Droughts are influenced by a combination of climatic, hydrological, and anthropogenic factors, including shifts in precipitation patterns, soil moisture levels, and land management practices. A comprehensive understanding of these drivers is critical for improving drought prediction, assessing impacts, and informing effective mitigation and adaptation strategies.

In this collection, we highlight research that examines the underlying causes and consequences of drought, with an emphasis on advancing predictive models and enhancing drought resilience. We include studies that utilize a range of methodologies, including observational data analysis, hydrological simulation, climate modeling, and machine learning techniques, to refine our understanding of drought dynamics and inform policy and decision-making.