My research focus is on the runout behaviour of rapid, flow-like landslides. It is difficult to estimate the area impacted by these events, and the intensity of those impacts, due to many sources of uncertainty. In many cases it is not practical (or possible) to eliminate this uncertainty, my focus is on applying probabilistic methods to empirical and numerical predictions of flow-like landslide runout to quantify the uncertainties. The objective is to develop predictive tools that can be used in assessing risks or designing mitigation measures in areas potentially affected by landlsides.
Mitchell, A., McDougall, S., Whittall, J., Brideau, M-A., and McClarty, D., 2018. New empirical-statistical tools for the analysis of rock avalanche runout. Geohazards 7.
Mitchell, A., Lato, M., McDougall, S., Porter, M., Bale, S., and Watson, A., 2017. Regional-scale landslide and erosion monitoring utilizing airborne LiDAR change detection analysis. Geological Society of America 129th Annual Meeting.
Mitchell, A. and Hungr, O., 2017, Theory and calibration of the Pierre 2 stochastic rock fall dynamics simulation program. Canadian Geotechnical Journal 54: 18 – 30.
Mitchell, A. and Hungr, O., 2015, PIERRE 2: A stochastic rock fall simulator – development, calibration and applications. GEOQuébec 2015, the 68th Conference of the Canadian Geotechnical Society.
Preh, A., Mitchell, A., Hungr, O., and Kolenprat, B, 2015, Stochastic analysis of rock fall dynamics on quarry slopes. International Journal of Rock Mechanics & Mining Sciences, 80: 57 – 66.
Gischig, V., Hungr, O., Mitchell, A., and Bourrier, F., 2015, Pierre3D – a 3D stochastic rock fall simulator based on random ground roughness and hyberbolic restitution coefficients. Canadian Geotechnical Journal, 52: 1360 – 1373.