Calibration and validation of the SSSPAM coupled soilscape-landform evolution model for simulating short-term gully development on a post-mining landform

Post-mining landforms consist of unconsolidated waste, which can be highly erodible. In such structures of loosely bonded material, rill erosion and gully erosion are significant issues that lead to landform degradation. These landforms need to be designed to minimize erosion to ensure long-term stability and sustainability. Various landform evolution models (LEMs) have been used to predict the evolution of such landforms and identify areas prone to gully erosion. However, there is a degree of uncertainty associated with predictions made by LEMs due to the lack of field data that can be used to assess their accuracy. Here we use the State Space Soil Production and Assessment Model (SSSPAM) to simulate gully erosion on a post-mining landform. For the first time, we performed a qualitative and quantitative comparison between model predictions and field data of a post-mining landform using the SSSPAM model. SSSPAM is a coupled soilscape-landform evolution model that simulates fluvial erosion and armouring, diffusive erosion, deposition and physical weathering within the soil profile. Here, two sites on an active coal mine with active gullies evolving in waste rock were examined. In addition, novel methodologies for model calibration based on experimental flume data and model parameter modification procedures for conducting model simulations at different spatial and temporal scales are introduced. Site-specific erosion parameters, initial landform digital elevation models and the daily rainfall record of the site were used to simulate the evolution of gullies at the two different sites. Results show that SSSPAM can predict the gullies' position and general geomorphic characteristics with a high degree of accuracy.

Automated summary

This study simulated gully erosion on post-mining landforms using the SSSPAM model, and for the first time, qualitatively and quantitatively compared the model predictions with field data. The results showed that the SSSPAM model can accurately predict the position and general geomorphic characteristics of gullies.