Enhanced Drought Prediction in Ethiopia: A Deep Learning Approach

Drought remains a multifaceted and devastating environmental hazard in the arid and semi-arid lowlands of Ethiopia, including in Afar and Somali regions, which experience extreme climatic vulnerability. This study investigates drought dynamics across six representative districts (woredas) by integrating remote sensing and climate-based metrics. This research provides a methodological framework for developing advanced, deep learning-based early warning systems to mitigate the socio-economic impacts of drought in highly vulnerable regions.