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Spatiotemporal analysis of drought characteristics across multiple timescales in the upper Blue Nile basin, Ethiopia

Alemu, Melkamu Meseret, Zaitchik, Benjamin F., Enku, Temesgen, Worqlul, Abeyou W., Yimer, Esifanos Addisu, and van Griensven, Ann, 2025. Spatiotemporal analysis of drought characteristics across multiple timescales in the upper Blue Nile basin, Ethiopia. Theoretical and Applied Climatology, 156(8):435, doi:10.1007/s00704-025-05667-w.

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@ARTICLE{2025ThApC.156..435A,
       author = {{Alemu}, Melkamu Meseret and {Zaitchik}, Benjamin F. and {Enku}, Temesgen and {Worqlul}, Abeyou W. and {Yimer}, Esifanos Addisu and {van Griensven}, Ann},
        title = "{Spatiotemporal analysis of drought characteristics across multiple timescales in the upper Blue Nile basin, Ethiopia}",
      journal = {Theoretical and Applied Climatology},
         year = 2025,
        month = jul,
       volume = {156},
       number = {8},
          eid = {435},
        pages = {435},
     abstract = "{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.}",
          doi = {10.1007/s00704-025-05667-w},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2025ThApC.156..435A},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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