Real-time prediction of rain-triggered lahars: incorporating seasonality and catchment recovery

Jones, Robbie; Manville, Vern; Peakall, Jeff; Froude, Melanie J.; Odbert, Henry M.

doi:https://doi.org/10.5194/nhess-17-2301-2017

Articles | Volume 17, issue 12

https://doi.org/10.5194/nhess-17-2301-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/nhess-17-2301-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 17, issue 12

Research article

|

13 Dec 2017

Research article |

| 13 Dec 2017

Real-time prediction of rain-triggered lahars: incorporating seasonality and catchment recovery

Robbie Jones, Vern Manville, Jeff Peakall, Melanie J. Froude, and Henry M. Odbert

Download

Final revised paper (published on 13 Dec 2017)
Preprint (discussion started on 23 May 2017)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'comments to the manuscript', Lucia Capra, 16 Jun 2017
- AC1: 'Response to RC1', Robbie Jones, 29 Aug 2017
RC2: 'Referee comments', Thomas Pierson, 04 Jul 2017
- AC2: 'Response to RC2', Robbie Jones, 29 Aug 2017

Peer-review completion

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

ED: Publish subject to minor revisions (further review by Editor) (07 Sep 2017) by Thomas Glade

AR by Robbie Jones on behalf of the Authors (16 Sep 2017) Author's response Manuscript

ED: Publish as is (21 Oct 2017) by Thomas Glade

Short summary

Rain-triggered lahars are significant secondary hazards at volcanoes where pyroclastic material is exposed to rainfall. Lahar risk mitigation typically relies upon ground-based flow detection or observation; however this study uses rainfall data and instrumental lahar records from the Belham valley, Montserrat, to devise new rain-triggered lahar prediction tools. These tools demonstrate the potential to effectively forecast lahars in real time, even in areas featuring strongly seasonal climates.