12 May 2023
 | 12 May 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

Abstract. In this study we present a model for the global Probabilistic Hydrological Estimation of LandSlides (PHELS). PHELS estimates the daily hazard of hydrologically-triggered landslides at a coarse spatial resolution of 36 km, by combining landslide susceptibility (LSS) and (percentiles of) hydrological variable(s). The latter include daily rainfall, a 7-day antecedent rainfall index (ARI7) or root-zone soil moisture content (rzmc) as hydrological predictor variables, or the combination of rainfall and rzmc. The hazard estimates with any of these predictor variables have areas under the Receiver Operation Characteristic curve (AUC) above 0.68. The best performance was found with combined rainfall and rzmc predictors (AUC = 0.79), which resulted in the least missed alarms (especially during spring) and false alarms. Furthermore, PHELS provides hazard uncertainty estimates by generating ensemble simulations based on repeated sampling of LSS and the hydrological predictor variables. The estimated hazard uncertainty follows the behaviour of the input variable uncertainties, is about 13.6 % of the estimated hazard value on average across the globe and in time, and smallest for very low and very high hazard values.

Anne Felsberg et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on Felsberg et al., PHELS Global Landslide Model', Ben Mirus, 16 Jun 2023
    • AC1: 'Reply on RC1', Anne Felsberg, 17 Aug 2023
  • RC2: 'Comment on egusphere-2023-869', Clàudia Abancó, 06 Jul 2023
    • AC2: 'Reply on RC2', Anne Felsberg, 17 Aug 2023

Anne Felsberg et al.

Video supplement

Animation of PHELS global ensemble average hazard (rzmc&rainfall) for the year 2015 Anne Felsberg

Anne Felsberg et al.


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Latest update: 26 Sep 2023
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 least amount of missed and false alarms. The ensemble approach moreover allowed to estimate the associated prediction uncertainty.