Daniel Adria, MSc Student, University of British Columbia

Biography:

Daniel was born and raised in Kelowna, BC, and attended the University of British Columbia. He earned his Bachelor’s of Civil Engineering with distinction in 2018. After graduation, Daniel was employed as an EIT for Knight Piesold. His experience in consulting includes hydrology and hydraulic studies for hydroelectric facilities and mining projects throughout BC and the world. The majority of his time was spent modelling dam breach events for hydroelectric facilities and tailings dams. These studies were conducted under Dr. Violeta Martin, an active member of the CDA Dam Safety Committee and international expert on tailings dam breach studies. Daniel returned to UBC for a Master’s of Applied Science in September 2020, supervised by Dr. Scott McDougall. After his degree, Daniel plans to return to consulting and use his academic experience to reduce uncertainty and risk for existing and proposed mining projects and their surrounding communities and environments.

Project: Impact of Dam Breach Parameters and Inputs on Tailings Dam Breach Runout Events

In conventional mining operations, the tailings and other waste materials are stored behind large dams. While extremely rare, these dams can and do fail with catastrophic societal and environmental impact, as shown by recent examples such as Mount Polley (Canada, 2014), Fundão and Feijão (Brazil, 2015 and 2019). Predicting these impacts is crucial for risk assessments and emergency preparedness. The physical processes that occur during the breach and runout are complex, inter-related, and poorly understood however, leading to large amounts of uncertainty in these estimates. Back analysis and modelling of the breach process and runout for up to 60 case histories is being performed. With this bank of modelled results, the trend of runout sensitivity to the uncertainties from breach characteristics can be quantified. By using these observed trends, forward analysis can be refined to address the greatest uncertainty for a given tailings facility and environment.