Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Master of Engineering Science

Program

Civil and Environmental Engineering

Supervisor

Power, Christopher

Abstract

Coal mining activities can leave an extensive network of abandoned underground workings that gradually flood after operations cease. This rising mine water, with low pH and high sulfate, acidity, and metals can lead to uncontrolled releases of harmful acid mine drainage to the environment. Treatment plants are used to extract and treat the mine water to maintain its elevations below suspected discharge zones. Accurate predictions of long-term water quality is highly challenging due to the complexity and volume of the underground workings. As numerical models have difficulty recreating complex mine pool geometry and hydrogeochemical processes, empirical models that are based on Younger’s ‘first-flush’ phenomenon, where mine water concentrations peak shortly after flooding and then exponentially decline, may provide better long-term predictive modeling. The objective of this study was to assess the robustness of ‘first-flush’ empirical models for describing and predicting mine water behavior at large, complex mine pools in The Sydney Coalfield (Nova Scotia, Canada). Numerous mine pools in the coalfield flooded at various times over 100+ years, allowing long-term mine water evolution to be studied in various pools of different ages. Analysis of extensive historical data from the older pools demonstrated that the evolving mine water quality, both overall and within each stratified layer, followed the ‘first-flush’ phenomenon. ‘First-flush’ trends were consistent across differing depths, water quality parameters (acidity, sulfate, iron), and concentration ranges. Two newer mine pools, which recently flooded in 2012, rely on a new active treatment plant to manage mine water levels below discharge points. Using behavioral conditions observed in the older mines, such as decay rate, ‘first-flush’ based empirical models were calibrated and validated to early mine water quality data collected at the treatment plant bi-weekly between 2012 and 2021. They were then used to predict future mine water quality and estimates of long-term treatment requirements and related expenses.

Summary for Lay Audience

Closed and abandoned mine tunnels underground can often fill-up with contaminated water that can damage the environment and ecosystems if it is allowed to escape. To prevent this from happening, mine water treatment plants are often constructed to pump out and treat this contaminated water so it does not fill-up the mine tunnels and spill over into the environment. These treatment plants are expensive infrastructure projects, often requiring millions of dollars to construct and operate. It is important to understand the long-term behavior and changes that happen to this mine water so that the treatment infrastructure can be designed and operated as good as possible. However, modeling these flooded underground mine workings is a very expensive and difficult task because of the size and complexity of these systems. Numerical models are often used in these situations as they can model in detail the physical and chemical processes that take place. However, numerical models often require data about the exact layout of the mine workings, which may be unknown or unreliable. Empirical models are more simple and less expensive and they are based only on analyzing the quality of the water after it was collected from the mine workings. Empirical models take a ‘higher-level’ approach to predict the water quality, going off of actual water data, changes and trends, instead of trying to model all the details and processes that make the water change.

This study collected and analyzed mine water sampling data from the historic Sydney Coalfield that is located in Nova Scotia, Canada, and a easy-to-use and low cost empirical model was developed to understand how the mine water changes over time. It was found that: (i) empirical models can accurately predict the behavior and changes in the mine water, and (ii) water quality is expected to get much better over the coming decades, which will result in less expenses in the treatment operations. The results of this study provide critical information needed for the planning and management of mine water treatment infrastructure, which can be used to protect the environment.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

Share

COinS