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<p>Ethiopia’s complex topography, intense seasonal rainfall, and active geological settings render it highly susceptible to landslides, particularly in highland regions above 2000&#xa0;m. This study presents a comprehensive national-scale landslide susceptibility assessment integrating multiple geospatial datasets using the Analytical Hierarchy Process (AHP) and Weighted Linear Combination (WLC) methodologies. Nine conditioning factors were systematically evaluated: slope gradient, precipitation, lithology, soil type, road proximity, land use/land cover, aspect, elevation, and historical landslide records. The susceptibility model classified Ethiopia’s terrain into five zones: very high (0.1%), high (8%), moderate (37%), low (44%), and very low (11%), indicating that approximately 45% of the national territory exhibits moderate to very high landslide probability. High-susceptibility zones predominantly occur in the Amhara, Oromia, Tigray, and Southern Ethiopian regions, and correlate with steep slopes (&gt; 25°), intense rainfall (&gt; 1,000&#xa0;mm/yr), volcanoclastic lithology, and anthropogenic pressures, including deforestation and infrastructure development. Model validation employed 405 historical landslide inventory points, achieving 87% accuracy in high-susceptibility zone predictions, while Receiver Operating Characteristic (ROC) analysis yielded an Area Under Curve (AUC) of 0.87. Complementary Interferometric Synthetic Aperture Radar (InSAR) displacement analysis in selected high-risk areas (Dessie, Arba Minch-Gofa, Debre Berhan, and Jimma) corroborated susceptibility predictions through detected surface deformation patterns. These findings provide critical baseline information for Ethiopia’s Multi-hazard Impact-based Early Warning and Early Action System (2023–2030), supporting evidence-based decision-making for land use planning, infrastructure development, and climate adaptation strategies in vulnerable regions. By enabling risk-informed land-use planning, prioritization of slope-stability interventions, and targeting of early warning in high-exposure corridors, this framework directly supports the Sustainable Development Goals—especially SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), and SDG 9 (Resilient Infrastructure)—with co-benefits for SDG 1 (No Poverty), SDG 2 (Zero Hunger), SDG 3 (Good Health and Well-being), and SDG 15 (Life on Land).</p>

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National scale landslide susceptibility mapping in Ethiopia using multi criteria decision analysis with InSAR validation for disaster risk reduction and early warning

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月18日

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  • Natnael Agegnehu Ayele,
  • Esubalew Mulugeta Engda,
  • Ziyen Achamyeleh Mekonne,
  • Taye Teshome,
  • Wendowssen Mindahun,
  • Yimer Assefa,
  • Esubalew Adem Yibrie,
  • Muralitharan Jothimani,
  • Robert Tenzer

摘要

Ethiopia’s complex topography, intense seasonal rainfall, and active geological settings render it highly susceptible to landslides, particularly in highland regions above 2000 m. This study presents a comprehensive national-scale landslide susceptibility assessment integrating multiple geospatial datasets using the Analytical Hierarchy Process (AHP) and Weighted Linear Combination (WLC) methodologies. Nine conditioning factors were systematically evaluated: slope gradient, precipitation, lithology, soil type, road proximity, land use/land cover, aspect, elevation, and historical landslide records. The susceptibility model classified Ethiopia’s terrain into five zones: very high (0.1%), high (8%), moderate (37%), low (44%), and very low (11%), indicating that approximately 45% of the national territory exhibits moderate to very high landslide probability. High-susceptibility zones predominantly occur in the Amhara, Oromia, Tigray, and Southern Ethiopian regions, and correlate with steep slopes (> 25°), intense rainfall (> 1,000 mm/yr), volcanoclastic lithology, and anthropogenic pressures, including deforestation and infrastructure development. Model validation employed 405 historical landslide inventory points, achieving 87% accuracy in high-susceptibility zone predictions, while Receiver Operating Characteristic (ROC) analysis yielded an Area Under Curve (AUC) of 0.87. Complementary Interferometric Synthetic Aperture Radar (InSAR) displacement analysis in selected high-risk areas (Dessie, Arba Minch-Gofa, Debre Berhan, and Jimma) corroborated susceptibility predictions through detected surface deformation patterns. These findings provide critical baseline information for Ethiopia’s Multi-hazard Impact-based Early Warning and Early Action System (2023–2030), supporting evidence-based decision-making for land use planning, infrastructure development, and climate adaptation strategies in vulnerable regions. By enabling risk-informed land-use planning, prioritization of slope-stability interventions, and targeting of early warning in high-exposure corridors, this framework directly supports the Sustainable Development Goals—especially SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), and SDG 9 (Resilient Infrastructure)—with co-benefits for SDG 1 (No Poverty), SDG 2 (Zero Hunger), SDG 3 (Good Health and Well-being), and SDG 15 (Life on Land).