Runout Prediction for Open Pit Slope Failures
John Whittall, Erik Eberhardt
Geological Engineering, Department of Earth, Ocean & Atmospheric
Sciences – University of British Columbia, Vancouver, BC, Canada
Derek Kinakin
BGC Engineering Inc., Kamloops, British Columbia, Canada
ABSTRACT
The April 10, 2013 pit wall failure and debris runout at Kennecott’s Bingham Canyon mine has increased regulatory and
industry interest in the prediction of the initiation and areas potentially affected by large rock slope failures. A common
approach to assessing the hazard posed by rockslide runouts involves the use of probabilistic empirical models using
concepts such as the “angle of reach” and “energy grade line”. These have been developed solely based on natural rock
slope failures and the suitability of these empirically derived models has yet to be validated for open pit slopes.
A database of open pit slope failures has been compiled and compared to existing empirical methods with promising
results. A variety of failure modes, rock types, slope design criteria, and debris volumes are used for benchmark testing
each method. Probabilistic methods are appropriate in a mining context as failures inherently related to geological
uncertainty require subjective judgement and time to assess deterministically. Economic constraints on personnel and
equipment withdrawal thresholds leave little time for detailed deterministic analyses and often don’t warrant such
precision.
Discrepancies from general trends developed for natural rock slope failures are related to the mining process and open
pit geometry. In contrast to natural slope failures, open pits create a catchment confining debris runout and alter failure
path behaviour at the opposing wall. Also material retention on berms may reduce the runout volume and consequent
path length. Nonetheless the dataset of failed open pit slopes superimposed on established empirical methods shows
general agreement. Incorporating runout prediction into the mine plan may offer opportunities to manage the failed
material and protect assets such as ramps, dewatering wells/drains, and equipment. Simple probabilistic runout
prediction methods described here are a useful starting point to help practitioners identify hazard zones and mitigate
loss.