Abstract Climate change intensifies droughts in Sub-Sahara, particularly South Ethiopia Region attributed to geographic location, poverty and rain-fed agriculture. Recurrent droughts drive crop failures, livestock losses, and malnutrition, yet research gaps persist in mapping vulnerability hotspots using integrated exposure, sensitivity, and adaptive capacity indicators. This study addresses these by quantifying drought vulnerability via the IPCC framework, fusing 38 years (1981–2018) of meteorological data from 36 stations with biophysical and socioeconomic variables. Sixteen indicators were normalized (min-max scaling), weighted (data variability method), and aggregated into composite indices using weighted linear summation in ArcGIS. Results pronounced drought vulnerability, with very high vulnerability in southern Burji and south-central South Omo and high vulnerability across northern Burji, Konso, and southern South Omo. In contrast, very low vulnerability is observed over Gamo highlands, parts of Ari, central Wolaita, and northern Gedeo. Spatial patterns are explained by high exposure in southern lowlands; associated with high counts of days of maximum temperature above 90th percentile, low aridity, and zero-precipitation days; combined with sensitivity patterns that are stronger in densely populated areas (Gedeo and Wolaita) and adaptive capacity that tends to favor northern highlands. Validation against national disaster profile priorities shows high consistency for Nyangatom and Hamer and moderate consistency for Alle, Arba Minch, and Humbo, supporting reliability of results. Based on these findings, it is recommended prioritizing interventions such as forest expansion and infrastructure development in Burji and Konso, alongside strengthened water conservation in high-exposure areas of South Omo and Konso to address hot and dry conditions.
Building similarity graph...
Analyzing shared references across papers
Loading...
Tefera Ashine Teyso
Ebrahim Esa Hassen
Mitiku Adisu Worku
Ethiopian Civil Service University
Building similarity graph...
Analyzing shared references across papers
Loading...
Teyso et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69fd7e5cbfa21ec5bbf068da — DOI: https://doi.org/10.1007/s44367-026-00041-7