Computational experiments on the 1962 and 1970 landslide events at Huascarán (Peru) with r.avaflow: Lessons learned for predictive mass flow simulations

Mergili, Martin; Frank, B.; Fischer, Jan-Thomas; Huggel, Christian; Pudasaini, Shiva P.

doi:10.1016/j.geomorph.2018.08.032

Cited by 85 publications

(73 citation statements)

References 52 publications

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“…tres away from the source and have led to major disasters in the past, such as the 1949 Khait rock avalanche-loess flow in Tajikistan (Evans et al, 2009b), the 1962 and 1970 Huascarán rockfall-debris avalanche events in Peru (Evans et al, 2009a;Mergili et al, 2018b), the 2002 Kolka-Karmadon ice-rock avalanche in Russia (Huggel et al, 2005), the 2012 Seti River debris flood in Nepal (Bhandari et al, 2012), or the 2017 Piz Cengalo-Bondo rock avalanche-debris flow event in Switzerland. The initial fall or slide sequences of such process chains are commonly related to a changing cryosphere characterized by glacial debuttressing, the formation of hanging glaciers, or a changing permafrost regime (Harris et al, 2009;Krautblatter et al, 2013;Haeberli and Whiteman, 2014;Haeberli et al, 2017).…”

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confidence: 99%

Back calculation of the 2017 Piz Cengalo–Bondo landslide cascade with r.avaflow: what we can do and what we can learn

Mergili

Jaboyedoff

Pullarello

et al. 2020

Nat. Hazards Earth Syst. Sci.

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128

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Abstract. In the morning of 23 August 2017, around 3×106 m3 of granitoid rock broke off from the eastern face of Piz Cengalo, southeastern Switzerland. The initial rockslide–rockfall entrained 6×105m3 of a glacier and continued as a rock (or rock–ice) avalanche before evolving into a channelized debris flow that reached the village of Bondo at a distance of 6.5 km after a couple of minutes. Subsequent debris flow surges followed in the next hours and days. The event resulted in eight fatalities along its path and severely damaged Bondo. The most likely candidates for the water causing the transformation of the rock avalanche into a long-runout debris flow are the entrained glacier ice and water originating from the debris beneath the rock avalanche. In the present work we try to reconstruct conceptually and numerically the cascade from the initial rockslide–rockfall to the first debris flow surge and thereby consider two scenarios in terms of qualitative conceptual process models: (i) entrainment of most of the glacier ice by the frontal part of the initial rockslide–rockfall and/or injection of water from the basal sediments due to sudden rise in pore pressure, leading to a frontal debris flow, with the rear part largely remaining dry and depositing mid-valley, and (ii) most of the entrained glacier ice remaining beneath or behind the frontal rock avalanche and developing into an avalanching flow of ice and water, part of which overtops and partially entrains the rock avalanche deposit, resulting in a debris flow. Both scenarios can – with some limitations – be numerically reproduced with an enhanced version of the two-phase mass flow model (Pudasaini, 2012) implemented with the simulation software r.avaflow, based on plausible assumptions of the model parameters. However, these simulation results do not allow us to conclude on which of the two scenarios is the more likely one. Future work will be directed towards the application of a three-phase flow model (rock, ice, and fluid) including phase transitions in order to better represent the melting of glacier ice and a more appropriate consideration of deposition of debris flow material along the channel.

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confidence: 99%

Back calculation of the 2017 Piz Cengalo–Bondo landslide cascade with r.avaflow: what we can do and what we can learn

Mergili

Jaboyedoff

Pullarello

et al. 2020

Nat. Hazards Earth Syst. Sci.

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128

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“…This work should be seen as a first step in the direction of simulating real multi‐phase mass flows. Several important aspects can further be considered when simulating multi‐phase flows: Interaction processes are the key drivers to cause transitioning from one dynamic mass flow regime to another, eventually leading to a cascading mass flow event (Mergili, Emmer, et al, ; Mergili, Frank, et al, ). Interactions with the basal sliding surface and with water bodies are most relevant for rapid gravity‐driven mass flows.…”

Section: Discussion and Future Perspectivesmentioning

confidence: 99%

“…• Interaction processes are the key drivers to cause transitioning from one dynamic mass flow regime to another, eventually leading to a cascading mass flow event (Mergili, Emmer, et al, 2018;Mergili, Frank, et al, 2018). Interactions with the basal sliding surface and with water bodies are most relevant for rapid gravity-driven mass flows.…”

Section: Discussion and Future Perspectivesmentioning

confidence: 99%

“…Key parameters (densities, internal and basal friction angles, and kinematic viscosities with proper units) characterizing each of the three phases in Test 1, and Test 2 are as follows (where the first, second, and third 10.1029/2019JF005204 entries correspond to solid, fine-solid, fluid phases respectively): = (2700, 1800, 1000); = (35, 10, −); = (15, 5, −); = (−, 10 2 [Test1]or 10 3 [Test 2], 10 −3 ). More detailed and physically constrained values of these parameters can be found in the literature (Domnik et al, 2013;Enos, 1977;Hampton, 1975;Johnson, 1996;Mergili et al, 2017;Mergili, Emmer, et al, 2018;Mergili, Frank, et al, 2018;Pierson, 1970;Takahashi, 2007;von Boetticher et al, 2016).…”

Section: Benchmark Numerical Simulationsmentioning

confidence: 99%

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A Multi‐Phase Mass Flow Model

2019

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Geomorphic mass flows are often complex in terms of material composition and its evolution in space and time. The simulation of those hazardous phenomena would strongly benefit from a multi‐phase model, considering the motion and—importantly—interaction of phases characterized by different physical aspects including densities, frictions, viscosities, fractions, and their mechanical responses. However, such a genuine multi‐phase model is still lacking. Here, we present a first‐ever, multi‐mechanical, multi‐phase mass flow model composed of three different phases: the coarse solid fraction, fine‐solid fraction, and viscous fluid. The coarse solid component, called solid, represents boulders, cobbles, gravels, or blocks of ice. Fine‐solid represents fine particles and sand, whereas water and very fine particles, including colloids, silt, and clay, constitute the viscous fluid component in the mixture. The involved materials display distinct mechanical responses and dynamic behaviors. Therefore, the solid, fine‐solid, and fluid phases are described by Coulomb‐plastic, shear‐ and pressure‐dependent plasticity‐dominated viscoplastic, and viscosity‐dominated viscoplastic rheologies. They are supposed to best represent those materials. The new model is flexible and addresses some long‐standing issues of multi‐phase mass flows on how to reliably describe the flow dynamics, runout, and deposition morphology of such type of phenomena. With reference to some benchmark simulations, the essence of the model and its applicability are discussed.

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“…Parameterization of 328 both scenarios is complex and highly uncertain, particularly in terms of optimizing the volumes of entrained till and 329 glacial meltwater, and injected pore water. In general, the parameter sets optimized to yield empirically adequate re-330 sults are physically plausible, in contrast to Mergili et al (2018b) who had to set the basal friction angle in a certain 331 zone to a negligible value in order to reproduce the observed overtopping of a more than 100 m high ridge (1970 low mobility of the flow in Zone E. This is achieved by increasing the friction (Table 1), accounting for the narrow 334 flow channel, i.e. the interaction of the flow with the channel walls, which is not directly accounted for in r.avaflow.…”

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confidence: 99%

Back-calculation of the 2017 Piz Cengalo-Bondo landslide cascade with r.avaflow

Mergili

Jaboyedoff

Pullarello

et al. 2019

Preprint

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Abstract. In the morning of 23 August 2017, around 3 million m3 of granitoid rock broke off from the east face of Piz Cengalo, SE Switzerland. The initial rock slide-rock fall entrained 0.6 million m3 of a glacier and continued as a rock(-ice) avalanche, before evolving into a channelized debris flow that reached the village of Bondo at a distance of 6.5 km after a couple of minutes. Subsequent debris flow surges followed in the next hours and days. The event resulted in eight fatalities along its path and severely damaged Bondo. The most likely candidates for the water causing the transformation of the rock avalanche into a long-runout debris flow are the entrained glacier ice and water originating from the debris beneath the rock avalanche. In the present work we try to reconstruct conceptually and numerically the cascade from the initial rock slide-rock fall to the first debris flow surge and thereby consider two scenarios in terms of qualitative conceptual process models: (i) entrainment of most of the glacier ice by the frontal part of the initial rock slide-rock fall and/or injection of water from the basal sediments due to sudden rise in pore pressure, leading to a frontal debris flow, with the rear part largely remaining dry and depositing mid-valley; and (ii) most of the entrained glacier ice remaining beneath/behind the frontal rock avalanche, and developing into an avalanching flow of ice and water, part of which overtops and partially entrains the rock avalanche deposit, resulting in a debris flow. Both scenarios can be numerically reproduced with the two-phase mass flow model implemented with the simulation software r.avaflow, based on plausible assumptions of the model parameters. However, these simulation results do not allow to conclude on which of the two scenarios is the more likely one. Future work will be directed towards the application of a three-phase flow model (rock, ice, fluid) including phase transitions, in order to better represent the melting of glacier ice, and a more appropriate consideration of deposition of debris flow material along the channel.

show abstract

Computational experiments on the 1962 and 1970 landslide events at Huascarán (Peru) with r.avaflow: Lessons learned for predictive mass flow simulations

Cited by 85 publications

References 52 publications

Back calculation of the 2017 Piz Cengalo–Bondo landslide cascade with r.avaflow: what we can do and what we can learn

Back calculation of the 2017 Piz Cengalo–Bondo landslide cascade with r.avaflow: what we can do and what we can learn

A Multi‐Phase Mass Flow Model

Back-calculation of the 2017 Piz Cengalo-Bondo landslide cascade with r.avaflow

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