Shape still matters – rockfall experiments with deadwood reveal a new facet of rock shape relevance
Abstract. Mountain forests have a substantial protective function in preventing natural hazards. Rates of deadwood production have already increased and are predicted to rise further, due to natural disturbances. In particular, higher windthrow event frequencies are expected, primarily due to the emerging even-aged forest stands in alpine regions combined with climate change. Here, we quantified the rockfall protection effect of mountain forests with and without deadwood in unprecedented detail. Repetitive experiments were conducted in which the two most important rock shapes from a hazard potential point of view and masses of 200 kg up to 3200 kg were considered. Based on a multi-camera setup, pre-and post-experimentally retrieved high- resolution lidar data, and rock data measured in situ, we completely reconstructed 63 trajectories. Every parameter of interest describing the rockfall kinematics was retrieved for each trajectory. A total of 164 tree impacts and 55 deadwood impacts were observed, and the currently applied energy absorption curves – partially only derived theoretically – could consequently be corroborated or even expanded to a greater absorption performance of certain species than hitherto assumed. Standing trees in general and deadwood, in particular, were found to strongly impede the notorious lateral spreading of platy rocks. Platy rocks featured a shorter mean run-out distance than their compact counterparts of similar weight, even in the absence of deadwood. These results indicate that the higher hazard potential of platy rocks compared with more compact rocks, previously postulated for open field terrain, applies less to forested areas. Lastly, reproducing the experimental setting showcases how complex forest states can be treated within rockfall simulations. Overall, the results of this study highlight the importance of incorporating horizontal forest structures that are as accurate as possible into simulations in order to obtain realistic deposition patterns.
Adrian Ringenbach et al.
Status: final response (author comments only)
RC1: 'Comment on esurf-2022-70', Louise M. Vick, 13 Jan 2023
- AC1: 'Reply on RC1', Adrian Ringenbach, 19 Feb 2023
RC2: 'Comment on esurf-2022-70', Christine Moos, 18 Jan 2023
- AC2: 'Reply on RC2', Adrian Ringenbach, 19 Feb 2023
Adrian Ringenbach et al.
Adrian Ringenbach et al.
Viewed (geographical distribution)
This paper represents an important dataset which expands the existing data on the performance of rock shape and size in differing forest conditions. The presentation of this paper will greatly further rockfall understanding and simulation accuracy, a vital step in the development of natural hazards science.
The data itself is well presented and straightforward, and the discussion summarises the work nicely. However the early stages of the paper create some confusion in terms of focus and methodology.
While the title leads readers to believe the paper focuses predominantly on rock shape, this is quite a small part of the experiment and results. Rock size/mass is the more varied input, and the text itself focuses mostly on forest. Additionally, in the introduction, rock shape is only mentioned in the last few lines with only one reference providing the necessary background for shape understanding. I would suggest revising the title slightly in order to not mislead the reader.
There was no introduction to some other key components. For example, soil moisture and its effect on rockfall runout is not mentioned, despite being part of the data collection. RAMMS and the way it simulates rockfall (this seems to have guided the data collection methodology, so it is important) is also not mentioned.
The text confused me most in the experiment design section. Having published rockfall experiment design myself I can appreciate the difficulty of communicating all the variables clearly. Can the authors clarify this section? In particular what the exact two different shapes are, and what they mean by ‘tree mass classes’. The total of 106 rocks is the total events, or total number of individual rock samples used? How many rock samples did they use, and how many repetitions of each were performed? Later in the text (L190) there is a mention of 13 trajectories. Where does this number come from?
Can the authors define early on what is meant by deadwood in this particular case- trees which have died but remain fully standing, or trees which are broken?
Figure 1a. Why are the green points not displayed according to size like the blue?
L182: How is this consideration threshold derived?
L183-4: What is a root plate and what is the purpose of this step?
L191: How were these parameters calibrated? What field data went into this?
L201: Does MDH mean resting elevation of the block? Unclear
L311: How can it be a pattern and also not statistically significant?
F9: What are the white lines crossing the slope?
L482: This is untrue. See for example https://doi.org/10.5194/nhess-19-1105-2019