the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling
Zdenko Heyvaert
Jean Poesen
Thomas Stanley
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: open (until 28 Jun 2023)
Anne Felsberg et al.
Video supplement
Animation of PHELS global ensemble average hazard (rzmc&rainfall) for the year 2015 Anne Felsberg https://doi.org/10.5281/zenodo.7882809
Anne Felsberg et al.
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