EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Toward national-covering dynamic rockfall simulations: adapting stnParabel with efficiency in mind

François Noël1,2, Thierry Oppikofer2,3, Michel Jaboyedoff1, Reginald Hermanns2,4, Martina Böhme2, and Synnøve Flugekvam Nordang5
François Noël et al.
  • 1Risk Analysis Group, Institute of Earth Sciences, University of Lausanne, Lausanne, Switzerland
  • 2Geohazard and Earth Observation, Geological Survey of Norway, Trondheim (
  • 3Terranum, Bussigny, Switzerland
  • 4Department of Geoscience and Petroleum, Norwegian University of Science and Technology, Trondheim, Norway
  • 5Engineering geology and slides, Rambøll, Trondheim, Norway

Working with 3D point clouds offers many benefits for reducing the subjectivity of rockfall simulations at a local scale. Indeed, many “dynamic” rockfall rebound models are strongly affected by the topography and the perceived surface roughness, which can be objectively represented with detailed terrain models. This reduces the need for complex time intensive back analyses and associated sensitive adjustments of parameters used for subjectively adjusting the simulations to the desired runout distances.

Predictable and reproductible simulations from a constrained set of parameters while still managing to reproduce observed runouts on a wide range of sites could be time saving for practitioners and their clients, ultimately improving quality at lower costs to the society. This could speed up the process for practitioners to deliver concise reports easier to interpret and quality-check by a wider range of employees on the client side.

However, working with 3D point clouds can have a steep learning curve and quickly becomes impractical at a larger scale for regional analysis, partially obscuring some of the previously mention advantages. To explore potential ways to circumvent these issues, a prototype of an algorithm that runs the stnParabel rockfall simulation freeware in batch was quickly implemented in 2020. It was developed to expand such dynamic simulation capabilities to larger regions and up to potentially national-covering capabilities.

Slight modifications were done on the impact detection algorithm to also work with high resolution gridded terrain models (DTMs) with a focus at not sacrificing the benefits of working on 3D point clouds. The sources biases due to the stretched grided cells underrepresenting the steep cliffs are worked around by randomly distributing the sources based on the 3D stretched surface occupied by the cells.

Preliminary results were produced regionally over 6000 km2, involving 115 000 000 simulated rockfalls with 10 m3 blocks of dimensions 3.8x3.2x1.8 m. The simulations were performed on the Norwegian national 1 m DTM from airborne LiDAR, up sampled to 50 cm cells for future proofing the approach. They were produced at a rate of about 15 000 000 simulated 3D trajectories per hour when ran on a small Ultrabook laptop with fast SSD.

The preliminary results from the dynamic rockfall model were then combined with databases of observed deposited blocks from previous rockfall events to act as a calibration guide for FlowR model. This simpler model based on gridded topographic-hydrologic spreading and sliding block approaches can be adjusted to produce a wide range of desired runouts envelopes from numerous processes, like rockfalls. The simpler simulations on 10 m DTM were used as a candidate for the revision of the national rockfall susceptibility mapping methodology.

The prototype approach to run detailed dynamic rockfall simulations regionally would require validations. Such potentially useful approach with objective dynamic simulations for hazard mapping as well as for the design of mitigation measures could then be shared through publications and be implemented in the distributed rockfall simulation freeware stnParabel. 

How to cite: Noël, F., Oppikofer, T., Jaboyedoff, M., Hermanns, R., Böhme, M., and Flugekvam Nordang, S.: Toward national-covering dynamic rockfall simulations: adapting stnParabel with efficiency in mind, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12230,, 2022.


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