the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 04 Feb 2022
Delimiting rockfall runout zones using reach probability values simulated with a Monte-Carlo based 3D trajectory model
Abstract. At present, a quantitative basis for delimiting realistic rockfall runout zones on the basis of trajectory simulation data is generally missing. The objective of this study is to come up with standardized reach probability threshold values (RPTV) to separate "realistic" from "unrealistic" simulated rockfall runouts. We therefore compared reach probability values (Preach) simulated with Rockyfor3D for 458 mapped, fresh rockfall blocks (silent witnesses SW) on 18 different sites with a volume >= 0.05 m3 and estimated occurrence frequencies up to 300 years. We analysed which block, slope and forest characteristics influenced Preach of the SW based on a linear mixed effects model. The results indicate that the limit of a realistic runout zone lies in the range where simulated Preach values are between > 1 % and approximately 3 %. We conclude that RPTV can be defined to values lying in the range from 1.2 % to 2.5 % depending on the defined block volume and the encountered cumulative basal area in a forested transit zone. Where possible, the defined RPTV should be compared and validated by field recordings of SW.
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RC1: 'Comment on nhess-2022-32', Anonymous Referee #1, 15 Feb 2022
The manuscript presents relevant work that will contribute standardization of rockfall hazard analyses. The work provides insight into the runout distances that can be considered plausible for delineation of hazard zones on the basis of field investigation and Monte Carlo simulations of rock fall trajectories. The work is well constructed from problem statement, to hypothesis to methods, results and discussion.
It would be beneficial for the readers to include a discussion on the influence of having different approaches for mapping SW in utilizing the aggregated results for general recommendations. Particularly, those rockfall deposits mapped whcih originated from muliple rockfall sources.
The values for damping (Rn) are referenced for different soild types. It is not clear if those correspond to one of the references cited earlier in the paper. Please clarify the choice of these ranges in light of the multiple calibrations for energy restitution for rockfall trajectories in the literature.
You excluded SW that did not fir the modelled results, under the assumtion that those belonged to larger blocks. Although plausible and a very small number, was there any real evidence of these blocks belonging to larger ones? This point is critical for the validity of interpreted.
The work aims at developing a standad aproach for delimiting rockfall hazards zones, and a probabilistic approach is presented. It is recommended in the discussion and conclusion sections that field vlidation and expert judgement needs to complement the models. I fully agree and I suggest his should be expanded to include what aspects of the results, input parameters or field validation should be evaluated through experience and what can be a process that becomes part of a standard.
Citation: https://doi.org/10.5194/nhess-2022-32-RC1 -
AC1: 'Reply on RC1', Luuk Dorren, 08 Mar 2022
Thank you for your comments.
Our analysis suggests that the influence of mapping all SW in comparison to only the SW with longer runouts does not have a significant impact on the results. For sites where all SW were mapped, one would expect that the median PreachSW value, as well as the total variation of the values below our 5% threshold would be larger than is we only would have mapped the long runout SW. The statistical analysis did not confirm this since it only revealed a significant difference for the sites Claro and Taesch. Here only Claro is in accordance to the above expectation, whereas Taesch evinces the opposite characteristics. There is no significant difference between all other sites where the four different mapping strategies were used, indicating that the fact that SW resulted from one or multiple rockfall events do not have a significant effect on the results. We will add this explanation to the discussion in the revised version of the paper.
The values for damping (Rn) used in the Rockyfor3D model have been defined since 2004 and originate from the following references: Dorren and Heuvelink, Int. J. G.I.S. Vol. 18(6) 2004, 595–609; Dorren et al., Natural Hazards and Earth System Sciences, 6, 145–153, 2006; and Dorren, L.: Rockyfor3D (v5.2) revealed – Transparent description of the complete 3D rockfall model, ecorisQ paper, p. 33, 2016. We will add these references to the corresponding section in the revised version of the paper.
Hard evidence of smaller blocks deposited on the lower slope sections being fragments of larger blocks is only available at the site of Evolène, where the rockfall event was filmed (see https://youtu.be/SxdaXGgoQW8?t=56) and at Vaujany where we did rockfall experiments. However, at Vaujany, during those experiments we only mapped the remaining large block volumes and not the released fragments. Another nice movie showing this effect, which was unfortunately not one of our study sites, can be seen here: but was https://youtu.be/fi2dMUT8WAo. However, the fact that all deposited blocks categorized as fragments had a significant lower volume compared to the neighbouring SW affirms our assumption. While mapping the SW at certain sites (e.g., Flaesch and Taesch), our impressions in the field strongly oriented us in the direction of that hypothesis.
Your last remark considers which aspects of the results, input parameters or field validation should be evaluated through experience and what can be a process that becomes part of a standard. We would strongly support that rockfall trajectory modelling, including a probabilistic component with a sufficiently large number of repeated simulations, to ensure a stable "converged" statistical distribution of the reach probabilities, should be a basis of a standard for rockfall hazard assessment. In addition, we would recommend the comparison of the outcomes of different modelling approaches. The collection of the field input data, as well as the delineation of the rockfall hazard zone based on modelling results and field mapped silent witnesses remains an expert task. This study provides a support for the latter process. We will add this precision to the revised version of the paper.
Citation: https://doi.org/10.5194/nhess-2022-32-AC1
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AC1: 'Reply on RC1', Luuk Dorren, 08 Mar 2022
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RC2: 'Comment on nhess-2022-32', Anonymous Referee #2, 09 Mar 2022
This study provides a reach probability threshold value for delimiting rockfall runout zones based on trajectory simulations and recording of rockfall events at 18 sites in Europe. The objective was to generate standardized reach probability threshold values that help with separating realistic from unrealistic simulated rockfall runouts. The findings can potentially contribute to quantitative assessment of rockfall hazards. I recommend publication provided that the following comments are addressed.
Fig 2 – Consider adding field photos for each topography type above or below the panel. Add image resolution/source.
Fig 3 – delete the word “ancient” or define it.
I suggest somewhere in section 2.2 include some references to previous work using Rockyfor3D model to assess rockfall hazards. How does this study build on previous efforts using this model?
Line 104 – The model requires the number of trees – Does this include tree density/spacing? If no, how does this may impact your model?
Line 121 – Explain why micro topography should not be taken into account when assigning surface roughness values. Small topographic or morphological irregularities may influence rockfall trajectory. How is this considered in this study?
Line 149 – Include a few references here.
Line 158 – Assuming that these SW are fragments of larger blocks might work for some slopes, but it may not be entirely correct for vertical/steep cliffs where detached rockfalls may not interact with the slope (wall) before deposition. Did your study sites include such vertical or almost vertical cliffs?
Fig 4 – Please add units for volume on the y-axis. What are the black dots, individual rockfall events? Can you add the number of rockfalls above each yes/no box? Overall, this figure is hard to understand and needs to be properly labeled and explained.
Line 183 – Insert confidence interval for the difference so readers know what significant difference refers to.
Fig 6 – Not everyone is familiar with reading box plots. Can you label or include in caption the following: show the median value for reach probabilities of all events at all sites (1.41%, e.g., drawing this as a horizontal red line on the plot), what are the gray dots (individual SW?), highlight the boxes for Claro and Taesch (the 2 sites that significantly differ from the rest – maybe coloring them in gray). Consider adding the same labels as Fig 1 (e.g., CH1) under each site name along the x-axis. Y-axis should be labeled the same way in both Fig 6 and 7.
Fig 7 – Draw the medium line for P(reach) across the plot.
Line 192 – What do you mean by “relatively high correspondence” here? Insert values here and in fig 9.
Line 197 – Block volume?
Line 223 – Explain what you mean by “long term practical experience” or delete.
Line 224 – define what you mean by abundant data (no. of SW?)
I encourage the authors to make the rockfall data and codes used in this study available upon request or provide a link to an open-access repository where the data are stored.
Citation: https://doi.org/10.5194/nhess-2022-32-RC2 -
AC2: 'Reply on RC2', Luuk Dorren, 05 Apr 2022
Dear referee,
First of all, we would like to thank you for the valuable comments and suggestions for improvement. Below, you'll find our answers listed point-by-point:
Fig2 – Consider adding field photos for each topography type above or below the panel. Add image resolution/source.
>> We considered adding photos, but since the three example sites in the Fig. 2, but also most of the other study sites, are covered by forests below the rock cliffs, one cannot see the details of the topography which are clearly visible in the hillshades. It would result in three photos showing just a cliff and forest below. Therefore, we decided to leave the photos out. We will of course add the image resolution and source in the revised version.Fig 3 – delete the word “ancient” or define it.
>> we'll delete it in the revised versionI suggest somewhere in section 2.2 include some references to previous work using Rockyfor3D model to assess rockfall hazards. How does this study build on previous efforts using this model?
>> we added additional references and explained better the history of Rockyfor3D and its use for this studyLine 104 – The model requires the number of trees – Does this include tree density/spacing? If no, how does this may impact your model?
>> The model does include tree density and spacing using positions and diameters of individual trees. Theses are derived from tree detection based on LiDAR Canopy Models or detailed forest and forest gap polygon maps. As such, we reproduced the existing forest structure at each site as realistically as possible. We will explain this point better in the revised version.Line 121 – Explain why micro topography should not be taken into account when assigning surface roughness values. Small topographic or morphological irregularities may influence rockfall trajectory. How is this considered in this study?
>> Since we use digital terrain models (elevation models) with a resolution of 2m, many topographic irregularities that influence trajectories are taken into account. What we meant with micro topography are landscape features such a cattle trails, which are often included in the roughness parameters by users of the Rockyfor3D model. To some extent, these are already included in the 2m terrain model and rather result in additional rebounds than in energy loss during an impact. The reason for feeding roughness parameter maps to the model, is to take into account energy loss during impacts on rock material that has previously been deposited and which are not represented in the digital terrain model. We will revise the paper accordingly.Line 149 – Include a few references here.
>> we will revise our statement slightly and improve its precision and we will include relevant references.Line 158 – Assuming that these SW are fragments of larger blocks might work for some slopes, but it may not be entirely correct for vertical/steep cliffs where detached rockfalls may not interact with the slope (wall) before deposition. Did your study sites include such vertical or almost vertical cliffs?
>> The study sites include almost vertical cliffs, but none with an almost horizontal deposition area below leading to short propagation distances. All sites had a relatively steep (in general 30° - 40°) transit zone below, leading to trajectories with intermitting flight and rebound phases causing fragmentation.Fig 4 – Please add units for volume on the y-axis. What are the black dots, individual rockfall events? Can you add the number of rockfalls above each yes/no box? Overall, this figure is hard to understand and needs to be properly labeled and explained.
>> We will revise the labelling and the explanation of the figure following these suggestionsLine 183 – Insert confidence interval for the difference so readers know what significant difference refers to.
>> We will add the significance levelFig 6 – Not everyone is familiar with reading box plots. Can you label or include in caption the following: show the median value for reach probabilities of all events at all sites (1.41%, e.g., drawing this as a horizontal red line on the plot), what are the gray dots (individual SW?), highlight the boxes for Claro and Taesch (the 2 sites that significantly differ from the rest – maybe coloring them in gray). Consider adding the same labels as Fig 1 (e.g., CH1) under each site name along the x-axis. Y-axis should be labeled the same way in both Fig 6 and 7.
>> We will revise the labelling / explanation of both figures following these suggestionsFig 7 – Draw the medium line for P(reach) across the plot.
>> We will add the line representing the median value and make the Y-axis label consistent with Fig. 6.Line 192 – What do you mean by “relatively high correspondence” here? Insert values here and in fig 9.
>> We will revise this paragraph and improve the explanationLine 197 – Block volume?
>> we'll correct it in the revised versionLine 223 – Explain what you mean by “long term practical experience” or delete.
>> we'll delete it in the revised versionLine 224 – define what you mean by abundant data (no. of SW?)
>> We will revise this paragraph and improve the explanationI encourage the authors to make the rockfall data and codes used in this study available upon request or provide a link to an open-access repository where the data are stored.
>> we will make the data and the analysis code available via Github. The used rockfall trajectory model Rockyfor3D is available via https://www.ecorisq.org/ecorisq-toolsCitation: https://doi.org/10.5194/nhess-2022-32-AC2
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AC2: 'Reply on RC2', Luuk Dorren, 05 Apr 2022
Interactive discussion
Status: closed
-
RC1: 'Comment on nhess-2022-32', Anonymous Referee #1, 15 Feb 2022
The manuscript presents relevant work that will contribute standardization of rockfall hazard analyses. The work provides insight into the runout distances that can be considered plausible for delineation of hazard zones on the basis of field investigation and Monte Carlo simulations of rock fall trajectories. The work is well constructed from problem statement, to hypothesis to methods, results and discussion.
It would be beneficial for the readers to include a discussion on the influence of having different approaches for mapping SW in utilizing the aggregated results for general recommendations. Particularly, those rockfall deposits mapped whcih originated from muliple rockfall sources.
The values for damping (Rn) are referenced for different soild types. It is not clear if those correspond to one of the references cited earlier in the paper. Please clarify the choice of these ranges in light of the multiple calibrations for energy restitution for rockfall trajectories in the literature.
You excluded SW that did not fir the modelled results, under the assumtion that those belonged to larger blocks. Although plausible and a very small number, was there any real evidence of these blocks belonging to larger ones? This point is critical for the validity of interpreted.
The work aims at developing a standad aproach for delimiting rockfall hazards zones, and a probabilistic approach is presented. It is recommended in the discussion and conclusion sections that field vlidation and expert judgement needs to complement the models. I fully agree and I suggest his should be expanded to include what aspects of the results, input parameters or field validation should be evaluated through experience and what can be a process that becomes part of a standard.
Citation: https://doi.org/10.5194/nhess-2022-32-RC1 -
AC1: 'Reply on RC1', Luuk Dorren, 08 Mar 2022
Thank you for your comments.
Our analysis suggests that the influence of mapping all SW in comparison to only the SW with longer runouts does not have a significant impact on the results. For sites where all SW were mapped, one would expect that the median PreachSW value, as well as the total variation of the values below our 5% threshold would be larger than is we only would have mapped the long runout SW. The statistical analysis did not confirm this since it only revealed a significant difference for the sites Claro and Taesch. Here only Claro is in accordance to the above expectation, whereas Taesch evinces the opposite characteristics. There is no significant difference between all other sites where the four different mapping strategies were used, indicating that the fact that SW resulted from one or multiple rockfall events do not have a significant effect on the results. We will add this explanation to the discussion in the revised version of the paper.
The values for damping (Rn) used in the Rockyfor3D model have been defined since 2004 and originate from the following references: Dorren and Heuvelink, Int. J. G.I.S. Vol. 18(6) 2004, 595–609; Dorren et al., Natural Hazards and Earth System Sciences, 6, 145–153, 2006; and Dorren, L.: Rockyfor3D (v5.2) revealed – Transparent description of the complete 3D rockfall model, ecorisQ paper, p. 33, 2016. We will add these references to the corresponding section in the revised version of the paper.
Hard evidence of smaller blocks deposited on the lower slope sections being fragments of larger blocks is only available at the site of Evolène, where the rockfall event was filmed (see https://youtu.be/SxdaXGgoQW8?t=56) and at Vaujany where we did rockfall experiments. However, at Vaujany, during those experiments we only mapped the remaining large block volumes and not the released fragments. Another nice movie showing this effect, which was unfortunately not one of our study sites, can be seen here: but was https://youtu.be/fi2dMUT8WAo. However, the fact that all deposited blocks categorized as fragments had a significant lower volume compared to the neighbouring SW affirms our assumption. While mapping the SW at certain sites (e.g., Flaesch and Taesch), our impressions in the field strongly oriented us in the direction of that hypothesis.
Your last remark considers which aspects of the results, input parameters or field validation should be evaluated through experience and what can be a process that becomes part of a standard. We would strongly support that rockfall trajectory modelling, including a probabilistic component with a sufficiently large number of repeated simulations, to ensure a stable "converged" statistical distribution of the reach probabilities, should be a basis of a standard for rockfall hazard assessment. In addition, we would recommend the comparison of the outcomes of different modelling approaches. The collection of the field input data, as well as the delineation of the rockfall hazard zone based on modelling results and field mapped silent witnesses remains an expert task. This study provides a support for the latter process. We will add this precision to the revised version of the paper.
Citation: https://doi.org/10.5194/nhess-2022-32-AC1
-
AC1: 'Reply on RC1', Luuk Dorren, 08 Mar 2022
-
RC2: 'Comment on nhess-2022-32', Anonymous Referee #2, 09 Mar 2022
This study provides a reach probability threshold value for delimiting rockfall runout zones based on trajectory simulations and recording of rockfall events at 18 sites in Europe. The objective was to generate standardized reach probability threshold values that help with separating realistic from unrealistic simulated rockfall runouts. The findings can potentially contribute to quantitative assessment of rockfall hazards. I recommend publication provided that the following comments are addressed.
Fig 2 – Consider adding field photos for each topography type above or below the panel. Add image resolution/source.
Fig 3 – delete the word “ancient” or define it.
I suggest somewhere in section 2.2 include some references to previous work using Rockyfor3D model to assess rockfall hazards. How does this study build on previous efforts using this model?
Line 104 – The model requires the number of trees – Does this include tree density/spacing? If no, how does this may impact your model?
Line 121 – Explain why micro topography should not be taken into account when assigning surface roughness values. Small topographic or morphological irregularities may influence rockfall trajectory. How is this considered in this study?
Line 149 – Include a few references here.
Line 158 – Assuming that these SW are fragments of larger blocks might work for some slopes, but it may not be entirely correct for vertical/steep cliffs where detached rockfalls may not interact with the slope (wall) before deposition. Did your study sites include such vertical or almost vertical cliffs?
Fig 4 – Please add units for volume on the y-axis. What are the black dots, individual rockfall events? Can you add the number of rockfalls above each yes/no box? Overall, this figure is hard to understand and needs to be properly labeled and explained.
Line 183 – Insert confidence interval for the difference so readers know what significant difference refers to.
Fig 6 – Not everyone is familiar with reading box plots. Can you label or include in caption the following: show the median value for reach probabilities of all events at all sites (1.41%, e.g., drawing this as a horizontal red line on the plot), what are the gray dots (individual SW?), highlight the boxes for Claro and Taesch (the 2 sites that significantly differ from the rest – maybe coloring them in gray). Consider adding the same labels as Fig 1 (e.g., CH1) under each site name along the x-axis. Y-axis should be labeled the same way in both Fig 6 and 7.
Fig 7 – Draw the medium line for P(reach) across the plot.
Line 192 – What do you mean by “relatively high correspondence” here? Insert values here and in fig 9.
Line 197 – Block volume?
Line 223 – Explain what you mean by “long term practical experience” or delete.
Line 224 – define what you mean by abundant data (no. of SW?)
I encourage the authors to make the rockfall data and codes used in this study available upon request or provide a link to an open-access repository where the data are stored.
Citation: https://doi.org/10.5194/nhess-2022-32-RC2 -
AC2: 'Reply on RC2', Luuk Dorren, 05 Apr 2022
Dear referee,
First of all, we would like to thank you for the valuable comments and suggestions for improvement. Below, you'll find our answers listed point-by-point:
Fig2 – Consider adding field photos for each topography type above or below the panel. Add image resolution/source.
>> We considered adding photos, but since the three example sites in the Fig. 2, but also most of the other study sites, are covered by forests below the rock cliffs, one cannot see the details of the topography which are clearly visible in the hillshades. It would result in three photos showing just a cliff and forest below. Therefore, we decided to leave the photos out. We will of course add the image resolution and source in the revised version.Fig 3 – delete the word “ancient” or define it.
>> we'll delete it in the revised versionI suggest somewhere in section 2.2 include some references to previous work using Rockyfor3D model to assess rockfall hazards. How does this study build on previous efforts using this model?
>> we added additional references and explained better the history of Rockyfor3D and its use for this studyLine 104 – The model requires the number of trees – Does this include tree density/spacing? If no, how does this may impact your model?
>> The model does include tree density and spacing using positions and diameters of individual trees. Theses are derived from tree detection based on LiDAR Canopy Models or detailed forest and forest gap polygon maps. As such, we reproduced the existing forest structure at each site as realistically as possible. We will explain this point better in the revised version.Line 121 – Explain why micro topography should not be taken into account when assigning surface roughness values. Small topographic or morphological irregularities may influence rockfall trajectory. How is this considered in this study?
>> Since we use digital terrain models (elevation models) with a resolution of 2m, many topographic irregularities that influence trajectories are taken into account. What we meant with micro topography are landscape features such a cattle trails, which are often included in the roughness parameters by users of the Rockyfor3D model. To some extent, these are already included in the 2m terrain model and rather result in additional rebounds than in energy loss during an impact. The reason for feeding roughness parameter maps to the model, is to take into account energy loss during impacts on rock material that has previously been deposited and which are not represented in the digital terrain model. We will revise the paper accordingly.Line 149 – Include a few references here.
>> we will revise our statement slightly and improve its precision and we will include relevant references.Line 158 – Assuming that these SW are fragments of larger blocks might work for some slopes, but it may not be entirely correct for vertical/steep cliffs where detached rockfalls may not interact with the slope (wall) before deposition. Did your study sites include such vertical or almost vertical cliffs?
>> The study sites include almost vertical cliffs, but none with an almost horizontal deposition area below leading to short propagation distances. All sites had a relatively steep (in general 30° - 40°) transit zone below, leading to trajectories with intermitting flight and rebound phases causing fragmentation.Fig 4 – Please add units for volume on the y-axis. What are the black dots, individual rockfall events? Can you add the number of rockfalls above each yes/no box? Overall, this figure is hard to understand and needs to be properly labeled and explained.
>> We will revise the labelling and the explanation of the figure following these suggestionsLine 183 – Insert confidence interval for the difference so readers know what significant difference refers to.
>> We will add the significance levelFig 6 – Not everyone is familiar with reading box plots. Can you label or include in caption the following: show the median value for reach probabilities of all events at all sites (1.41%, e.g., drawing this as a horizontal red line on the plot), what are the gray dots (individual SW?), highlight the boxes for Claro and Taesch (the 2 sites that significantly differ from the rest – maybe coloring them in gray). Consider adding the same labels as Fig 1 (e.g., CH1) under each site name along the x-axis. Y-axis should be labeled the same way in both Fig 6 and 7.
>> We will revise the labelling / explanation of both figures following these suggestionsFig 7 – Draw the medium line for P(reach) across the plot.
>> We will add the line representing the median value and make the Y-axis label consistent with Fig. 6.Line 192 – What do you mean by “relatively high correspondence” here? Insert values here and in fig 9.
>> We will revise this paragraph and improve the explanationLine 197 – Block volume?
>> we'll correct it in the revised versionLine 223 – Explain what you mean by “long term practical experience” or delete.
>> we'll delete it in the revised versionLine 224 – define what you mean by abundant data (no. of SW?)
>> We will revise this paragraph and improve the explanationI encourage the authors to make the rockfall data and codes used in this study available upon request or provide a link to an open-access repository where the data are stored.
>> we will make the data and the analysis code available via Github. The used rockfall trajectory model Rockyfor3D is available via https://www.ecorisq.org/ecorisq-toolsCitation: https://doi.org/10.5194/nhess-2022-32-AC2
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AC2: 'Reply on RC2', Luuk Dorren, 05 Apr 2022
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Cited
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- The Potential of UAV-Acquired Photogrammetric and LiDAR-Point Clouds for Obtaining Rock Dimensions as Input Parameters for Modeling Rockfall Runout Zones B. Žabota et al. 10.3390/drones7020104
- A scenario-based approach for immediate post-earthquake rockfall impact assessment M. Alvioli et al. 10.1007/s10346-023-02127-2
- Vers une nouvelle approche quantitative pour l’évaluation de l’aléa de chute de blocs A. Rossignol et al. 10.1051/geotech/2024016