Field-based landslide susceptibility assessment in a data-scarce environment: the populated areas of the Rwenzori Mountains

Abstract

Abstract. The inhabited zone of the Ugandan Rwenzori Mountains is affected by landslides, frequently causing loss of life, damage to infrastructure and loss of livelihood. This area of ca. 1230 km2 is characterized by contrasting geomorphologic, climatic and lithological patterns, resulting in different landslide types. In this study, the spatial pattern of landslide susceptibility is investigated based on an extensive field inventory constructed for five representative areas within the region (153 km2) and containing over 450 landslides. To achieve a reliable susceptibility assessment, the effects of (1) using different topographic data sources and spatial resolutions and (2) changing the scale of assessment by comparing local and regional susceptibility models on the susceptibility model performances are investigated using a pixel-based logistic regression approach. Topographic data are extracted from different digital elevation models (DEMs) based on radar interferometry (SRTM and TanDEM-X) and optical stereophotogrammetry (ASTER DEM). Susceptibility models using the radar-based DEMs tend to outperform the ones using the ASTER DEM. The model spatial resolution is varied between 10, 20, 30 and 90 m. The optimal resolution depends on the location of the investigated area within the region but the lowest model resolution (90 m) rarely yields the best model performances while the highest model resolution (10 m) never results in significant increases in performance compared to the 20 m resolution. Models built for the local case studies generally have similar or better performances than the regional model and better reflect site-specific controlling factors. At the regional level the effect of distinguishing landslide types between shallow and deep-seated landslides is investigated. The separation of landslide types allows us to improve model performances for the prediction of deep-seated landslides and to better understand factors influencing the occurrence of shallow landslides such as tangent curvature and total rainfall. Finally, the landslide susceptibility assessment is overlaid with a population density map in order to identify potential landslide risk hotspots, which could direct research and policy action towards reduced landslide risk in this under-researched, landslide-prone region.

Towards a Transferable Antecedent Rainfall—Susceptibility Threshold Approach for Landsliding

“…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].…”

“…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].…”

“…Identifying thresholds for rainfall-triggered landsliding in data-scarce environments is challenging with respect to information on landslide occurrence and hydrophysical parameters, resulting in the quasi-absence of research on this topic in regions such as Central Africa [3] despite high hazard potential [29,[44][45][46][47]. The AR-S approach allowed defining the first regional threshold for landsliding in the western branch of the East African Rift (WEAR) [35].…”

Landslide Susceptibility Assessment at the Basin Scale for Rainfall- and Earthquake-Triggered Shallow Slides

“…In this study, 9 morphometric parameters were considered for the characterization of the shallow slides for the comparison between LI 1 and LI 2. The analysis of variance with a factor (one-way analysis of variance (ANOVA)) was used to assess whether the means of two groups of landslides (LI 1 and LI 2) were different [33,38,39]. For each parameter, the mean and standard deviation, the one-way ANOVA F test, and the respective statistical significance level (p-value) area are summarized in Table 1.…”

Supplementary material to "A susceptibility-based rainfall threshold approach for landslide occurrence"

“…Though being identified as a pressing issue in the scientific community, rainfall threshold research is almost nonexistent in Africa (Segoni et al, 2018) despite high levels of landslide susceptibility and hazard, especially in mountainous tropical Africa, characterized by intense rainfall, deep weathering profiles, and high demographic pressure on the environment (Aristizábal et al, 2015;Jacobs et al, 2018;Migoń and Alcántara-Ayala, 2008;Monsieurs et al, 2018a). The lack of scientific investigation in this area is most likely related to the dearth of data on timing and location of landslides (Kirschbaum and Stanley, 2018).…”