Assessing the long-term evolution of mine water quality in abandoned underground mine workings using first-flush based models

Coal mining activities can leave an extensive network of abandoned underground workings that gradually flood after operations cease. This rising mine water can eventually lead to uncontrolled releases of harmful acid mine drainage (AMD) to the environment. Treatment plants are used to extract and treat the mine water to maintain its elevation below suspected discharge points. Accurate predictions of long-term water quality, and treatment plant operations, are highly challenging due to the complexity and volume of the underground workings. As numerical models require considerable effort to effectively implement, empirical models that are based on the 'first-flush' phenomenon, where mine water concentrations peak shortly after flooding and then exponentially decline, may provide suitable long-term predictions. The objective of this study was to assess the robustness of first-flush based models for describing mine water behavior at large, complex mine pools in the Sydney Coalfield (Nova Scotia, Canada). Numerous mine pools across the coalfield flooded at various times over 100+ years, with extensive mine water quality data available in various pools of different ages. The historical evolution of mine water quality demonstrated first-flush behavior across key AMD indicator parameters (acidity, sulfate, iron), concentration ranges, and mine pool depths. Two 'newer' mine pools, which only flooded in the past 10-15 years, rely on an active treatment plant to manage mine water levels below environmental discharge points. Influent water quality from each mine pool was sampled bi-weekly between 2011 and 2022, and first-flush models were then applied to predict the future quality of mine water entering the treatment plant over the long-term. Knowledge on long-term influent quality can help to optimize treatment plant requirements and related expenses.