Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 8
Articles | Volume 19, issue 8
https://doi.org/10.5194/gmd-19-3075-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-3075-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 8
Model description paper
 | 
21 Apr 2026
Model description paper |  | 21 Apr 2026

Landslide-Tsurrogate v1.0: a computationally efficient framework for probabilistic tsunami hazard assessment applied to Mayotte (France)

Cléa Denamiel, Alexis Marboeuf, Anne Mangeney, Anne Le Friant, Marc Peruzzetto, Antoine Lucas, Manuel J. Castro Díaz, and Enrique Fernández-Nieto

Viewed

Total article views: 614 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
267 324 23 614 18 35
  • HTML: 267
  • PDF: 324
  • XML: 23
  • Total: 614
  • BibTeX: 18
  • EndNote: 35
Views and downloads (calculated since 12 Jan 2026)
Cumulative views and downloads (calculated since 12 Jan 2026)

Viewed (geographical distribution)

Total article views: 614 (including HTML, PDF, and XML) Thereof 518 with geography defined and 96 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 21 Apr 2026
Download
Short summary
Landslide-Tsurrogate v1.0 is an open-source Python/MATLAB tool that create surrogate models that replace costly numerical simulations. These models estimate tsunami hazards from submarine landslides in a few seconds. Based on polynomial chaos expansions, they also enable sensitivity analyses, fast probabilistic results, and user-friendly visualization. Tested in Mayotte, Landslide-Tsurrogate v1.0 can be applied to any coastal region.
Read more
Share