Comparing Flow-R, Rockyfor3D and RAMMS to Rockfalls from the Mel de la Niva Mountain: A Benchmarking Exercise

Author:

Noël François12ORCID,Nordang Synnøve Flugekvam3,Jaboyedoff Michel1ORCID,Digout Michael4,Guerin Antoine5,Locat Jacques6,Matasci Battista4

Affiliation:

1. Risk Analysis Group, Institute of Earth Sciences, University of Lausanne, CH-1015 Lausanne, Switzerland

2. Geohazard and Earth Observation Team, Earth Surface and Seabed Division, Geological Survey of Norway (NGU), NO-7491 Trondheim, Norway

3. Rambøll Norge AS, NO-7493 Trondheim, Norway

4. BEG SA, CH-1994 Aproz (Nendaz), Switzerland

5. Norbert SA, Engineering Geology and Hydrogeology, CH-1920 Martigny, Switzerland

6. Natural Hazards Study Laboratory (LERN), Department of Geology and Geological Engineering, Laval University, Québec City, QC G1V 0A6, Canada

Abstract

Rockfall simulations are often performed at various levels of detail depending on the required safety margins of rockfall-hazard-related assessments. As a pseudo benchmark, the simulation results from different models can be put side-by-side and compared with reconstructed rockfall trajectories, and mapped deposited block fragments from real events. This allows for assessing the objectivity, predictability, and sensitivity of the models. For this exercise, mapped data of past events from the Mel de la Niva site are used in this paper for a qualitative comparison with simulation results obtained from early calibration stages of the Flow-R 2.0.9, Rockyfor3D 5.2.15 and RAMMS::ROCKFALL 1.6.70 software. The large block fragments, reaching hundreds of megajoules during their fall, greatly exceed the rockfall energies of the empirical databases used for the development of most rockfall models. The comparison for this challenging site shows that the models could be improved and that combining the use of software programs with different behaviors could be a workaround in the interim. The findings also highlight the inconvenient importance of calibrating the simulations on a per-site basis from onsite observations. To complement this process, a back calculation tool is briefly described and provided. This work also emphasizes the need to better understand rockfall dynamics to help improve rebound models.

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Reference83 articles.

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2. Jones, C.L., Higgins, J.D., Andrew, R.D., and Colorado Rockfall Simulation Program (2021, January 10). Available online: https://coloradogeologicalsurvey.org/publications/colorado-rockfall-simulation-program/.

3. Labiouse, V. (2004). Landslides: Evaluation and Stabilization/Glissement de Terrain: Evaluation et Stabilisation, Set of 2 Volumes, CRC Press.

4. Marui, H., and Matjaž, M. (2006). Disaster Mitigation of Debris Flows, Slope Failures and Landslides, Universal Academy Press.

5. Berger, F., Martin, R., Auber, B., and Mathy, A. (2011). Etude Comparative, En Utilisant l’événement Du 28 Décembre 2008 à Saint Paul de Varces, Du Zonage de l’aléa Chute de Pierre Avec Différents Outils de Simulation Trajectographique et Différentes Matrices d’Aléa, Cemagref UREMGR.

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