the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Feb 2022
Multi-method monitoring of rockfall activity along the classic route up Mont Blanc (4809 m a.s.l.) to encourage adaptation by mountaineers
Jacques Mourey
Pascal Lacroix
Pierre-Allain Duvillard
Guilhem Marsy
Marco Marcer
Emmanuel Malet
Ludovic Ravanel
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- Final revised paper (published on 16 Feb 2022)
- Preprint (discussion started on 27 Apr 2021)
Interactive discussion
Status: closed
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RC1: 'Comment on nhess-2021-128', Anonymous Referee #1, 12 May 2021
The manuscript by Mourey et al. “Rockfall and vulnerability of mountaineers on the west face of the Aiguille du Goûter (classic route up Mont Blanc, France), an interdisciplinary study” investigates the rockfall occurrence at the west face of the Aiguille du Goûter, discusses potential triggers of rockfall and analyses hazard potential for mountain climbers. The study addresses an interesting topic, the use of mountains for recreation, the economic importance of this use and geomorphic hazards threatening the participants that potentially increase due to climate change and due to an increase of climbing. Therefore, the manuscript could be suited for Natural Hazard and Earth System Sciences. However, the study is a case study and it remains unclear how representative the study results are for other mountain regions, which should be more clearly discussed. The study quantifies mountaineering activity, thermal processes able to trigger rockfalls, rockfall occurrence and links triggers to rockfall and hazard potential. Unfortunately, (1) the basic definitions are unclear, (2) the manuscript is poorly written and structured, (3) the role of preconditioning and preparing factors are not addressed and (4) important rockfall triggers are not investigated at all or not sufficiently. However, the presented data set is impressive and the manuscript could be an important contribution to a little investigated topic. Therefore, I recommend major revision.
(1) The authors use the terms vulnerability, danger and hazards without defining them. Vulnerability includes the mountaineers and their potential to mitigate the hazard. Mountaineers could develop strategies to reduce risk. However, this is not investigated in this manuscript. The authors focus to quantify the number of mountaineers and, therefore, they investigate the hazard potential of rockfall and not the vulnerability of climbers. They have no data to analyse vulnerability. In addition, they should be careful to link accidents with rockfall. Accidents or rescue of mountaineers can have numerous reasons and there is no a priori link to rockfall.
(2) The manuscript is poorly written. The introduction pretty vague and geomorphic knowledge necessary to understand the objectives are presented in Chapter 2 after the outline of this study. In addition, the outline of the objectives remain pretty vague or unclear. The study area is insufficiently introduced. The climbing route is important to understand the hazard potential, however, not every reader is a specialist to mountain climbing in the Mont Blanc area and familiar with the route. The methods are not sufficiently described. The authors record 68 days of seismic data in 2019 and classify this data but it remains unclear what the basis of the classification is. They “keep” data when the rockfall origin was sure but they present no information on which basis they decide if a rockfall is “sure” or not. They present a Figure 3 with seismic data without explaining it and it is completely unclear how they process the data to get the energy or number of rockfall they analyse in the manuscript. The authors use automatic photogrammetry to monitor snow cover, however, it is unclear what kind of equipment they use (camera type), how they process the data (software, filters…), how they calculate the snow covered area and how representative this area is. Does the photograph covers the entire route? Furthermore, the authors use three temperature loggers for three years without presenting any data. They correlate one logger to air temperature and use a 16-17 year data set to drive the thermal model CRYOGRID2. It remains unclear what parameters CRYOGRID2 uses and what values are used as input data. Why a 17-year data set is necessary to analyse 68 days of rockfall in 2019 remains unclear. In summary, the author uses four different time periods in their study which is confusing and not necessary. In addition, the text is poorly structured, very repetitive and complicated written, which makes it very difficult to follow the story and to capture the key messages.
(3) The authors focus on triggers but are not investigating preconditioning and preparing factors at all. Rockfall is prepared by numerous processes including frost weathering or active-layer thaw that breakdown rock without that the rock is released as rockfall. The rock can be stored within the rockwall and later released as secondary rockfall. The authors can detect when the rockfall occurrence is but they should discuss more critically what they measure and what the limitations of their approach are.
(4) A priori the authors assume that freezing and permafrost are the major rockfall triggers. Other factors like earthquakes are excluded but can be an important factor. The authors mention rainfall and climbers as potential triggers but are not analysing the role of precipitation and climbers in detail. Permafrost and frost weathering can be important preparing factors but precipitation and climbers can be a major trigger of secondary rockfall, which is not equally addressed in this paper. In addition, frost weathering is very qualitatively addressed in terms of efficient freeze-thaw cycles and the discussion lacks papers presenting new data and alternative interpretation of the data (e.g. Girard et al., 2013). Purely thermal processes were identified to trigger rockfall (Collins and Stock, 2016), however, the authors mentions these processes without going into detail. The paper lacks a multi-hypothesis approach where other potential triggers than permafrost and freezing are equally introduced and discussed.
For detailed comments, see the attached pdf.
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CC1: 'Reply on RC1', Jacques Mourey, 09 Jun 2021
First of all, thank you for the two thorough reviews. They made us really think about what were the main objectives and novelties of our study.
There are on average 35 fatal accidents per year in summer mountaineering in France (Soulé et al. 2014). On average, 3.7 of those fatal accidents have occurred every summer in the Grand couloir du Goûter since 1990 (Mourey et al. 2018), hence its reputation in the media as the "couloir of death". Rockfalls directly explain at least 29% of the accidents and are partly involved in the accidents due to a fall, which account for 50% of the accidents (Mourey et al. 2018). Rockfalls are therefore one of the main factors that explain this high accident rate and contribute in making it one of the most accident-prone area in the Alps for mountaineers.
It is this particular context that motivated our study with the objective of acquiring knowledge on rockfalls and their triggering factors in the Grand couloir du Goûter that would be of interest to mountaineers and help them adapt to the local risk of rockfalls. This would potentially reduce the number of accidents in this sector.
Regarding this motivation, we provided one of the few continuous databases on rockfall activity in permafrost conditions with day and night and weather independent conditions thanks to the deployment of a seismic array. To our knowledge, only Guillemot et al., 2020, GJI, provided such database (which is not analyzed in terms of triggers), and other previous rockfall databases were either continuous but focusing on local unglaciated mountain areas (Helmstetter and Garambois, 2010; Dietze et al. 2017a, 2017b, 2020; Hibert et al. 2011, 2017, Durand et al. 2018; DeRoin, N., and McNutt, S. R., 2012) or at regional scales (Dussauge et al. 2003; Dammeier et al. 2011; Manconi et al. 2016; Hibert et al. 2019), or on discontinuous monitoring of rockfalls at high elevation thanks to sensors other than seismic (TLS for example). This database allowed us to investigate the daily and sub-daily scale of rockfall triggering, thanks also to the complementary monitoring of other parameters (precipitations, ground and air temperatures, frequentation, snow cover). This new data provides complementary observations to seasonal, annual, or decadal observations usually investigated (Gruber and Haeberli, 2007; Krautblatter and Moser, 2009; Ravanel and Deline, 2010; Allen and Huggel, 2013; Draebing et al. 2014). We therefore show the effect of temperature and snow melt at this time-scale, as well as anomalous peaks of rockfall activity, that correlate with high human frequentation. Although the effect of temperature at the hourly scales are well known by mountaineers, the phenomenon has never been quantified.
Also, our data on the mountaineers traffic on Mont Blanc route show that climbers are not aware of the variations in rockfall frequency and/or that they cannot/won't adapt their behavior to this hazard. Therefore, the cross-comparison of data on rockfalls and climbers traffic in the couloir provide a second novel findings regarding the behaviour of mountaineers facing rockfall danger. This justifies all the more the importance of acquiring knowledge on rockfalls and their triggering factors in the local context of the Grand couloir du Goûter and to disseminate it to the mountaineers to encourage their adaptation. This comparison also allowed us to identify the type of knowledge needed by climbers to adapt in the most efficient way. This interdisciplinary analysis between rockfall hazard and mountaineers behaviour is also quite new.
The two reviewers point out that our work is a case-study, and wonder how it can be generalized. We fully agree with this case-study comment. We however oppose to this argument the exceptional site studied here with a very high accidents rate which, to our point of view, justify by itself focusing on this specific case-study with a strong operational objective. Furthermore, in a context where several international scientific entities (IPCC, MRI, WMO) clearly identify a profound lack of knowledge on the vulnerability to climate change of socio-economic activities in mountains and a lack of medium- and long-term efficiency of adaptation strategies in glaciated mountain areas (McDowell et al. 2019), our study is a relevant example of operational research that promotes adaptation measures. We agree with the referees that this motivation was not sufficiently put forward. In a new version of the article we propose to emphasize this point by completely reformulating the introduction, discussion and conclusion (see specific comments below).
In particular, we also propose to limit the parts where our results confirm previous studies on the effects of snowmelt and permafrost degradation at the seasonal scale but to emphasize the value of our data in identifying hourly triggering factors and discussing the effects of thermal processes as triggering factors.
Finally as raised out by the two reviewers, we will clarify all the method sections, for instance by adding figures to explain the classification of the seismic data.
Specific answer to Referee 1:
Thank you for your very thorough evaluation of our work. Your suggestions will help us improve our work. Based on the two evaluations we received, we decided to strongly modify our manuscript. We appreciated that you pointed out the rich database obtained here. Your comments allowed us to realize that the main novel aspects of our work were drawn into more classical ones. For instance the hourly and daily triggering of rockfall is very little investigated in permafrost conditions due to the absence of such a continuous rockfall database, that only seismic monitoring can get. This will lead us to rewrite the introduction and discussion, and better explain both the motivations of this work and the main novel points.
The other main novelty of this study is its operational objective: acquire knowledge on the danger of rockfalls in the specific context of the Grand couloir du Goûter, on the classic route up Mont Blanc, and the dissemination of this knowledge to the mountaineering community in order to promote the adaptation of mountaineers and try to reduce the number of accidents. Therefore, we will follow the main suggestion of referee 2 and reduce the sections on the identification of the rockfalls triggering factors (chapter 2 and discussion) and we will add two sections in the discussion on the “Interest of the acquired knowledge for mountaineers” and the “Dissemination of the acquired knowledge to the mountain community and implementation of management measures of the route”.
(1) In the current version of the manuscript we agree that we are not investigating mountaineers' vulnerability but rockfall hazard. However, in a new version of the article we plan to add two sections in the discussion in which we explain what are the interests of the acquired knowledge for mountaineers to mitigate the hazard and the dissemination of the acquired knowledge to the mountain community and the implementation of management measures of the route.
Concerning the link between rockfalls and accidents, we precise in the introduction that, according to the study of the accidents that occured in the Goûter area between 1990 and 2017 (Mourey et al., 2018), rockfalls explain directly 29% of the accidents and are partly involved in the accidents due to a fall, which account for 50% of the accidents. Rockfalls are therefore one of the main factors explaining this high accident rate. In the revised version of our manuscript, the introduction will focus more on the motivation of our study, and therefore the context should be clearer.
(2) In the revised version of our manuscript, we will give more details on the study area, how mountaineers are organising their ascent and when they have to cross the Grand couloir du Goûter in the “Study site” section. The introduction will be fully reorganised in order to better explain our objectives, justify them according to scientific literature and link them better with the methods we used and the triggering factors that were presented in section 2. According to your recommendations, section 2 will be integrated into the introduction, and lead to a clear objective of the study related both to the rockfall activity/triggering at hourly and daily scales, and to the adaptation of mountaineers to this hazard.
We will add precisions on the method used, especially the classification method of seismic signals. Although this classification is well described in previous mentioned paper (e.g. Helmstetter and Garambois, 2010), we will describe more in detail the types of signals we record on our site of study. We will particularly add a figure to show them, that will highlight the classification process. We will also add details on how to obtain the seismic energy from the signal envelope.
Concerning the monitoring of the snow cover, we will add precisions on the type of camera we used, the processing of the data, etc. Photographs taken by the camera are presented in figure 8 to illustrate the evolution of the snow cover in the couloir and temperature from temperature logger C3 is also presented in figure 8.
We will remove the CRYOGRID model. Following the restructuring of the manuscript it is not needed. We only used the CRYOGRID model to show that the active layer is the deepest at the end of the summer season, which has already been shown by other studies (Magnin et al. 2017 ; Pogliottio et al. 2015). Moreover, it limits the number of time series and clarifies the manuscript.
(3) We will be more precise in the description of preparing and preconditioning factors in the description of the site. We will, among other things, precise that the topographical and geological characteristics of the Grand Couloir du Goûter are particularly favourable to the triggering of rockfalls and due to the fracturing of the rock in the area and previous rockfalls in the couloir, many rocks/blocks are mobilizable as secondary rockfalls. We will also note that the couloir is in the altitudinal range where permafrost is degrading, which has been identified as the one where rock collapses related to permafrost degradation occur the most (Ravanel et al. 2017).
(4) We agree that we focused our results too much on the effects of freezing and permafrost degradation as triggering factors. According to the suggestions of Referee 2, we will reformulate the discussion accordingly. However we propose to insist on thermal processes as triggering factors. Our results allow us to quantify the correlation between rockfalls and different parameters (rainfall, temperature, frequentation) on a daily scale. To do so we can compute the cross‐correlation function between hourly rockfall rates (R) and other parameters P at the hourly rate, defined by CR,P(t) =Sum (Pi R(ti)P(ti + t)). cf Helmstetter & Garambois, 2010). The results show that the correlation explaining the rockfall rates at the hourly scale the most is the air temperature measured at the Gouter station. The correlation is low (0.28), but significant (much higher than the peak of all the correlations; see the attached document). A time-delay of 2h is found between the temperature time-series and the hourly rockfall rates. Based on this finding we can discuss in more detail the effects of “purely thermal processes” on rockfalls triggering and compare our results with other studies such as Collins and Stock, 2016 and Draebing, 2020.
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AC1: 'Reply on RC1', Jacques Mourey, 10 Jun 2021
First of all, thank you for the two thorough reviews. They made us really think about what were the main objectives and novelties of our study.
There are on average 35 fatal accidents per year in summer mountaineering in France (Soulé et al. 2014). On average, 3.7 of those fatal accidents have occurred every summer in the Grand couloir du Goûter since 1990 (Mourey et al. 2018), hence its reputation in the media as the "couloir of death". Rockfalls directly explain at least 29% of the accidents and are partly involved in the accidents due to a fall, which account for 50% of the accidents (Mourey et al. 2018). Rockfalls are therefore one of the main factors that explain this high accident rate and contribute in making it one of the most accident-prone area in the Alps for mountaineers.
It is this particular context that motivated our study with the objective of acquiring knowledge on rockfalls and their triggering factors in the Grand couloir du Goûter that would be of interest to mountaineers and help them adapt to the local risk of rockfalls. This would potentially reduce the number of accidents in this sector.
Regarding this motivation, we provided one of the few continuous databases on rockfall activity in permafrost conditions with day and night and weather independent conditions thanks to the deployment of a seismic array. To our knowledge, only Guillemot et al., 2020, GJI, provided such database (which is not analyzed in terms of triggers), and other previous rockfall databases were either continuous but focusing on local unglaciated mountain areas (Helmstetter and Garambois, 2010; Dietze et al. 2017a, 2017b, 2020; Hibert et al. 2011, 2017, Durand et al. 2018; DeRoin, N., and McNutt, S. R., 2012) or at regional scales (Dussauge et al. 2003; Dammeier et al. 2011; Manconi et al. 2016; Hibert et al. 2019), or on discontinuous monitoring of rockfalls at high elevation thanks to sensors other than seismic (TLS for example). This database allowed us to investigate the daily and sub-daily scale of rockfall triggering, thanks also to the complementary monitoring of other parameters (precipitations, ground and air temperatures, frequentation, snow cover). This new data provides complementary observations to seasonal, annual, or decadal observations usually investigated (Gruber and Haeberli, 2007; Krautblatter and Moser, 2009; Ravanel and Deline, 2010; Allen and Huggel, 2013; Draebing et al. 2014). We therefore show the effect of temperature and snow melt at this time-scale, as well as anomalous peaks of rockfall activity, that correlate with high human frequentation. Although the effect of temperature at the hourly scales are well known by mountaineers, the phenomenon has never been quantified.
Also, our data on the mountaineers traffic on Mont Blanc route show that climbers are not aware of the variations in rockfall frequency and/or that they cannot/won't adapt their behavior to this hazard. Therefore, the cross-comparison of data on rockfalls and climbers traffic in the couloir provide a second novel findings regarding the behaviour of mountaineers facing rockfall danger. This justifies all the more the importance of acquiring knowledge on rockfalls and their triggering factors in the local context of the Grand couloir du Goûter and to disseminate it to the mountaineers to encourage their adaptation. This comparison also allowed us to identify the type of knowledge needed by climbers to adapt in the most efficient way. This interdisciplinary analysis between rockfall hazard and mountaineers behaviour is also quite new.
The two reviewers point out that our work is a case-study, and wonder how it can be generalized. We fully agree with this case-study comment. We however oppose to this argument the exceptional site studied here with a very high accidents rate which, to our point of view, justify by itself focusing on this specific case-study with a strong operational objective. Furthermore, in a context where several international scientific entities (IPCC, MRI, WMO) clearly identify a profound lack of knowledge on the vulnerability to climate change of socio-economic activities in mountains and a lack of medium- and long-term efficiency of adaptation strategies in glaciated mountain areas (McDowell et al. 2019), our study is a relevant example of operational research that promotes adaptation measures. We agree with the referees that this motivation was not sufficiently put forward. In a new version of the article we propose to emphasize this point by completely reformulating the introduction, discussion and conclusion (see specific comments below).
In particular, we also propose to limit the parts where our results confirm previous studies on the effects of snowmelt and permafrost degradation at the seasonal scale but to emphasize the value of our data in identifying hourly triggering factors and discussing the effects of thermal processes as triggering factors.
Finally as raised out by the two reviewers, we will clarify all the method sections, for instance by adding figures to explain the classification of the seismic data.
Specific answer to Referee 1:
Thank you for your very thorough evaluation of our work. Your suggestions will help us improve our work. Based on the two evaluations we received, we decided to strongly modify our manuscript. We appreciated that you pointed out the rich database obtained here. Your comments allowed us to realize that the main novel aspects of our work were drawn into more classical ones. For instance the hourly and daily triggering of rockfall is very little investigated in permafrost conditions due to the absence of such a continuous rockfall database, that only seismic monitoring can get. This will lead us to rewrite the introduction and discussion, and better explain both the motivations of this work and the main novel points.
The other main novelty of this study is its operational objective: acquire knowledge on the danger of rockfalls in the specific context of the Grand couloir du Goûter, on the classic route up Mont Blanc, and the dissemination of this knowledge to the mountaineering community in order to promote the adaptation of mountaineers and try to reduce the number of accidents. Therefore, we will follow the main suggestion of referee 2 and reduce the sections on the identification of the rockfalls triggering factors (chapter 2 and discussion) and we will add two sections in the discussion on the “Interest of the acquired knowledge for mountaineers” and the “Dissemination of the acquired knowledge to the mountain community and implementation of management measures of the route”.
(1) In the current version of the manuscript we agree that we are not investigating mountaineers' vulnerability but rockfall hazard. However, in a new version of the article we plan to add two sections in the discussion in which we explain what are the interests of the acquired knowledge for mountaineers to mitigate the hazard and the dissemination of the acquired knowledge to the mountain community and the implementation of management measures of the route.
Concerning the link between rockfalls and accidents, we precise in the introduction that, according to the study of the accidents that occured in the Goûter area between 1990 and 2017 (Mourey et al., 2018), rockfalls explain directly 29% of the accidents and are partly involved in the accidents due to a fall, which account for 50% of the accidents. Rockfalls are therefore one of the main factors explaining this high accident rate. In the revised version of our manuscript, the introduction will focus more on the motivation of our study, and therefore the context should be clearer.
(2) In the revised version of our manuscript, we will give more details on the study area, how mountaineers are organising their ascent and when they have to cross the Grand couloir du Goûter in the “Study site” section. The introduction will be fully reorganised in order to better explain our objectives, justify them according to scientific literature and link them better with the methods we used and the triggering factors that were presented in section 2. According to your recommendations, section 2 will be integrated into the introduction, and lead to a clear objective of the study related both to the rockfall activity/triggering at hourly and daily scales, and to the adaptation of mountaineers to this hazard.
We will add precisions on the method used, especially the classification method of seismic signals. Although this classification is well described in previous mentioned paper (e.g. Helmstetter and Garambois, 2010), we will describe more in detail the types of signals we record on our site of study. We will particularly add a figure to show them, that will highlight the classification process. We will also add details on how to obtain the seismic energy from the signal envelope.
Concerning the monitoring of the snow cover, we will add precisions on the type of camera we used, the processing of the data, etc. Photographs taken by the camera are presented in figure 8 to illustrate the evolution of the snow cover in the couloir and temperature from temperature logger C3 is also presented in figure 8.
We will remove the CRYOGRID model. Following the restructuring of the manuscript it is not needed. We only used the CRYOGRID model to show that the active layer is the deepest at the end of the summer season, which has already been shown by other studies (Magnin et al. 2017 ; Pogliottio et al. 2015). Moreover, it limits the number of time series and clarifies the manuscript.
(3) We will be more precise in the description of preparing and preconditioning factors in the description of the site. We will, among other things, precise that the topographical and geological characteristics of the Grand Couloir du Goûter are particularly favourable to the triggering of rockfalls and due to the fracturing of the rock in the area and previous rockfalls in the couloir, many rocks/blocks are mobilizable as secondary rockfalls. We will also note that the couloir is in the altitudinal range where permafrost is degrading, which has been identified as the one where rock collapses related to permafrost degradation occur the most (Ravanel et al. 2017).
(4) We agree that we focused our results too much on the effects of freezing and permafrost degradation as triggering factors. According to the suggestions of Referee 2, we will reformulate the discussion accordingly. However we propose to insist on thermal processes as triggering factors. Our results allow us to quantify the correlation between rockfalls and different parameters (rainfall, temperature, frequentation) on a daily scale. To do so we can compute the cross‐correlation function between hourly rockfall rates (R) and other parameters P at the hourly rate, defined by CR,P(t) =Sum (Pi R(ti)P(ti + t)). cf Helmstetter & Garambois, 2010). The results show that the correlation explaining the rockfall rates at the hourly scale the most is the air temperature measured at the Gouter station. The correlation is low (0.28), but significant (much higher than the peak of all the correlations; see the attached document). A time-delay of 2h is found between the temperature time-series and the hourly rockfall rates. Based on this finding we can discuss in more detail the effects of “purely thermal processes” on rockfalls triggering and compare our results with other studies such as Collins and Stock, 2016 and Draebing, 2020.
Citation: https://doi.org/10.5194/nhess-2021-128-AC1
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CC1: 'Reply on RC1', Jacques Mourey, 09 Jun 2021
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RC2: 'Comment on nhess-2021-128', Anonymous Referee #2, 24 May 2021
The authors present an empirical study of rockfall activity and potentially responsible environmental conditions as well as a link to the affected part of our society for a study site in the French Alps. They describe seismically detected rockfall rates and link the seasonal and diurnal patterns to several possible drivers and triggers. The general scope of the manuscript addresses indeed a timely and valuable reasearch gap. However, I am afraid that the actual conduction of the study and especially the quality of the manuscript are a fair bit from suitable for prompt publication. The presented study is in general very premature and unorganised, and in many cases simply speculative due to unsupported claims, breaks in argumentative logic and lacks of reasoning. I shall note that most of these shortcomings can be accounted for in a thorough revision, and that the structural flaws can be managed, which would eventually render the study in principle for publication.
The title is actually a good example to illustrate the flaws mentioned above. While rockfalls are indeed addressed, I did not find any robust analysis of the vulnerability. There is no quantitative exposure analysis or an estimation of the change in exposure with changing boundary conditions (season, weather conditions, climber passing windows etc.). Likewise, I do not see a deep expression of interdisciplinarity. Most of the material presented stems from evaluation of instrument data deployed on site. There is neither a real link to adjacent scientific fields nor a scientifically valid analysis/evaluation of the social scientific aspects of the study. Finally, although this is just an example, the title gives a lot of attention to the site, more than 50 % of the words used. To me this reads mostly like a study by Mont Blanc enthusiasts.
Fundamentally, I missed a clear hypothesis that the authors wish to test in pursuing their research. Accordingly, the introduction did not gain sufficient momentum to motivate and justify the study and to provide the right background. Sadly, the interesting link to the societal relevance (l. 38-44) is not really picked up later in the article. The scope (l. 65-66) thus simply appears to be: collecting a site specific catalogue of rockfall events and test if their occurrence pattern is in agreement with drivers and triggers that the community has reported on already a long time ago. Overall, the study was quite disappointing in just reporting findings that the scientific community has already embraced for years to decades. At least this is the implication of the discussion. Without more emphasis on novel findings, the material reduces itself to a case study. I encourage the authors to revise their text to avoid this (mis)interpretation and make clear where the study contributes new, original findings.
Section 2 (rockfall triggers) is very exhaustive and not really aligned to the context of the study. It reads like a review of rockfall triggers, but I could not really find where it points the reader to existing knowledge gaps (hence research oppotunities) or where it motivates the methodological approach employed in the study. I suggest to significantly shorten this section and add concise support for the actual study. Why is it important to mention all these drivers and triggers? And how does this background contribute to a better emplacement of the study? In addition, I advise the authors to clearly distinct between drivers and triggers, as these are two fundamentally different terms and they should not be used interchangably or mixed in their appearance throughout the text.
Section 3.1 is quite long and reads like a glossy promotion of Mont Blanc for tourists. Either stablish a clear link to the questions pursued by the study or remove the section. In other words, this section is only needed if better motivated and linked to the objectives.
The study contains several argumentation weaknesses. One example is the link between number of accidents and rockfalls occurrences. The authors have argued that the number of accidents scales with the number of climbers on track, which is logical. But how have the authors constrained the link between rockfalls and accidents? There is not even any information if the accidents are due to rockfall injuries, at all. See my detailed comments for further argumentation issues.
The general reasoning (l. 17-19) is pulling the straw man argument. The authors claim that the processes in their study area are “intense” (whatever that means) and claim that yet there has been limited research in this area. This is not a valid argument. Many other regions of the Alps and other mountains in the world have been studied intensively, so why engaging with just another case study – especially since it seems to show the same trends as most of the other global sites, already studied before? Please revise and provide a proper justification for the study. Just saying we worked there because no one else has, is not enough. You can easily pull the climbing route motivation, here.
The description of the methods is not always sufficiently clear to be reproductive. For example, the parameters or criteria used to define rockfall events from the seismic time series is vague. Specifically, l. 177-179 leave a lot of questionmarks: which waveform or spectral criteria were used? What did the control events look like? How were they constrained in the field? What software was used? And so on. Similarly, the beam forming method needs to be described more rigorously and also with a few more sentences of information for people unfamiliar with this technique. Which filter windows were used? Which wave velocity (or slowness)? How much time before onset and after event end were added? How were the signals pre-processed in general? Were there always data from all stations available?
I do not see how the authors were able to extract rockfall volume from the seismic data. I am not even sure how they extracted the energy of the impacting rock mass. How has the spatially mobile source been taken into account? Which wave attenuation model has been used? See for example the description of Le Roy et al. or the scaling efforts by Hibert et al. (all cited) for a proper way of rigorously describing an approach. I strongly suggest to expand that section and either explain how volume has been constrained or leave the link to volumes. In a similar manner, I am not sure the description of how oblique imagery was converted to aerial extent of snow allows reproduction of the results with the currently provided additional information. Please make sure, the readers can reconcile your analysis steps to be in a position that allows you to draw proper conclusions. A further example of unclear methodological clarity occurs in l. 234-235. Please give the numbers you used to constrain your model. Which values have been taken from “geotechnical surveys” and which reference needs to be added here? It is frustrating to be asked to take these words at face value without any chance to check for their appropriateness, not to speak of the model code used for the thermal modelling.
The presentation of results is often biased by unmotivated and apparently arbitrary classifications of continuous data into clusters. See for example l. 253-257. Why not simply plotting histograms, density estimate plots or boxplots of for example the energy of the events? A similar example is the definition of three seasonal periods (fig. 8, l. 318-321). Why three and not four or five? Or, why designating groups from continuous data first of all?
The discussion, especially the drivers of rockfall activity (l. 375-395) is very speculative and is lacking support by the own findings. This flaw is already reflected by the wording (“It is likely that this difference…”, “probably all the more active…”, “It is likely that nocturnal…”, “It probably leads to the cementation…” and so on. I understand that the measured variables do not allow to pin down these unknowns. This is fair enough but then the discussion should not dive too deeply into this direction. If the data do not allow to constrain the mechanisms of rockfall initiation then the discussion should not put too much emphasis on this question. Another very specualtive, or at least not well constrained, claim is given in l. 434-436: I do not agree that the data allow to claim that climbers trigger rockfalls. A further quite speculative section is at l. 470-476; this discussion about potential future trigger dynamics is simply beyond your presented data. I suggest to remove this part (and other parts that are not direct derivates of your own data).
The language is a fair bit from acceptale for publication. I started to mark typos, awkward phrases and wrongly used references but gave up after a few pages. I strongly suggest the authors seek the advice of a native speaker and, more importantly, that they check their material for the numerous small technical issues (spelling, punctation, consistency, referencing, figure font size).
l. 1-3, the title is way too long and focused on the case study. I suggest to reduce it by about 50 %, focusing on the research question, not the study site.
l. 14, what are “rockfall destabilisations”?
l. 17-18, what means “intensity of the geomorphological processes at work”? Please use a clear scientific language.
l. 24, quantify the term “frequent”, you have the numbers at hand. Make the abstract as conclusive and informative as possible.
l. 27, how do you know the climbers are not aware of their risk? Certainly this is not possible by the methodological approach presented in this study. Have you used interviews to be able to make this claim?
l. 32, what means “deep”? Revise.
l. 40, remove one “to climate change”.
l. 42, what are “well thought-out plans”?
l. 52, “most accident-prone…”. Without any comparison to other sites this statement cannot be made.
l. 55, explain why/how climbers are vulnerable in this specific case.
l. 67-69, this laudable goal is not touched upon in the study (except for two brief points in the discussion that sadly lack a reference). I suggest to either expand the study into the adaptation part or leave this sentence out, here.
l. 75, use “Alpine” not “alpine”, also at later occurences
l. 76, “McColl”, not “Mc Coll”
l. 78, what is the difference in this context between “climatic” and “meteorological”?
l. 83, “Moore” not “Moores”
l. 91-92, repetitive, consider removing. Almost the same point has been made already above.
l. 96, what means “streaming” or water? Check terminology
l. 97, “drag force”, not “flow force”
Fig. 1, small grey text is barely readable. Also, where would convective rock heating come from in a solid medium?
l. 132, define MBM or, ideally do not use such acronyms first of all.
l. 143, Are you sure that “couloir” is a proper technical English term?
Fig. 2, actually this aerial image makes it really hard to understand the situation. I had to use it in combination with fig. 6 back and forth to understand your study area. I encourage the authors to use a topographic map or at least a hillshade map to better illustrate/justify their instrumentation scheme. It would also help to clearly state where the climbers are at risk. From fig. 2 and 6 it looks like it is the passage between C1 and C2.
l. 212, “area in m^3”? How would that work?
l. 252, “significant activity”, this statement needs comparison to other sites. With just that number of 1 event per 37 minutes I would not dare to say this is or is not a significant rockfall activity. Actually, this rate also needs to be normalised by area. Please provide an estimate of the source area, otherwise it is really hard to judge how significant that value is.
Fig. 5, is the day time in CET or CEST or UTC? Also, in the right y-axis add the normalisation by hour to the axis label.
l. 281, “recordings were recorded”?
Fig. 6, interesting modelling exercise, but how do the temporal reconstructions match up with your few month long empirical data set? Why do we need this look back into the recent past?
l. 298, where does the uncertainty range come from? Mention this in the methods before, and ideally, propagate this uncertainty also to the 41.9 and 58.1 % values later in that sentence.
l. 303, “sometime significantly” (add an “s”) and please quantify, i.e. define what you mean with significantly.
Fig. 7, where do the blue vertical errors come from. How do you know these are rockfalls potentially caused by climbers? These arrows appear absolutely subjective and arbitrary to me.
l. 330-343 and 349-360, I do not really get the point here. What is the point in mentioning that all the findings are in agreement with previous findings? What is new then in thist study other than confirming already confirmed knowledge? Please shorten significantly and/or focus on those points that add new insight or are not in agreement with the commonly expected patterns, which were based on often longer and/or better instrumented surveys.
Fig. 8, consider using line plots instead of bar charts.
l. 364, use “covaried” instead of correlated, or quantify this correlation.
l. 370-375, so can you clarify if the cause is insolation or conduction with a time lag? If not, make clear that you cannot decipher the relative importance of these two triggers.
Fig. 9, avoid overplotting of the axes/graphs.
l. 439, why 50 %? Did the number of 10 % in the methods section not rather point at 90 % false detections?
l. 441, “machine learning”, not “deep learning”
l. 456-457, this is quite arm waving. Of course it always helps to put more sensors. But how many crack meters do you want to deploy in that large area? And how do you know where to put them? This is one of the main limitations on instrumentation driven research in high mountain terrain. Actually, I think we have a quite good understanding of the triggers of mass wasting processes. Nevertheless, it will remain a stochastic process at the catchment scale.
l. 464, the statement of permafrost degradation needs a reference.
l. 466-467, also here a reference is needed.
l. 469, “percentage points”, please use 4.5–5.0 %
l. 473, provide a reference after “Drias-climat”
l. 489, a better estimation of the vulnerability should take into account the time of climbers spent in the window of rockfall trajectories and the rate of events happening as a function of daytime, season and trigger conditions. Currently, I can only see broad tendencies for inceased rockfall activity like melting season and late summer, and afternoon to night.
l. 490-491, this imlies that the accidents are actually related to rockfalls. Is this a given? From the teft it rather reads like the accident rate scales with number of climbers on track.
l. 496, I disagree that this study has demonstrated that it has included these criteria in the analysis.
l. 498, I also could not find recommended adaptation methods in the discussion.
l. 502-503, please give the references (URLs) to these outreach activities.
Citation: https://doi.org/10.5194/nhess-2021-128-RC2 -
CC2: 'Reply on RC2', Jacques Mourey, 09 Jun 2021
First of all, thank you for the two thorough reviews. They made us really think about what were the main objectives and novelties of our study.
There are on average 35 fatal accidents per year in summer mountaineering in France (Soulé et al. 2014). On average, 3.7 of those fatal accidents have occurred every summer in the Grand couloir du Goûter since 1990 (Mourey et al. 2018), hence its reputation in the media as the "couloir of death". Rockfalls directly explain at least 29% of the accidents and are partly involved in the accidents due to a fall, which account for 50% of the accidents (Mourey et al. 2018). Rockfalls are therefore one of the main factors that explain this high accident rate and contribute in making it one of the most accident-prone area in the Alps for mountaineers.
It is this particular context that motivated our study with the objective of acquiring knowledge on rockfalls and their triggering factors in the Grand couloir du Goûter that would be of interest to mountaineers and help them adapt to the local risk of rockfalls. This would potentially reduce the number of accidents in this sector.
Regarding this motivation, we provided one of the few continuous databases on rockfall activity in permafrost conditions with day and night and weather independent conditions thanks to the deployment of a seismic array. To our knowledge, only Guillemot et al., 2020, GJI, provided such database (which is not analyzed in terms of triggers), and other previous rockfall databases were either continuous but focusing on local unglaciated mountain areas (Helmstetter and Garambois, 2010; Dietze et al. 2017a, 2017b, 2020; Hibert et al. 2011, 2017, Durand et al. 2018; DeRoin, N., and McNutt, S. R., 2012) or at regional scales (Dussauge et al. 2003; Dammeier et al. 2011; Manconi et al. 2016; Hibert et al. 2019), or on discontinuous monitoring of rockfalls at high elevation thanks to sensors other than seismic (TLS for example). This database allowed us to investigate the daily and sub-daily scale of rockfall triggering, thanks also to the complementary monitoring of other parameters (precipitations, ground and air temperatures, frequentation, snow cover). This new data provides complementary observations to seasonal, annual, or decadal observations usually investigated (Gruber and Haeberli, 2007; Krautblatter and Moser, 2009; Ravanel and Deline, 2010; Allen and Huggel, 2013; Draebing et al. 2014). We therefore show the effect of temperature and snow melt at this time-scale, as well as anomalous peaks of rockfall activity, that correlate with high human frequentation. Although the effect of temperature at the hourly scales are well known by mountaineers, the phenomenon has never been quantified.
Also, our data on the mountaineers traffic on Mont Blanc route show that climbers are not aware of the variations in rockfall frequency and/or that they cannot/won't adapt their behavior to this hazard. Therefore, the cross-comparison of data on rockfalls and climbers traffic in the couloir provide a second novel findings regarding the behaviour of mountaineers facing rockfall danger. This justifies all the more the importance of acquiring knowledge on rockfalls and their triggering factors in the local context of the Grand couloir du Goûter and to disseminate it to the mountaineers to encourage their adaptation. This comparison also allowed us to identify the type of knowledge needed by climbers to adapt in the most efficient way. This interdisciplinary analysis between rockfall hazard and mountaineers behaviour is also quite new.
The two reviewers point out that our work is a case-study, and wonder how it can be generalized. We fully agree with this case-study comment. We however oppose to this argument the exceptional site studied here with a very high accidents rate which, to our point of view, justify by itself focusing on this specific case-study with a strong operational objective. Furthermore, in a context where several international scientific entities (IPCC, MRI, WMO) clearly identify a profound lack of knowledge on the vulnerability to climate change of socio-economic activities in mountains and a lack of medium- and long-term efficiency of adaptation strategies in glaciated mountain areas (McDowell et al. 2019), our study is a relevant example of operational research that promotes adaptation measures. We agree with the referees that this motivation was not sufficiently put forward. In a new version of the article we propose to emphasize this point by completely reformulating the introduction, discussion and conclusion (see specific comments below).
In particular, we also propose to limit the parts where our results confirm previous studies on the effects of snowmelt and permafrost degradation at the seasonal scale but to emphasize the value of our data in identifying hourly triggering factors and discussing the effects of thermal processes as triggering factors.
Finally as raised out by the two reviewers, we will clarify all the method sections, for instance by adding figures to explain the classification of the seismic data.
Specific answer to referee 2:
(1) In accordance with all the modifications planned in this revised manuscript, and in order to focus more on the research objective we propose the following title : Multimethods monitoring of rockfall activity on the classic route up Mont Blanc to promote the adaptation of mountaineers.
Concerning the interdisciplinarity of this work, Darbelley F. 2014. Rethinking inter-and transdisciplinarity:undisciplined knowledge and the emergence of a new thought style. Futures 65, 163-174. DOI:10.1016/j.futures.2014.10.009, define interdisciplinarity as follows: “Interdisciplinarity: this brings into play two or more established disciplines so that they interact dynamically to allow the complexity of a given object of study to be described, analyzed and understood”. As we use measurement methods, concepts and analysis methods from several disciplines (human geography, seismology, remote sensing, geomorphology) and we cross the results from each method to answer the same research question, we consider our work as interdisciplinary.
(2) In reaction to the second comment, we will completely rework the introduction and the discussion of the article to show the interest and the new findings of our study. We conducted this study because the Goûter couloir sector is very popular for mountaineers and has a particularly high accident rate. We have shown in a previous study (Moureyet al. 2018) that rockfall appears to be one of the main factors explaining accidents (see comment below for more details on how we established the link between rockfall and accidents). Our prime objective was therefore not to gain new knowledge about the factors triggering rockfalls in high alpine mountains. Our objective was to document rockfalls and their triggering factors specifically in the Goûter couloir, in order to help mountaineers adapt to rockfall hazard in this particularly accident-prone sector. Despite this site-specific study, we also show that the observations we provided follow classical patterns of rockfall triggering at the seasonal scale in permafrost areas. This shows that the results obtained on our site of study - in particular the novel hourly and daily time scales of triggering - can be representative of other areas. We will therefore completely revise the organization of the article to justify this objective and show how we have achieved it. We will integrate section 2 ( Rockfall Triggering Factors) into the introduction and better connect it to our objectives and the method used. In the discussion, we will reduce the section in which we explain that our work confirms the results of previous studies at the seasonal scale (although this is an interesting result in itself). Instead, we will emphasize our results at the daily scale. Databases on rock destabilization in high alpine mountains at such a fine scale are rare and our results bring interesting elements on the factors of rock fall triggering at the daily scale. Indeed, if the triggering of rockfalls in high mountains is often associated with permafrost degradation (multiannual scale) and freeze-thaw cycles (daily and seasonal scale), our results suggest that temperature variations and thermal stress is an important triggering factors at the hourly scale in the grand couloir du Goûter.
In order to meet the main objective of this study, which is to promote the adaptation of mountaineers to the risk of rockfall, specifically for the Goûter couloir, we will also add two sections in the discussion on the "Interest of the acquired knowledge for mountaineers" and "Dissemination of the acquired knowledge to the mountain community and implementation of management measures of the route".
(3) We will significantly shorten section 2 and integrate it to the introduction in order to justify the methods we used. We will be more precise in the description of preparing and preconditioning factors in the description of the site. We will among other things precise that the topographical and geological characteristics of the Grand Couloir du Goûter are particularly favourable to the triggering of rockfalls and due to the fracturing of the rock in the area and previous rockfalls in the couloir, many rocks/blocks are mobilizable as secondary rockfalls. We will also note that the couloir is in the altitudinal range where permafrost is degrading, which has been identified as the one where rock collapses related to permafrost degradation occur the most (Ravanel et al. 2017).
(4) We will remove the section 3.1 and keep only one section in which we describe the study site and better describe the site, how mountaineers are organising their ascent and when they have to cross the Grand couloir du Goûter.
(5) We explained in the introduction, based on a previous study (Mourey et al., 2018), that 29% of the accidents are due to a rockfall, and that rockfalls are also involved in parts of the 50% of accidents due to a climber fall. Rockfalls are therefore one of the main factors that explain this high accident rate. The identification of the cause of the accidents was based on the analysis of the reports that rescuers drafted after each accident one by one. This method is well described in the mentioned study: Mourey et al. 2018. We will make a specific attention to clarify this point in the future introduction and site-study sections.
(6) We will follow this later proposition to better justify our study in the new introduction. We engaged with this new case study because it is an area with a high accident rate and rockfalls are one of the main factors of this accidentology. Despite this accidentology, almost no studies have been undertaken to document this hazard.
(7) Thanks for these comments also pointed out by reviewer 1. This shows that our methods section lacks sufficient explanations that we will provide in our revised manuscript (See also our answer to the referee 1 to the similar question). We will add the clarifications required including a new figure to better explain the classification. In addition we will provide the keys to understand the rockfall localization methods, which is well described in Lacroix and Helmstetter (2011), but some parameters were indeed slightly adapted to this case-study.
(8) The seismic energy is defined by integrating the seismic envelope over the signal duration. We will define it in the text. Therefore it is not a rockfall energy but the seismic energy recorded by the array. This can then be transformed onto a volume, as LeRoy or Hibert do, but requires calibration that we don’t have. It would also require to better take into account the effect of the snow cover on the impact attenuation, which is not possible without calibration data in hard/soft snow conditions and bare rock conditions. So this step is a study by itself. Therefore we are not dealing with volumes and just keep the analysis of the seismic energy recorded. As we explained, this seismic energy reflects on the first order the variation of the rockfall volumes in similar snow conditions, as all the sources are coming from the same area. We will pay attention in the revised manuscript to clarify this aspect.
We will also remove the CRYOGRID model. Following the restructuring of the manuscript it is not needed. We only used the CRYOGRID model to show that the active layer is the deepest at the end of the summer season, which has already been shown by other studies (Magnin et al. 2017 ; Pogliottio et al. 2015). Moreover, it limits the number of time series and clarifies the manuscript.
(9) The three periods in the discussion were defined according to the variations in rockfall frequencies at the seasonal scale. Designating groups from continuous data allows us to clarify the discussion and easily designate a period of the season. We feel it makes the flow of the discussion easier. In the revised manuscript, we will better explain how and why we designed our 3 seasonal periods.
(10) We propose to shorten the discussion on the triggering factors related to snowmelt and permafrost degradation for which we effectively confirm previous studies. The fact that our results are in agreement with these studies is, however, a result in itself and gives even more credibility to our results. On the other hand, we propose to add details on the interest of our results to better evaluate the effects of daily temperature variations and thermal stress on the triggering of rock falls. It seems to us that this is a point in which our data provide interesting and innovative results on the triggering of rockfalls in high alpine mountains.
Finally, as we have already stated, in order to make the link with the first objective of our study ( the acquisition of knowledge to favour the adaptation of mountaineers to the local risk of rock falls) we will add two sections on the "Interest of the acquired knowledge for mountaineers" and "Dissemination of the acquired knowledge to the mountain community and implementation of management measures of the route". The conclusion will also be rewritten.
We do not claim that our data “allow to claim that climbers trigger rockfalls”. We explain that according to our fields observations some rockfalls are triggered by the climbers themselves and it is possible that 2 anomalies in the daily distribution of rockfalls may be due to anthropogenic triggers. On days when rockfalls are least frequent we can estimate that the “natural” triggers are the least effective and the rockfalls triggered by mountaineers can be highlighted. Therefore we can support the assumption that mountaineers are triggering rockfalls with the example of a day when rockfalls activity is very limited but strictly coincides with the frequentation.
The section "Climate change and future projections" is indeed not directly linked to the acquired data. However, it seems important to us to specify that the situation in the future will probably not improve, which justifies all the more a better consideration of the rockfall hazard by mountaineers. We will clarify this point and move the section "Climate change and future projections" after the section on "implementation of management measure of the route".
(11) In order to improve the quality of the writing we will have the manuscript corrected by a native english speaker. Referee 1 also sended a document with several suggestions to improve the texte that we will take into account.
Citation: https://doi.org/10.5194/nhess-2021-128-CC2 -
AC2: 'Reply on RC2', Jacques Mourey, 10 Jun 2021
First of all, thank you for the two thorough reviews. They made us really think about what were the main objectives and novelties of our study.
There are on average 35 fatal accidents per year in summer mountaineering in France (Soulé et al. 2014). On average, 3.7 of those fatal accidents have occurred every summer in the Grand couloir du Goûter since 1990 (Mourey et al. 2018), hence its reputation in the media as the "couloir of death". Rockfalls directly explain at least 29% of the accidents and are partly involved in the accidents due to a fall, which account for 50% of the accidents (Mourey et al. 2018). Rockfalls are therefore one of the main factors that explain this high accident rate and contribute in making it one of the most accident-prone area in the Alps for mountaineers.
It is this particular context that motivated our study with the objective of acquiring knowledge on rockfalls and their triggering factors in the Grand couloir du Goûter that would be of interest to mountaineers and help them adapt to the local risk of rockfalls. This would potentially reduce the number of accidents in this sector.
Regarding this motivation, we provided one of the few continuous databases on rockfall activity in permafrost conditions with day and night and weather independent conditions thanks to the deployment of a seismic array. To our knowledge, only Guillemot et al., 2020, GJI, provided such database (which is not analyzed in terms of triggers), and other previous rockfall databases were either continuous but focusing on local unglaciated mountain areas (Helmstetter and Garambois, 2010; Dietze et al. 2017a, 2017b, 2020; Hibert et al. 2011, 2017, Durand et al. 2018; DeRoin, N., and McNutt, S. R., 2012) or at regional scales (Dussauge et al. 2003; Dammeier et al. 2011; Manconi et al. 2016; Hibert et al. 2019), or on discontinuous monitoring of rockfalls at high elevation thanks to sensors other than seismic (TLS for example). This database allowed us to investigate the daily and sub-daily scale of rockfall triggering, thanks also to the complementary monitoring of other parameters (precipitations, ground and air temperatures, frequentation, snow cover). This new data provides complementary observations to seasonal, annual, or decadal observations usually investigated (Gruber and Haeberli, 2007; Krautblatter and Moser, 2009; Ravanel and Deline, 2010; Allen and Huggel, 2013; Draebing et al. 2014). We therefore show the effect of temperature and snow melt at this time-scale, as well as anomalous peaks of rockfall activity, that correlate with high human frequentation. Although the effect of temperature at the hourly scales are well known by mountaineers, the phenomenon has never been quantified.
Also, our data on the mountaineers traffic on Mont Blanc route show that climbers are not aware of the variations in rockfall frequency and/or that they cannot/won't adapt their behavior to this hazard. Therefore, the cross-comparison of data on rockfalls and climbers traffic in the couloir provide a second novel findings regarding the behaviour of mountaineers facing rockfall danger. This justifies all the more the importance of acquiring knowledge on rockfalls and their triggering factors in the local context of the Grand couloir du Goûter and to disseminate it to the mountaineers to encourage their adaptation. This comparison also allowed us to identify the type of knowledge needed by climbers to adapt in the most efficient way. This interdisciplinary analysis between rockfall hazard and mountaineers behaviour is also quite new.
The two reviewers point out that our work is a case-study, and wonder how it can be generalized. We fully agree with this case-study comment. We however oppose to this argument the exceptional site studied here with a very high accidents rate which, to our point of view, justify by itself focusing on this specific case-study with a strong operational objective. Furthermore, in a context where several international scientific entities (IPCC, MRI, WMO) clearly identify a profound lack of knowledge on the vulnerability to climate change of socio-economic activities in mountains and a lack of medium- and long-term efficiency of adaptation strategies in glaciated mountain areas (McDowell et al. 2019), our study is a relevant example of operational research that promotes adaptation measures. We agree with the referees that this motivation was not sufficiently put forward. In a new version of the article we propose to emphasize this point by completely reformulating the introduction, discussion and conclusion (see specific comments below).
In particular, we also propose to limit the parts where our results confirm previous studies on the effects of snowmelt and permafrost degradation at the seasonal scale but to emphasize the value of our data in identifying hourly triggering factors and discussing the effects of thermal processes as triggering factors.
Finally as raised out by the two reviewers, we will clarify all the method sections, for instance by adding figures to explain the classification of the seismic data.
Specific answer to referee 2:
(1) In accordance with all the modifications planned in this revised manuscript, and in order to focus more on the research objective we propose the following title : Multimethods monitoring of rockfall activity on the classic route up Mont Blanc to promote the adaptation of mountaineers.
Concerning the interdisciplinarity of this work, Darbelley F. 2014. Rethinking inter-and transdisciplinarity:undisciplined knowledge and the emergence of a new thought style. Futures 65, 163-174. DOI:10.1016/j.futures.2014.10.009, define interdisciplinarity as follows: “Interdisciplinarity: this brings into play two or more established disciplines so that they interact dynamically to allow the complexity of a given object of study to be described, analyzed and understood”. As we use measurement methods, concepts and analysis methods from several disciplines (human geography, seismology, remote sensing, geomorphology) and we cross the results from each method to answer the same research question, we consider our work as interdisciplinary.
(2) In reaction to the second comment, we will completely rework the introduction and the discussion of the article to show the interest and the new findings of our study. We conducted this study because the Goûter couloir sector is very popular for mountaineers and has a particularly high accident rate. We have shown in a previous study (Moureyet al. 2018) that rockfall appears to be one of the main factors explaining accidents (see comment below for more details on how we established the link between rockfall and accidents). Our prime objective was therefore not to gain new knowledge about the factors triggering rockfalls in high alpine mountains. Our objective was to document rockfalls and their triggering factors specifically in the Goûter couloir, in order to help mountaineers adapt to rockfall hazard in this particularly accident-prone sector. Despite this site-specific study, we also show that the observations we provided follow classical patterns of rockfall triggering at the seasonal scale in permafrost areas. This shows that the results obtained on our site of study - in particular the novel hourly and daily time scales of triggering - can be representative of other areas. We will therefore completely revise the organization of the article to justify this objective and show how we have achieved it. We will integrate section 2 ( Rockfall Triggering Factors) into the introduction and better connect it to our objectives and the method used. In the discussion, we will reduce the section in which we explain that our work confirms the results of previous studies at the seasonal scale (although this is an interesting result in itself). Instead, we will emphasize our results at the daily scale. Databases on rock destabilization in high alpine mountains at such a fine scale are rare and our results bring interesting elements on the factors of rock fall triggering at the daily scale. Indeed, if the triggering of rockfalls in high mountains is often associated with permafrost degradation (multiannual scale) and freeze-thaw cycles (daily and seasonal scale), our results suggest that temperature variations and thermal stress is an important triggering factors at the hourly scale in the grand couloir du Goûter.
In order to meet the main objective of this study, which is to promote the adaptation of mountaineers to the risk of rockfall, specifically for the Goûter couloir, we will also add two sections in the discussion on the "Interest of the acquired knowledge for mountaineers" and "Dissemination of the acquired knowledge to the mountain community and implementation of management measures of the route".
(3) We will significantly shorten section 2 and integrate it to the introduction in order to justify the methods we used. We will be more precise in the description of preparing and preconditioning factors in the description of the site. We will among other things precise that the topographical and geological characteristics of the Grand Couloir du Goûter are particularly favourable to the triggering of rockfalls and due to the fracturing of the rock in the area and previous rockfalls in the couloir, many rocks/blocks are mobilizable as secondary rockfalls. We will also note that the couloir is in the altitudinal range where permafrost is degrading, which has been identified as the one where rock collapses related to permafrost degradation occur the most (Ravanel et al. 2017).
(4) We will remove the section 3.1 and keep only one section in which we describe the study site and better describe the site, how mountaineers are organising their ascent and when they have to cross the Grand couloir du Goûter.
(5) We explained in the introduction, based on a previous study (Mourey et al., 2018), that 29% of the accidents are due to a rockfall, and that rockfalls are also involved in parts of the 50% of accidents due to a climber fall. Rockfalls are therefore one of the main factors that explain this high accident rate. The identification of the cause of the accidents was based on the analysis of the reports that rescuers drafted after each accident one by one. This method is well described in the mentioned study: Mourey et al. 2018. We will make a specific attention to clarify this point in the future introduction and site-study sections.
(6) We will follow this later proposition to better justify our study in the new introduction. We engaged with this new case study because it is an area with a high accident rate and rockfalls are one of the main factors of this accidentology. Despite this accidentology, almost no studies have been undertaken to document this hazard.
(7) Thanks for these comments also pointed out by reviewer 1. This shows that our methods section lacks sufficient explanations that we will provide in our revised manuscript (See also our answer to the referee 1 to the similar question). We will add the clarifications required including a new figure to better explain the classification. In addition we will provide the keys to understand the rockfall localization methods, which is well described in Lacroix and Helmstetter (2011), but some parameters were indeed slightly adapted to this case-study.
(8) The seismic energy is defined by integrating the seismic envelope over the signal duration. We will define it in the text. Therefore it is not a rockfall energy but the seismic energy recorded by the array. This can then be transformed onto a volume, as LeRoy or Hibert do, but requires calibration that we don’t have. It would also require to better take into account the effect of the snow cover on the impact attenuation, which is not possible without calibration data in hard/soft snow conditions and bare rock conditions. So this step is a study by itself. Therefore we are not dealing with volumes and just keep the analysis of the seismic energy recorded. As we explained, this seismic energy reflects on the first order the variation of the rockfall volumes in similar snow conditions, as all the sources are coming from the same area. We will pay attention in the revised manuscript to clarify this aspect.
We will also remove the CRYOGRID model. Following the restructuring of the manuscript it is not needed. We only used the CRYOGRID model to show that the active layer is the deepest at the end of the summer season, which has already been shown by other studies (Magnin et al. 2017 ; Pogliottio et al. 2015). Moreover, it limits the number of time series and clarifies the manuscript.
(9) The three periods in the discussion were defined according to the variations in rockfall frequencies at the seasonal scale. Designating groups from continuous data allows us to clarify the discussion and easily designate a period of the season. We feel it makes the flow of the discussion easier. In the revised manuscript, we will better explain how and why we designed our 3 seasonal periods.
(10) We propose to shorten the discussion on the triggering factors related to snowmelt and permafrost degradation for which we effectively confirm previous studies. The fact that our results are in agreement with these studies is, however, a result in itself and gives even more credibility to our results. On the other hand, we propose to add details on the interest of our results to better evaluate the effects of daily temperature variations and thermal stress on the triggering of rock falls. It seems to us that this is a point in which our data provide interesting and innovative results on the triggering of rockfalls in high alpine mountains.
Finally, as we have already stated, in order to make the link with the first objective of our study ( the acquisition of knowledge to favour the adaptation of mountaineers to the local risk of rock falls) we will add two sections on the "Interest of the acquired knowledge for mountaineers" and "Dissemination of the acquired knowledge to the mountain community and implementation of management measures of the route". The conclusion will also be rewritten.
We do not claim that our data “allow to claim that climbers trigger rockfalls”. We explain that according to our fields observations some rockfalls are triggered by the climbers themselves and it is possible that 2 anomalies in the daily distribution of rockfalls may be due to anthropogenic triggers. On days when rockfalls are least frequent we can estimate that the “natural” triggers are the least effective and the rockfalls triggered by mountaineers can be highlighted. Therefore we can support the assumption that mountaineers are triggering rockfalls with the example of a day when rockfalls activity is very limited but strictly coincides with the frequentation.
The section "Climate change and future projections" is indeed not directly linked to the acquired data. However, it seems important to us to specify that the situation in the future will probably not improve, which justifies all the more a better consideration of the rockfall hazard by mountaineers. We will clarify this point and move the section "Climate change and future projections" after the section on "implementation of management measure of the route".
(11) In order to improve the quality of the writing we will have the manuscript corrected by a native english speaker. Referee 1 also sended a document with several suggestions to improve the texte that we will take into account.
-
CC2: 'Reply on RC2', Jacques Mourey, 09 Jun 2021
Peer review completion
