Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling

Felsberg, Anne; Heyvaert, Zdenko; Poesen, Jean; Stanley, Thomas; De Lannoy, Gabriëlle J. M.

doi:https://doi.org/10.5194/nhess-23-3805-2023

Articles | Volume 23, issue 12

https://doi.org/10.5194/nhess-23-3805-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-23-3805-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 12

Research article

|

14 Dec 2023

Research article |

| 14 Dec 2023

Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling

Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy

Data sets

Ensemble of global landslide hazard from PHELS A. Felsberg et al. https://doi.org/10.5281/zenodo.7188355

Global Landslide Catalog Downloadable Products Gallery Landslides @ NASA https://maps.nccs.nasa.gov/arcgis/apps/MapAndAppGallery/index.html?appid=574f26408683485799d02e857e5d9521

Probabilistic Hydrological Estimation of LandSlides (PHELS): code and input A. Felsberg et al. https://doi.org/10.5281/zenodo.7194280

Model code and software

Probabilistic Hydrological Estimation of LandSlides (PHELS): code and input A. Felsberg et al. https://doi.org/10.5281/zenodo.7194280

Video supplement

Animation of PHELS global ensemble average hazard (rzmc&rainfall) for the year 2015 Anne Felsberg https://doi.org/10.5281/zenodo.7882809

Short summary

The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.