Abstract. Rainfall threshold determination is a pressing issue in
the landslide scientific community. While major improvements have been made towards more reproducible techniques for the identification of triggering
conditions for landsliding, the now well-established rainfall intensity or
event-duration thresholds for landsliding suffer from several
limitations. Here, we propose a new approach of the frequentist method for
threshold definition based on satellite-derived antecedent rainfall
estimates directly coupled with landslide susceptibility data. Adopting a
bootstrap statistical technique for the identification of threshold
uncertainties at different exceedance probability levels, it results in
thresholds expressed as AR = (α±Δα)⋅S(β±Δβ), where AR is antecedent rainfall (mm), S is
landslide susceptibility, α and β are scaling parameters, and
Δα and Δβ are their uncertainties. The main
improvements of this approach consist in (1) using spatially continuous
satellite rainfall data, (2) giving equal weight to rainfall characteristics
and ground susceptibility factors in the definition of spatially varying
rainfall thresholds, (3) proposing an exponential antecedent rainfall
function that involves past daily rainfall in the exponent to account for
the different lasting effect of large versus small rainfall,
(4) quantitatively exploiting the lower parts of the cloud of data points, most
meaningful for threshold estimation, and (5) merging the uncertainty on
landslide date with the fit uncertainty in a single error estimation. We
apply our approach in the western branch of the East African Rift based on
landslides that occurred between 2001 and 2018, satellite rainfall estimates
from the Tropical Rainfall Measurement Mission Multi-satellite Precipitation
Analysis (TMPA 3B42 RT), and the continental-scale map of landslide
susceptibility of Broeckx et al. (2018) and provide the first regional rainfall
thresholds for landsliding in tropical Africa.
A susceptibility-based rainfall threshold approach for landslide occurrence
