Spatial assessment employing fusion logistic regression and frequency ratio models to monitor landslide susceptibility in the upper Blue Nile basin of Ethiopia: Muger watershed

Abstract

Abstract At the global level, landslides are a dreadful hazard that restricts socio-economic and ecological balances. Recent human activities in hilly areas, coupled with geological predispositions, have potentially exacerbated landslide frequency and magnitude. However, the impacts of these factors on landslide occurrences in the upper Blue Nile basin of Ethiopia remain largely unexplored. This study aims to identify landslide triggers, quantify landslide-susceptible zones, and validate the landslide models. Topographic parameters, geology, hydrology, and land use-land cover inventories were utilized to generate a landslide susceptibility map. The factors were analyzed using a combination of logistic regression (LR) and frequency ratio (FR) models. The area under the curve (AUC) under the receiver operating characteristic (ROC) was used to compare the performance of the models. The result indicates that about 185 sq. km (40.2%) of the total falls under high to very-high susceptible landslide zones, and 92 sq. km (20%) falls under moderate susceptibility. Yet, 183.1 sq. km (40.2%) of the total is classified in the low-to-no landslide hazard zones. The LR and FR model validation demonstrated an average predictive performance of 75 and 81.45%, indicating good precision. The landslide evaluation can help policymakers identify LSH zones for early warning systems and mitigation purposes.

Keywords

• Frequency ratio model
• Landslide incidence
• Logistic regression model
• ROC