Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 18, issue 8
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:
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

Viewed

Total article views: 4,893 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,135 1,614 144 4,893 131 145
  • HTML: 3,135
  • PDF: 1,614
  • XML: 144
  • Total: 4,893
  • BibTeX: 131
  • EndNote: 145
Views and downloads (calculated since 12 Dec 2017)
Cumulative views and downloads (calculated since 12 Dec 2017)

Viewed (geographical distribution)

Total article views: 4,893 (including HTML, PDF, and XML) Thereof 4,539 with geography defined and 354 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Nov 2025
Download
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.
Read more
Share
Special issue
Landslide early warning systems: monitoring systems, rainfall...
Altmetrics
Final-revised paper
Preprint