Abstract
Determining rainfall thresholds for landsliding is crucial in landslide hazard evaluation and early warning system development, yet challenging in data-scarce regions. Using freely available satellite rainfall data in a reproducible automated procedure, the bootstrap-based frequentist threshold approach, coupling antecedent rainfall (AR) and landslide susceptibility data as proposed by Monsieurs et al., has proved to provide a physically meaningful regional AR threshold equation in the western branch of the East African Rift. However, previous studies could only rely on global- and continental-scale rainfall and susceptibility data. Here, we use newly available regional-scale susceptibility data to test the robustness of the method to different data configurations. This leads us to improve the threshold method through using stratified data selection to better exploit the data distribution over the whole range of susceptibility. In addition, we discuss the effect of outliers in small data sets on the estimation of parameter uncertainties and the interest of not using the bootstrap technique in such cases. Thus improved, the method effectiveness shows strongly reduced sensitivity to the used susceptibility data and is satisfyingly validated by new landslide occurrences in the East African Rift, therefore successfully passing first transferability tests.
Highlights
Rainfall-triggered landslides pose a severe threat to societies on all continents [1,2]
62 mm in the least susceptible areas to AR = 7 mm in the highest susceptibility pixels, respectively, landslide have been reported (Equation (10)). These triggering AR conditions might seem low at first for which landslide have been reported (Equation (10)). These triggering AR conditions might seem sight when compared to values obtained in other studies that look into antecedent rainfall conditions low at first sight when compared to values obtained in other studies that look into antecedent rainfall based on gauge measurements, e.g., a required minimum of 139 mm cumulated over 20 days to trigger conditions based on gauge measurements, e.g., a required minimum of 139 mm cumulated over 20 landslides in the NE Himalaya [68]; a mean triggering rainfall accumulation of 376 mm for periods ranging between 15 and 40 days in NW Spain [69]; a critical rainfall amount of 450 mm over a two-week period in the greater Durban region in South Africa [70]
We propose a modified antecedent rainfall–susceptibility (AR-S) threshold approach that improves on the initial AR-S method of [35], being transferable to other data sets for landsliding and S
Summary
Rainfall-triggered landslides pose a severe threat to societies on all continents [1,2]. The conservative low-exceedance probability thresholds are most reliable, affected by a degraded distribution of data used for the threshold calibration (FNR ≈ TPE). 62 mm in the least susceptible areas to AR = 7 mm in the highest susceptibility pixels, respectively, landslide have been reported (Equation (10)) These triggering AR conditions might seem low at first for which landslide have been reported (Equation (10)). The triggering values obtained in our study are conceivable given the following main factors contributing to their relative lower values: (1) the exponential decay function applied in our AR calculation (Equation (1)) in contrast to the values obtained in the above cited studies through mere accumulation; (2) the high weathering conditions in the tropical context of the WEAR that may increase the sensitivity to landsliding [50]; and (3) the underestimation of the area-averaged SRE [33,56] used in the calculation of AR (Equation (1))
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