| 27 Oct 2025
Assessing the predictability of rockfall simulations constrained to simple objective input parameters
Abstract. Rockfall simulations are used to predict runout distances in case potentially unstable rock compartments would eventually fail. Transit simulated values such as the bounce heights and involved energies are also useful for hazard and risk assessments and for mitigation design tasks. However, it has been shown that the predictions from simulation results can vary significantly from user to user and from site to site. This highlights the need for simulation models with quantified accuracy and precision, low parametric subjectivity, and with good performance at predicting the transit values. The objective of this work is to present a validation methodology for rockfall simulation models and to objectively evaluate the predictive performance of stnParabel freeware simulation model when used with the Rolling friction rebound model. For this purpose, numerous mapped observations from a combination of back analyses of rockfall experiments and real events involving different remote sensing techniques were gathered. They cover twelve sites of various characteristics and geometries. The extensive collected observations include several hundred mapped deposited rock fragments of known dimensions and respective source locations. Each individual rock’s dimensions and masses were repetitively simulated without any other parameter adjustments in order to minimize the subjectivity of the simulation approach. In complement to the systematic objective process-based simulations, the runouts were also predicted for all sites with simulated trajectories from two additional process-based models for comparisons. Moreover, runout extents were also obtained geometrically with a commercial software and with a common geometrical approach for comparison. The results showed that the runout prediction accuracy from our process-based simulated trajectories is generally stable from site to site. Moreover, the runout precision of the simulations with stnParabel is improved by 2× to 3× compared to those of all other methods tested. And this is achieved with limited errors on the predicted transit values such as the bounce heights and translational velocities.
General
The manuscript presents a well-conceptualized and thoroughly executed study evaluating the predictive performance of rockfall simulations. The approach integrates the Rolling Friction Rebound model within the stnParabel framework and contrasts its outcomes with process-based and geometric methods, offering a methodological comparison. Validation is carried out across twelve sites.
Although rockfall modelling is a widely investigated topic, this work provides a valuable contribution by demonstrating that reliable predictions of runout distances, lateral dispersion, and kinematic metrics can be achieved without extensive site-specific calibration. However, the Methods section would need more concise explanations and a clearer distinction between novel contributions and previous work. Additionally, limitations related to inventory collection, vegetation filtering, and boulder fragmentation effects should be discussed in depth to contextualize the results.
Overall, the study is scientifically relevant and of clear practical value for rockfall hazard management, and it has strong potential for publication once the suggested clarifications and improvements are incorporated.
Specific Comments
Introduction
Line 115 – In this line, the authors already indicate that validation for the Mel de la Niva case was extended to 11 additional sites in their previous work (Noël & Nordang, 2025), among other objectives, to compare runout distances and assess the predictive performance of stnParabel under varying geometries and conditions. It would be recommendable to include a clarification that clearly differentiates what was achieved in the previous study and what constitutes the novelty of the present work.
Approach
Line 183 – In this line, it is mentioned that no artificial roughness or subjective adjustments to terrain material properties were applied, and the conclusions indicate that this was done to facilitate comparability. However, if this is the case, it remains unclear how the effect of vegetation was considered, particularly if any of the selected sites included areas with dense vegetation (no information is provided on this). If high or dense vegetation was present in any case, it is necessary to explain how this was considered, given its influence on perceived surface roughness and, consequently, on the model’s predictability, including runout distances and lateral spreading.
Line 208, 455 and others – Please clarify in the text how boulder fragmentation was considered in the trajectory comparisons. This clarification should also be applied to other sections of the manuscript, for example, explaining how this was addressed in the inventory and in the simulation.
Line 243 – The validation of velocities and bounce heights was performed at only two sites, as these are the only locations where such data are available. It is therefore important to discuss whether this limited sample is sufficient to support general conclusions, particularly when contrasted with the validation of runout distances, which considers a broader range of sites and geomorphological contexts.
Line 245 and 383 – For validation, the results are compared against Berger and Dorren (2006). However, given the strong influence of terrain model resolution on the analysis of velocities and bounce heights, it is essential to discuss the limitations and challenges of such a comparison. Berger and Dorren (2006) relied on a contour line–based model with a 2.5 m resolution, whereas the present study uses high-resolution DTMs with a 0.2 m resolution.
Simulation results and analyses
Lines 444, 610 and Appendix – The article should address the limitations associated with the inventory, as these may have contributed to deviations in some results. Furthermore, the Appendix reveals a wide range of approaches used to compile the inventory, from exhaustive field campaigns to image-based reconnaissance. The inventory was assembled by different institutions, which may have applied varying criteria during data collection, such as the minimum block size included or the spatial extent considered part of the studied rockfall event. All these aspects should be clearly discussed in the manuscript, explaining how these points were managed.
Appendix
As previously recommended, Tables A1 and A2 could also include brief information on the existing vegetation within the transit zone.