Articles | Volume 17, issue 2
https://doi.org/10.5194/nhess-17-225-2017
https://doi.org/10.5194/nhess-17-225-2017
Research article
 | 
21 Feb 2017
Research article |  | 21 Feb 2017

Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change

Susana Almeida, Elizabeth Ann Holcombe, Francesca Pianosi, and Thorsten Wagener

Viewed

Total article views: 5,512 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,780 2,589 143 5,512 120 125
  • HTML: 2,780
  • PDF: 2,589
  • XML: 143
  • Total: 5,512
  • BibTeX: 120
  • EndNote: 125
Views and downloads (calculated since 12 Sep 2016)
Cumulative views and downloads (calculated since 12 Sep 2016)

Viewed (geographical distribution)

Total article views: 5,512 (including HTML, PDF, and XML) Thereof 5,158 with geography defined and 354 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 18 Mar 2024
Download
Short summary
Landslides threaten communities globally, yet predicting their occurrence is challenged by uncertainty about slope properties and climate change. We present an approach to identify the dominant drivers of slope instability and the critical thresholds at which slope failure may occur. This information helps decision makers to target data acquisition to improve landslide predictability, and supports policy development to reduce landslide occurrence and impacts in highly uncertain environments.
Altmetrics
Final-revised paper
Preprint