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Development of Mineral Environmental Assessment Methodologies
Task 2 - Development of Mineral Environmental Assessment Techniques at the Watershed Scale

Methods to Evaluate Uncertainty

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Subtask Contact: Mike Friedel

Subtask Objectives

Statement of Work


Subtask Objectives

Mining activities pose uncertain space- and time-dependent hazards. Examples of uncertain mining hazards can include deteriorating infrastructure, engineering and environmental failures, and waste rock and tailings piles. The possibility of harm from uncertain mining-related hazards that lead to personal damage is called risk. Examples of mining-related risk can include the likelihood of damage to property and/or health (human and/or ecological). Whereas about 90% of all mining liabilities are associated with waste rock, tailings, and mine water management, there are several deficiencies in their assessment. First, their currently is no consistent framework to forecast and/or evaluate scale-and time-dependent mining hazards (present or future) and their risks. Second, there is a need by scientists to improve spatial and temporal risk analysis by incorporating relevant model predictions and their uncertainty.

In many cases, however, there are no relevant numerical models. Even where numerical models exist, the success to provide reliable estimates and predictions depends on the ability to couple disparate numerical models and perform appropriate calibration and validation. Because field models have elements that are complex and unpredictable, and are calibrated using limited field measurements, traditional validation methods are weak and predictions uncertain. Methods must be developed and applied for quantitative evaluation and assessment of uncertainty in the mineral environmental assessment process.

Subtasks objectives are listed below:

  1. Develop a nationally consistent environmental framework for forecasting and evaluating environmental mining risk.
  2. Develop and apply methods and strategies for numerical model calibration, validation, and quantification of prediction uncertainty.

Statement of Work

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