constructed post-mining landform rehabilitation, where predicting long-term erosional stability is vital for sustainable closure planning. In addition to long-term average erosion rates, the spatial patterns of gullies, rills, and channels are critical for assessing landform stability. This review examines Digital Elevation Model (DEM)—driven, process-based Landform Evolution Models (LEMs), with a primary focus on SIBERIA, CAESAR-Lisflood, and SSSPAM, which are widely used to evaluate the erosional behaviour of constructed post-mining landforms, each with distinct characteristics. These models are systematically compared in terms of input requirements, process representations, parameterisation, and predictive capabilities. Recent advances in high-spatial resolution DEMs (e.g., LiDAR, SRTM), along with digital soil and rainfall databases and satellite-derived vegetation indices, have improved the parameterisation of erosion, hydrological, and sediment-transport processes of the LEMs. A brief comparative case study is presented to demonstrate how these LEMs simulate 1000-year erosional behaviour along a linear hillslope. This review synthesises the current capabilities and limitations of DEM-driven LEMs, providing guidance for researchers, land managers, and practitioners in selecting appropriate models to support sustainable post-mining landform management, as well as outlining potential future advancements.