An Integrated Remote Sensing-Numerical Modeling Approach for Monitoring Tailings Dam

Tailings dams are used to store water and waste that come as by-products from the mining process. They can be huge in size, as big as lakes, and reach 300 meters high.
Tailings storage facilities can pose a threat to local wildlife and ecosystem, especially in the case of failure. In Canada, the Mount Polley copper-gold mine dam collapsed in 2014 and released 25 million cubic meters of wastewater and tailings, including huge amounts of toxic elements like arsenic, lead and mercury, into adjacent water systems and lakes (Pyle et al. 2022). This is why regular maintenance and monitoring is vital to ensure that the dam is strong enough to contain the mining waste.
An automated method is introduced in this project for remote monitoring of the tailings dams, which can prevent the potential failure or leakage using an early warning system. The numerical stability model is also employed to predict the behavior of tailing dams during their different life stages.

Faculty Supervisor:

Kamran Esmaeili

Student:

Partner:

Kinross Gold

Discipline:

Engineering

Sector:

Mining

University:

University of Toronto

Program: