Incorporating Uncertainty into Dam Closure Risk Assessments
Creators: Al-Mohamad, Marwa
Publisher: name: University of Alberta Library
Year: 2023

<p>Best practice guidance of dam safety management mandates the application of risk assessment in all stages of the lifecycle of dams: design, construction, operation, closure and post closure. Risk can be defined as a measure of the probability and severity of an adverse effect on the public, environment and property (CDA, 2013). Risk assessment is one of the dam risk management system components that provides an answer to the question, “Is the dam safe enough?”<br><br>
Site-specific dam information  is critical for conducting a risk assessment. This information could be missing, incomplete or outdated, which identifies many sources of uncertainties regarding the availability of information (AI).  Uncertainties could also be due to geotechnical assumptions, methods used in site investigation, analysis, and design and will be referred to as quality of available information (QAI).  Conducting the risk assessment without considering the level of uncertainty in AI and QAI could be misleading. Limited AI could lead to unconsidered high risks, while a lack of QAI could lead to a false interpretation of risk. Confidence in the risk assessment outcomes is related to both the quality of dam information and its availability.  Insufficient information and substandard analyses would increase epistemic uncertainty, which would result in low confidence in the estimated risk.<br>
Tailings dams have some added characteristics that may contribute to more AI and QAI challenges than water dams. These challenges are amplified when conducting a long-term risk assessment of facilities. The characteristics include material sources, geochemistry, multi staging in construction, impounding a mix of saturated tailings solids and water (instead of only water) and overlapping the design-construction-operation sequence. Tailings dam properties are site-specific and this contributes to limiting the amount of information that can be shared among sites. Further, there are competing interests with safety goals such as profitability of an operation, which can lead to low levels of AI and QAI if the organization does not have a robust safety management culture.<br>
For long-term risk assessments of tailings dams, not only the current properties of a particular element are needed, but also it is important to include the potential future changes of these properties. While the behaviour of tailings dams components is well documented against known failure modes throughout the active stage, much less is understood about the aging processes that tailings ponds and their dams undergo and how a dam will evolve over time. This challenge increases the complexity of conducting a long-term risk assessment. Additionally, given that risk assessments are required for the long term  (i.e., in excess of 100 years), the ownership of a facility may be transferred before the risk-assessment period has expired. It is critically important to have an effective data management plan and to communicate information through changes of personnel and ownership.  In order to forecast the long-term behaviour of these facilities, we must have reliable site-specific information about a dam, where reliable information is defined as information that is subject to quality assurance and on ongoing review to ensure its validity and accuracy.<br><br>
This research evaluates the effects of AI and QAI uncertainties on the potential success of long-term risk assessment of tailings dams. A framework to incorporate the uncertainty into the risk assessments was developed using the most recent state-of-practice risk-analysis tool. The sources of AI and QAI uncertainties affecting the confidence in the estimated risks in tailings dams were identified through the framework based on the industry experience gathered through site visits to western Canadian tailings dams sites. <br>
With many of Alberta’s coal mine tailings dams scheduled to close by 2030, a case study from the coal mining industry in Alberta was selected to test the uncertainty evaluation framework. The findings of the case study application are based on our assumptions and hypothetical scenario using site data as a guide and do not reflect the actual risks at the site. The selected failure modes were assessed following closure activities when the closed facility may be at its greatest risk of failure prior to reaching equilibrium.  The discussed failure modes have high uncertainty based on the available information and the assumptions. Incorporating these uncertainties through the closure risk assessment poses a low confidence level in the risk estimation</p>