Abstract
Landslides susceptibility assessment has to be conducted to identify prone areas and guide risk management. Landslides in Rwanda are very deadly disasters. The current research aimed to conduct landslide susceptibility assessment by applying Spatial Multi-Criteria Evaluation Model with eight layers of causal factors including: slope, distance to roads, lithology, precipitation, soil texture, soil depth, altitude and land cover. In total, 980 past landslide locations were mapped. The relationship between landslide factors and inventory map was calculated using the Spatial Multi-Criteria Evaluation. The results revealed that susceptibility is spatially distributed countrywide with 42.3% of the region classified from moderate to very high susceptibility, and this is inhabited by 49.3% of the total population. In addition, Provinces with high to very high susceptibility are West, North and South (40.4%, 22.8% and 21.5%, respectively). Subsequently, the Eastern Province becomes the peak under low susceptibility category (87.8%) with no very high susceptibility (0%). Based on these findings, the employed model produced accurate and reliable outcome in terms of susceptibility, since 49.5% of past landslides fell within the very high susceptibility category, which confirms the model’s performance. The outcomes of this study will be useful for future initiatives related to landslide risk reduction and management.
Highlights
Landslides are confirmed severe forms of natural disasters [1] and most of them are caused by specific geological, geomorphological and climatological conditions as well as anthropogenic activities [2]
The hazard assessment and mapping can utilize existing and consistent datasets [29,59,65]. This methodology has been ascertained to be suitable for some circumstances, especially: (a) when landslide susceptibility assessment is scratching from the ground, as starting stage; and (b) when acquiring enough and sufficient datasets for a national scale is challenged by some limitations such as lack of numerical datasets, absence of a complete landslide inventory covering the entire study area, inaccessibility to some prone areas and time constraints
To make the Spatial Multi-Criteria Evaluation (SMCE) model more effective in modeling landslide susceptibility, researchers need to combine it with landslide inventory data from the study area [26,64]
Summary
Landslides are confirmed severe forms of natural disasters [1] and most of them are caused by specific geological, geomorphological and climatological conditions as well as anthropogenic activities [2]. It is necessary that strong and adequate measures are provided for preventing landslides and mass movements which will contribute to reducing associated impacts [5]. In many cases, this is not feasible due to various reasons, innovative and realistic approaches have to be adopted for enhancing landslides’ risks management, and their susceptibility must be well mapped to enable rational decisions in line with landslide risk management [6,7]. Existing figures have confirmed their rise in damages and losses.
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