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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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NHESS | Articles | Volume 20, issue 3
Nat. Hazards Earth Syst. Sci., 20, 815–829, 2020
https://doi.org/10.5194/nhess-20-815-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Nat. Hazards Earth Syst. Sci., 20, 815–829, 2020
https://doi.org/10.5194/nhess-20-815-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 24 Mar 2020

Research article | 24 Mar 2020

Probabilistic landslide susceptibility analysis in tropical mountainous terrain using the physically based r.slope.stability model

Johnnatan Palacio Cordoba et al.

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Status: closed
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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (19 Jan 2020) by Mario Parise
AR by Johnnatan Palacio on behalf of the Authors (20 Jan 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (03 Feb 2020) by Mario Parise
RR by Anonymous Referee #2 (12 Feb 2020)
ED: Publish subject to minor revisions (review by editor) (13 Feb 2020) by Mario Parise
AR by Johnnatan Palacio on behalf of the Authors (17 Feb 2020)  Author's response    Manuscript
ED: Publish as is (20 Feb 2020) by Mario Parise
Publications Copernicus
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Short summary
Landslides triggered by rainfall are very common phenomena in complex tropical environments such as the Colombian Andes. In this work, we perform probabilistic analyses with r.slope.stability for landslide susceptibility analysis. We test the model in the La Arenosa catchment, northern Colombian Andes. The results are compared to those yielded with the corresponding deterministic analyses and with other physically based models applied in the same catchment.
Landslides triggered by rainfall are very common phenomena in complex tropical environments such...
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