The added value of a regional landslide susceptibility assessment: The western branch of the East African Rift

Depicker, Arthur; Jacobs, Liesbet; Delvaux, Damien; Havenith, Hans-Balder; Mateso, Jean-Claude Maki; Govers, Gérard; Dewitte, Olivier

doi:10.1016/j.geomorph.2019.106886

Cited by 48 publications

(81 citation statements)

References 93 publications

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“…The WEAR covers an area of~350,000 km 2 in tropical Africa (Figure 1). This highly populated region is characterized by high rainfall intensities, recent seismicity, deeply weathered substrates, and a complex rift topography [33,47,[49][50][51][52]. These factors render the area highly susceptible to landsliding [45,49].…”

Section: Underreported Landslide Events In the Wearmentioning

confidence: 99%

“…This highly populated region is characterized by high rainfall intensities, recent seismicity, deeply weathered substrates, and a complex rift topography [33,47,[49][50][51][52]. These factors render the area highly susceptible to landsliding [45,49]. Indeed, recent studies incorporating observations from satellite images and fieldwork reveal high landslide activity, with hundreds of recent landslide events over the last 10 years accounting for more than 5000 individual landslides mapped in the area [44,49,50,53].…”

Section: Underreported Landslide Events In the Wearmentioning

confidence: 99%

“…These factors render the area highly susceptible to landsliding [45,49]. Indeed, recent studies incorporating observations from satellite images and fieldwork reveal high landslide activity, with hundreds of recent landslide events over the last 10 years accounting for more than 5000 individual landslides mapped in the area [44,49,50,53]. An event is defined as a single landslide or a group of landslides with a common trigger over the same area [29].…”

Section: Underreported Landslide Events In the Wearmentioning

confidence: 99%

“…An event is defined as a single landslide or a group of landslides with a common trigger over the same area [29]. Landslide types vary greatly from dominant shallow slides and earth and debris flows to less frequent rock avalanches and deep-seated rotational slides [44,47,49,50]. Rainfall has been identified as the prevailing trigger of these recent landslides [29,35,47,49,54].…”

Section: Underreported Landslide Events In the Wearmentioning

confidence: 99%

“…There is hence a strong need for testing the method's robustness with other data sets. A regional S model is now available for the WEAR [49], which outperforms the global and continental models with regard to prediction accuracy and geomorphological plausibility [49]. Moreover, the landslide event database used in [35] has now grown by about 27%.…”

Section: Introductionmentioning

confidence: 99%

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Towards a Transferable Antecedent Rainfall—Susceptibility Threshold Approach for Landsliding

Monsieurs

Dewitte

Depicker

et al. 2019

Water

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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 globaland 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. parameters through a spatially extended infinite-slope stability model [25]. However, the large required data input for well-calibrated process-based thresholds explains their current limitation to mostly applications at the hillslope scale or through numerical simulations [4,21,[25][26][27].The estimation of empirical rainfall thresholds is also associated with additional sources of uncertainty. Firstly, landslide inventories are inherently biased towards high-impact landslide events and regions that are most accessible, while their accuracy is constrained by the scientific validity of the reporting sources, especially in data-scarce low-capacity environments [1,[28][29][30][31]. Secondly, rainfall data comprise uncertainties related to the spatial representativeness of rain gauges or biases in satellite-derived estimates [32,33]. Thirdly, the definition of rainfall parameters, with intensity and duration forming the most frequently used parameter couple [3,5], varies strongly across studies [3]. Finally, the latter parameters' interdependence is problematic, obscuring the physical processes associated with the calculated thresholds [34].In order to account for and characterize threshold uncertainties, a growing number of reproducible statistical techniques have been developed [3]. A weakness of such methods is, however, that they are generally tailored to a specific area and available data sets, which often prevents straightforward transferability to other regions and data sets [35]. Nevertheless, transferability is not only essential for evaluating and comparing landslide hazard over different regions of the world [10,36], but also valuable in the context of the in...

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