Spatiotemporal Patterns of Drought Migration Across the Contiguous United States - Amitesh Sabut; Ashok Mishra; Dara Entekhabi (Water Resources Research, 2025)
Abstract Drought phenomena exhibit three‐dimensional spatiotemporal propagation patterns, often impacting vast regions and lasting for extended periods. Quantifying these spatial and temporal dynamics is essential for understanding their progression and underlying causes. However, there is a lack of studies investigating the spatiotemporal progression and migration of major drought events. In this study, we employed the Spatio‐temporal Density‐Based Spatial Clustering of Applications with Noise (ST‐DBSCAN) clustering method to identify significant drought events across the Contiguous United States (CONUS) from 1901 to 2022. This algorithm effectively identifies clusters of arbitrary shapes within a specified three‐dimensional space. By tracking the centroids of these drought clusters, we analyzed the progressive development and migration pathways of these events. Our findings indicate that the Great Plains region acts as a key migration corridor, experiencing a higher frequency of drought events compared to other areas in the CONUS. We observed that droughts can travel hundreds of kilometers, gradually intensifying before eventually dissipating. Moreover, a significant linear relationship exists between migration distances and the duration of droughts. Moreover, over 77% of the analyzed drought events exhibited notable spatial shifts, suggesting that the majority of these events migrated across different regions instead of staying confined to a single area. Furthermore, we identified two primary migration patterns for these drought clusters: eastward and westward movements. These findings offer crucial spatiotemporal frameworks for studying the migration process and provide valuable insights for predicting drought occurrences.