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Comparative quantitative modeling of landslide susceptibility in Feresmay, Central Tigray

Year: 2026
Type: article
Abstract: Landslides frequently occur in the hilly and mountainous regions of the Ethiopian highlands, particularly during the summer season, resulting in loss of life, damage to agricultural lands, and destruction of residential areas. This study focuses on the Feresmay area in the central part of Tigray, located between Bizet and Adwa and accessible via the main asphalt road from Mekelle to Adwa. The main objective was to assess landslide occurrences, identify causative factors and failure mechanisms, produce a landslide susceptibility map (LSM), and recommend remedial measures. The study utilized previous work/secondary data, conducted field data collection, and interpreted the results. A total of 202 landslide events were inventoried in the study area, covering approximately 10.75 km 2 . LSMs were generated using the frequency ratio (FR) and logistic regression (LR) models. The FR model calculates the landslide susceptibility index by summing the FR values of each causative factor, while the LR model is based on predictor variables associated with each factor. Validation of the susceptibility maps was performed using inventoried landslide data and the Area Under the Curve (AUC) method. The reliability of the susceptibility maps was validated using an independent landslide inventory (30% of the data) and the area under the curve (AUC) method. Validation results show good agreement between predicted susceptibility classes and observed landslides, with the logistic regression model achieving a higher prediction accuracy (AUC = 0.838) compared to the frequency ratio model (AUC = 0.800). Quantitative results show that the FR model identifies approximately 10.64% of the area as highly susceptible landslide zones, while the LR model designates around 13% of the total study area as highly susceptible zones. Catastrophic impacts observed include destruction of houses and agricultural lands, with displacement of local residents. The main causative factors identified in this study are lithology, land use/land cover, and distance to the stream. The LR model demonstrates better prediction accuracy than the FR method. Detailed surveys utilizing geophysical methods and geotechnical approaches are recommended for investigating high and very high susceptibility zones. These surveys will provide a better understanding of the geological materials in the area and aid in developing effective mitigation strategies.
DOI: 10.1007/s42452-026-09632-8
Language: English
Open Access status: diamond
OpenAlex ID: W7222891013
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