Rainfall-induced landslides of different types and sizes frequently affect the hilly and mountainous terrains of the highlands of Ethiopia. The principal objective of the proposed research study was intended to prepare a landslide hazard zonation map of the area, particularly for hazardous zones. In the present study, the Slope Susceptibility Evaluation Parameter rating scheme has been implemented as a relevant approach to map the landslide hazard of the Debresina area, which has experienced slope failure problems for a long period of time. The geology of the area includes quaternary sediments, ignimbrite, rhyolite, different kinds of basalts, and tuff deposits, which are highly weathered and changed into unconsolidated sediments at some localities. Locally observed geological structures such as joints, dykes, and other discontinuities have a considerable role in the initiation of landslide hazards. As a general methodology, a facet map was prepared from a topographic map (1:50,000) and rating values were assigned to each causative parameter (both intrinsic and external) based on its severity in triggering landslide hazard. The study area was classified into three hazard classes, of which 25 % of the slopes fall into a moderate hazard zone, while 58 % and 17 %were found to be high and very high hazard zones, respectively. Validation of the landslide hazard zonation map with past landslide activities suggests the rationality of the considered governing parameters, the adopted technique, tools, and procedures in developing the study area's landslide hazard map. Further, in order to validate the landslide hazard map prepared during the present study, active landslide activities and potential instability areas, delineated through inventory mapping, were overlaid on it, which yielded promising results.
CITATION STYLE
Tadele, T. (2022). Landslide Hazard Assessment and Zonation by using Slope Susceptibility Evaluation Parameter (SSEP) Rating Scheme- a Case from Debre Sina, Northern Ethiopia. East African Journal of Biophysical and Computational Sciences, 3(1), 23–42. https://doi.org/10.4314/eajbcs.v3i1.4s
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