Assessing uncertainties in landslide susceptibility predictions in a changing environment (Styrian Basin, Austria)
- 1Department of Geography, Friedrich Schiller University Jena, Jena, 07743, Germany
- 2Remote Sensing and Geoinformation Department, JOANNEUM RESEARCH Forschungsgesellschaft mbH, Graz, 8010, Austria
- 3Centre for Low-Emission Transport, AIT Austrian Institute of Technology GmbH, Vienna, 1210, Austria
- 4Wegener Centre for Climate and Global Change, Regional Climate Research Group, Karl-Franzens-University Graz, Graz, 8010, Austria
- 1Department of Geography, Friedrich Schiller University Jena, Jena, 07743, Germany
- 2Remote Sensing and Geoinformation Department, JOANNEUM RESEARCH Forschungsgesellschaft mbH, Graz, 8010, Austria
- 3Centre for Low-Emission Transport, AIT Austrian Institute of Technology GmbH, Vienna, 1210, Austria
- 4Wegener Centre for Climate and Global Change, Regional Climate Research Group, Karl-Franzens-University Graz, Graz, 8010, Austria
Abstract. The assessment of uncertainties in landslide susceptibility modelling in a changing environment is an important, yet often neglected task. In an Austrian case study, we investigated the uncertainty cascade in storylines of landslide susceptibility emerging from climate change and parametric landslide model uncertainty. In June 2009, extreme events of heavy thunderstorms occurred in the Styrian basin, triggering thousands of landslides. Using a storyline approach, we discovered a generally lower landslide susceptibility for pre-industrial climate, while for future climate (2071–2100) a potential increase of 35 % in highly susceptible areas (storyline of much heavier rain) may be compensated by much drier soils (-45 % areas highly susceptible to landsliding). However, the estimated uncertainties in predictions were generally high. While uncertainties related to within-event internal climate model variability were substantially lower than parametric uncertainties of the landslide susceptibility model (ratio of around 0.25), parametric uncertainties were of the same order as the climate scenario uncertainty for the higher warming levels (+3 K and +4 K). We suggest that in future uncertainty assessments, an improved availability of event-based landslide inventories and high-resolution soil and precipitation data will help to reduce parametric uncertainties of landslide susceptibility models used to assess the impacts of climate change on landslide hazard and risk.
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Journal article(s) based on this preprint
Raphael Knevels et al.
Interactive discussion
Status: closed
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RC1: 'Reviewer Comment on nhess-2022-154', Anonymous Referee #1, 30 Jun 2022
The manuscript is a good piece of science addressing a relevant issue, i.e. the evaluation of the uncertainties in landslide susceptibility modeling, taking into account also climate and environmental changes. The manuscript is clear, written in fluent English, and well-organized. The figures and tables are useful for presenting and discussing the results. The introduction is complete and useful for focusing on the topic. The method is well presented and the discussion is clear. However, I've found some issues that need to be addressed and explained before the manuscript can be reconsidered for publication.
Although earlier work by some of the authors is recalled in several places, the whole manuscript is rather long, so I would suggest trying to shorten it by at least 10% of the current length.Â
In the following, I list the main methodological issues I found in the manuscript. Overall, I think that minor revisions are needed.
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You use the term "storyline approach". I can't grab what you mean with "storyline" and "storyline approach". It seems to me that this term is not common in landslide analyses. I would suggest adding some explanationÂ
You defined the events that occurred in June 2009 and September 2014 as "extreme". How can you classify such events as "extreme"? Was a statistical analysis carried out?
You added in the susceptibility analysis the rainfall data on the landslide failure day, i.e. the triggering precipitation conditions. I think this is questionable and in contrast with the theoretical definition of susceptibility (see e.g. Reichenbach et al. (2018) [https://doi.org/10.1016/j.earscirev.2018.03.001]; van Westen et al. (2008) [https://doi.org/10.1016/j.enggeo.2008.03.010]). Landslide susceptibility is "the likelihood of a landslide occurring in an area on the basis of the local terrain and environmental conditions", therefore the triggering rainfall conditions should be removed from this analysis.Â
You also wrote "For the landslide susceptibility analysis, we linked predisposing and triggering factors to landslide occurrences.". I think this can be considered a methodological issue.ÂRegarding the environmental change simulation, you wrote (line 153) that "Adopting active forest management in the developed future LULC scenario, coniferous forest was replaced by climate resilient mixed forest".
If I have understood well, all LULC changes were defined to have a potentially positive effect on slope stability. If it is so, why not considering also some "negative" changes?Furthermore, you wrote (line 161) "Specifically, for each grid cell we determined the maximum three-hour rainfall intensity, and we took the maximum five-day rainfall."
In my opinion, also this is questionable, given that it is not always the most severe rainfall condition during a meteorological event that can trigger landslides. An explanation is needed.ÂFinally, I suggest using round brackets for units of measurement. Please check all over the text.
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AC1: 'Reply on RC1', Raphael Knevels, 16 Aug 2022
The comment was uploaded in the form of a supplement: https://nhess.copernicus.org/preprints/nhess-2022-154/nhess-2022-154-AC1-supplement.pdf
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AC1: 'Reply on RC1', Raphael Knevels, 16 Aug 2022
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RC2: 'Comment on nhess-2022-154', Anonymous Referee #2, 23 Jul 2022
This paper investigated the uncertainty cascade in storylines of landslide susceptibility emerging from climate change and parametric landslide model uncertainty. In general, this paper is interesting and rich in content.  However, there are many mistakes in the basic concept of landslide susceptibility, hazard and risk assessment.  In terms of landslide susceptibility prediction modeling process, the writing of this paper is rather rough.  In terms of organizational structure, the thesis is difficult to understand.  Therefore, it is recommended to reject the paper.Â
- Landslide susceptibility refers to the spatial probability of landslide occurrence affected by landslides them-selves conditioning factors, without considering triggering factors such as heavy rainfall, earthquake, et al. Landslide hazard refers to the spatial and time probability of landslide occurrence under condition factors and trigger factors. Hence, this paper focus on landslide susceptibility affected by land cover change and heavy rainfall. I believe this paper has problems with the basic concepts of landslide susceptibility.
- The writing ideas of this paper are very confused, and it is difficult for people to understand the specific steps and methods of the research.  Especially in the introduction and methods section.Â
- Where are the input and output variables of landslide susceptibility prediction modeling described in this paper?  How is the uncertainty problem concerned in this paper quantified?  Where are the environmental factor maps of landslide susceptibility and landslide susceptibility outcome maps?  These problems are not well reflected.
- The figures are not clear enough.
- The references are not new enough and are not representative enough.
- The uncertainty characteristics are assessed by which indexes? These description are not clear.
- There is insufficient analysis of feasible solutions to the problems in this paper.Â
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AC2: 'Reply on RC2', Raphael Knevels, 16 Aug 2022
The comment was uploaded in the form of a supplement: https://nhess.copernicus.org/preprints/nhess-2022-154/nhess-2022-154-AC2-supplement.pdf
Peer review completion






Interactive discussion
Status: closed
-
RC1: 'Reviewer Comment on nhess-2022-154', Anonymous Referee #1, 30 Jun 2022
The manuscript is a good piece of science addressing a relevant issue, i.e. the evaluation of the uncertainties in landslide susceptibility modeling, taking into account also climate and environmental changes. The manuscript is clear, written in fluent English, and well-organized. The figures and tables are useful for presenting and discussing the results. The introduction is complete and useful for focusing on the topic. The method is well presented and the discussion is clear. However, I've found some issues that need to be addressed and explained before the manuscript can be reconsidered for publication.
Although earlier work by some of the authors is recalled in several places, the whole manuscript is rather long, so I would suggest trying to shorten it by at least 10% of the current length.Â
In the following, I list the main methodological issues I found in the manuscript. Overall, I think that minor revisions are needed.
---
You use the term "storyline approach". I can't grab what you mean with "storyline" and "storyline approach". It seems to me that this term is not common in landslide analyses. I would suggest adding some explanationÂ
You defined the events that occurred in June 2009 and September 2014 as "extreme". How can you classify such events as "extreme"? Was a statistical analysis carried out?
You added in the susceptibility analysis the rainfall data on the landslide failure day, i.e. the triggering precipitation conditions. I think this is questionable and in contrast with the theoretical definition of susceptibility (see e.g. Reichenbach et al. (2018) [https://doi.org/10.1016/j.earscirev.2018.03.001]; van Westen et al. (2008) [https://doi.org/10.1016/j.enggeo.2008.03.010]). Landslide susceptibility is "the likelihood of a landslide occurring in an area on the basis of the local terrain and environmental conditions", therefore the triggering rainfall conditions should be removed from this analysis.Â
You also wrote "For the landslide susceptibility analysis, we linked predisposing and triggering factors to landslide occurrences.". I think this can be considered a methodological issue.ÂRegarding the environmental change simulation, you wrote (line 153) that "Adopting active forest management in the developed future LULC scenario, coniferous forest was replaced by climate resilient mixed forest".
If I have understood well, all LULC changes were defined to have a potentially positive effect on slope stability. If it is so, why not considering also some "negative" changes?Furthermore, you wrote (line 161) "Specifically, for each grid cell we determined the maximum three-hour rainfall intensity, and we took the maximum five-day rainfall."
In my opinion, also this is questionable, given that it is not always the most severe rainfall condition during a meteorological event that can trigger landslides. An explanation is needed.ÂFinally, I suggest using round brackets for units of measurement. Please check all over the text.
-
AC1: 'Reply on RC1', Raphael Knevels, 16 Aug 2022
The comment was uploaded in the form of a supplement: https://nhess.copernicus.org/preprints/nhess-2022-154/nhess-2022-154-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Raphael Knevels, 16 Aug 2022
-
RC2: 'Comment on nhess-2022-154', Anonymous Referee #2, 23 Jul 2022
This paper investigated the uncertainty cascade in storylines of landslide susceptibility emerging from climate change and parametric landslide model uncertainty. In general, this paper is interesting and rich in content.  However, there are many mistakes in the basic concept of landslide susceptibility, hazard and risk assessment.  In terms of landslide susceptibility prediction modeling process, the writing of this paper is rather rough.  In terms of organizational structure, the thesis is difficult to understand.  Therefore, it is recommended to reject the paper.Â
- Landslide susceptibility refers to the spatial probability of landslide occurrence affected by landslides them-selves conditioning factors, without considering triggering factors such as heavy rainfall, earthquake, et al. Landslide hazard refers to the spatial and time probability of landslide occurrence under condition factors and trigger factors. Hence, this paper focus on landslide susceptibility affected by land cover change and heavy rainfall. I believe this paper has problems with the basic concepts of landslide susceptibility.
- The writing ideas of this paper are very confused, and it is difficult for people to understand the specific steps and methods of the research.  Especially in the introduction and methods section.Â
- Where are the input and output variables of landslide susceptibility prediction modeling described in this paper?  How is the uncertainty problem concerned in this paper quantified?  Where are the environmental factor maps of landslide susceptibility and landslide susceptibility outcome maps?  These problems are not well reflected.
- The figures are not clear enough.
- The references are not new enough and are not representative enough.
- The uncertainty characteristics are assessed by which indexes? These description are not clear.
- There is insufficient analysis of feasible solutions to the problems in this paper.Â
-
AC2: 'Reply on RC2', Raphael Knevels, 16 Aug 2022
The comment was uploaded in the form of a supplement: https://nhess.copernicus.org/preprints/nhess-2022-154/nhess-2022-154-AC2-supplement.pdf
Peer review completion






Journal article(s) based on this preprint
Raphael Knevels et al.
Data sets
Event-based landslide susceptibility models (Styrian Basin, Austria) Knevels, Raphael; Petschko, Helene; Proske, Herwig; Leopold, Philip; Maraun, Douglas; Brenning, Alexander https://doi.org/10.5281/zenodo.6365228
Raphael Knevels et al.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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