Probabilistic landslide ensemble prediction systems: lessons to be learned from hydrology

Canli, Ekrem; Mergili, Martin; Thiebes, Benni; Glade, Thomas

doi:https://doi.org/10.5194/nhess-18-2183-2018

Articles | Volume 18, issue 8

https://doi.org/10.5194/nhess-18-2183-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Landslide early warning systems: monitoring systems, rainfall...

https://doi.org/10.5194/nhess-18-2183-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 8

Research article

|

16 Aug 2018

Research article |

| 16 Aug 2018

Probabilistic landslide ensemble prediction systems: lessons to be learned from hydrology

Ekrem Canli, Martin Mergili, Benni Thiebes, and Thomas Glade

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Final revised paper (published on 16 Aug 2018)
Preprint (discussion started on 12 Dec 2017)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Comments on "Probabilistic landslide ensemble prediction systems: Lessons to be learned from hydrology"', Anonymous Referee #1, 12 Jan 2018
- AC1: 'Reply to comments by referee #1', Ekrem Canli, 07 May 2018
RC2: 'Review of the paper “Probabilistic landslide ensemble prediction systems: Lessons to be learned from hydrology” by Ekrem Canli et al', Anonymous Referee #2, 13 Jan 2018
- AC3: 'Reply to comments by referee #2', Ekrem Canli, 28 May 2018
RC3: 'Review', Anonymous Referee #3, 17 Jan 2018
- AC2: 'Reply to comments by referee #3', Ekrem Canli, 15 May 2018

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Reconsider after major revisions (further review by editor and referees) (28 May 2018) by Samuele Segoni

AR by Ekrem Canli on behalf of the Authors (04 Jul 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (09 Jul 2018) by Samuele Segoni

RR by Anonymous Referee #3 (14 Jul 2018)

Suggestions for revision or reasons for rejection

I have read the revised version of the manuscript and I have found that it was improved considerably. The Authors addressed all my comments and suggestions; in addition, all the comments made by other referees were taken into account.
My opinion is that the paper is now acceptable for publication.

I have only two comments about the literature on the topic. I saw that Authors made an accurate literature review, mentioning several recent papers. I would like to suggest other two recent papers dealing with rainfall thresholds for landslide prediction and with early warning systems for rainfall induced landslides.
In particular, the recent literature review made by Segoni et al. (2018) could be mentioned at page 2, line 19, to update the work made by Guzzetti and co-authors in 2007.
Moreover, the review of the “territorial” early warning systems for rainfall induced landslides operating around the world, made by Piciullo et al. (2018) could be mentioned at page 4, line 3. Reading this paper, in particular looking at its Figure 2, one can see that the nation-wide landslide early warning systems currently operating around the world are in Italy, Norway, Sri Lanka, and Bangladesh (period of activity retrieved by the authors from reliable references). Moreover, there are nation-wide systems in Taiwan, Japan and Malaysia, for which period of activity, and their current functioning, was assumed by the authors of the paper. I believe that this information could be added in the introduction of the paper (page 2, line 9).

References:
Piciullo, L., Calvello, M., Cepeda J.M.: Territorial early warning systems for rainfall-induced landslides, Earth-Science Reviews , 179, 228–247, doi:10.1016/j.earscirev.2018.02.013, 2018.
Segoni, S., Piciullo, L., Gariano S.L.: A review of the recent literature on rainfall thresholds for landslide occurrence, Landslides, doi:10.1007/s10346-018-0966-4, 2018.

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RR by Anonymous Referee #1 (17 Jul 2018)

ED: Publish subject to minor revisions (review by editor) (22 Jul 2018) by Samuele Segoni

AR by Ekrem Canli on behalf of the Authors (26 Jul 2018) Author's response Manuscript

ED: Publish as is (27 Jul 2018) by Samuele Segoni

AR by Ekrem Canli on behalf of the Authors (27 Jul 2018) Author's response Manuscript

Short summary

Regional-scale landslide forecasting traditionally strongly relies on empirical approaches and landslide-triggering rainfall thresholds. Today, probabilistic methods utilizing ensemble predictions are frequently used for flood forecasting. In our study, we specify how such an approach could also be applied for landslide forecasts and for operational landslide forecasting and early warning systems. To this end, we implemented a physically based landslide model in a probabilistic framework.