Rock avalanche runout prediction using stochastic analysis of a regional dataset

Mitchell, A.; McDougall, Scott; Nolde, Natalia; Brideau, Marc-André; Whittall, John; Aaron, Jordan

doi:10.1007/s10346-019-01331-3

Cited by 39 publications

(51 citation statements)

References 27 publications

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“…The regression model for the Zone 1 runout distance ( Figure 8B) shows a strong association between the runout distance, volume, fall height and whether or not the topography is laterally confined. These results are consistent with those reported in Mitchell et al (2020). The effect of topographic confinement on the Zone 1 impact area was tested, but the uncertainty on the estimate was too high to be used for the regression equation (see Supplementary Material).…”

Section: Discussionsupporting

confidence: 85%

“…The quantitative and qualitative attributes used in this study to describe the Zone 1 impact areas are consistent with the terms used in Mitchell et al (2020). The attributes used to describe the Zone 1 and Zone 2 impact areas are shown in Table 1.…”

Section: Dataset Compilationmentioning

confidence: 77%

“…The runout length is also estimated using multiple linear regression of the dataset. The path topography in the Zone 1 area was considered as an indicator variable, consistent with Mitchell et al (2020). The regression model for Zone 1 runout is:…”

Section: Methodsmentioning

confidence: 99%

“…This inconsistency is problematic when assessing rock avalanche hazard and risk because many empirical and numerical runout prediction methods that are used for this purpose (e.g., McDougall, 2017) are based on statistical analyses or model calibration approaches that implicitly rely on consistent case study data. Runout prediction methods that use case study datasets that include prehistoric events where distal mass flow impacts were not recognized, or datasets that are based exclusively on the mapped extents of coarse rocky deposits (e.g., Mitchell et al, 2020), may underestimate potential rock avalanche impacts unless suitable adjustments are made to the predictions. Furthermore, there is little information currently available in order to make a well constrained estimate of the likelihood of a mass flow occurring due to a rock avalanche.…”

Section: Introductionmentioning

confidence: 99%

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Rock Avalanche-Generated Sediment Mass Flows: Definitions and Hazard

et al. 2020

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Rock avalanches can trigger destructive associated hazards following the initial collapse and fragmentation of a rock slope failure. One of these associated hazards occurs when the material derived from the initial collapse of the source zone impacts and mobilizes a mass flow composed of sediment from along the travel path. These mass flows can be grouped into radial impact areas that occur on relatively flat, open terrain (typically a floodplain), and more linear impact areas that occur in channelized terrain. Rock avalanche-generated sediment mass flows are an important consideration because they can significantly increase the area impacted by an event, thereby increasing the hazard area, especially in valley bottoms where there are likely more elements at risk. Existing runout prediction methods do not consistently account for the increase in the impact area from rock avalanche-generated sediment mass flows. Thus, there is a need for a simple data-supported method for estimating the extent of mass flow impacts resulting from an initial rock avalanche event with sediments along the potential travel path. This paper presents data from 32 rock avalanches and 23 rock avalanche-generated sediment mass flows from around the world, described using a consistent set of quantitative and qualitative attributes. A wide range of mass flow impacts were observed, with the sediment mass flow impact area or runout length exceeding the impact of the coarse, rocky debris in some cases. The area and length impacted by the coarse, rocky debris is estimated using multiple linear regressions considering the event volume and topographic features. The sediment mass flow dataset is used as input to develop an exponential distribution of the area or runout length of the sediment mass flow over that of the coarse, rocky debris. A decision tree framework is presented for estimating the extent of potential rock avalanches and potential rock avalanche-generated sediment mass flows for hazard and risk analysis, which is demonstrated by comparing the stochastic empirical predictions to those from numerical runout modeling.

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Section: Discussionsupporting

confidence: 85%

Section: Dataset Compilationmentioning

confidence: 77%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Rock Avalanche-Generated Sediment Mass Flows: Definitions and Hazard

et al. 2020

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“…The fahrboshung angle from the Joffre Peak source area to the highway is 0.2 and the highway grade is 19 m above the distal margin of the Cerise Creek fan. Based on these values, a landslide of sufficient volume to reach Highway 99 is unlikely (Mitchell et al 2019).…”

Section: Impactsmentioning

confidence: 99%

Observations on the May 2019 Joffre Peak landslides, British Columbia

et al. 2020

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Two catastrophic landslides occurred in quick succession on 13 and 16 May 2019, from the north face of Joffre Peak, Cerise Creek, southern Coast Mountains, British Columbia. With headscarps at 2560 m and 2690 m elevation, both began as rock avalanches, rapidly transforming into debris flows along middle Cerise Creek, and finally into debris floods affecting the fan. Beyond the fan margin, a flood surge on Cayoosh Creek reached bankfull and attenuated rapidly downstream; only fine sediment reached Duffey Lake. The toe of the main debris flow deposit reached 4 km from the headscarp, with a travel angle of 0.28, while the debris flood phase reached the fan margin 5.9 km downstream, with a travel angle of 0.22. Photogrammetry indicates the source volume of each event is 2-3 Mm 3 , with combined volume of 5 Mm 3 . Lidar differencing, used to assess deposit volume, yielded a similar total result, although error in the depth estimate introduced large volume error masking the expected increase due to dilation and entrainment. The average velocity of the rock avalanche-debris flow phases, from seismic analysis, was~25-30 m/s, and the velocity of the 16 May debris flood on the upper fan, from superelevation and boulder sizes, was 5-10 m/s. The volume of debris deposited on the fan was~10 4 m 3 , 2 orders of magnitude less than the avalanche/debris flow phases. Progressive glacier retreat and permafrost degradation were likely the conditioning factors; precursor rockfall activity was noted at least~6 months previous; thus, the mountain was primed to fail. The 13 May landslide was apparently triggered by rapid snowmelt, with debuttressing triggering the 16 May event.

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