Prediction of acid and metalliferous drainage for greenfield projects

Theme: Earth science and resources

Description: 

Accurate prediction of AMD generation is complicated by the need to upscale results from small-scale laboratory tests to field conditions (Morin & Hutt, 2001). Laboratory tests are conducted under controlled environments that often accelerate weathering and sulfide oxidation, whereas field conditions are characterised by heterogeneous waste rock, variable water infiltration, gas flow, and fluctuating temperatures (Morin & Hutt, 1997). Methodological limitations, such as the inability to account for spatial heterogeneity, dynamic hydrological processes, and extended temporal scales, undermine the reliability of AMD predictions. Previous studies (Vriens et al., 2019) in cold climates such as Alaska and Peru revealed that leaching occurs primarily during warming periods, rather than continuously as laboratory models suggest. In arid regions like northern Chile, episodic leaching and evaporation-driven suppression of drainage contradict steady-state laboratory assumptions (Tapia et al., 2018). Reliable AMD prediction requires integrated approaches that combine laboratory testing with site-specific field trials, adaptive monitoring, and waste classification schemes that consider both physical and chemical parameters.

Additional Information: This project explores how upscaling laboratory-derived data from bench-top kinetic leaching columns to a mesoscale can improve understanding and prediction of AMD risk in waste rock dumps located in cold and dry climates.

Contact: Assoc Professor Carlos Spier / Prof. Mansour Edraki