Spatiotemporal analysis of drought characteristics across multiple timescales in the upper Blue Nile basin, Ethiopia
2025
Alemu, Melkamu | Zaitchik, Benjamin | Enku, Temesgen | Abeyou, Abeyou | Yimer, Esifanos | Griensven, Ann
In the context of climate change, in-depth analysis of the spatiotemporal characteristics, propagation dynamics, and influencing factors of droughts is critical for early warning and decision-making. However, such analyses are often constrained by a lack of sufficient in-situ hydro-meteorological data. This study addresses this gap by utilizing the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil Moisture Index (SSMI), and Gravity Recovery and Climate Experiment Drought Severity Index (GRACE-DSI) from remote sensing and reanalysis sources. We assessed meteorological, agricultural, and hydrological droughts in the Upper Blue Nile Basin (UBNB) using run theory to analyze key drought characteristics: events, duration, and severity from 1982 to 2023. The Granger causality test evaluated causal relationships between meteorological and agricultural/hydrological droughts, while the maximum Pearson correlation coefficient method identified the propagation times of droughts across various agroecological zones and land cover types. Additionally, hierarchical cluster analysis was conducted to pinpoint homogeneous drought regions. Results indicated that the UBNB experienced frequent droughts, with spatial variations in drought characteristics: drought duration and severity increased with longer timescales, while the number of drought events decreased. Causal relationships were confirmed between meteorological and agricultural/hydrological droughts, with a short propagation time of about 2 months from meteorological to agricultural drought, and approximately 12 months to hydrological drought. These propagation times varied by agroecological zones, being longer in croplands and highlands, and shorter in lowlands and tree-covered areas. Cluster analysis identified three distinct drought clusters in the UBNB, providing insights for targeted adaptation measures in drought-prone regions.
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