Gillo et al. (2025) Integrated assessment of meteorological, hydrological and agricultural drought in Abaya Chamo sub Basin, Ethiopia

Identification

• Journal: Scientific Reports
• Year: 2025
• Date: 2025-11-06
• Authors: Tamirat Tessema Gillo, Tadesse Tujuba Kenea, Yoseph Arba Orke, Yared Godine Demeke
• DOI: 10.1038/s41598-025-22809-2

Research Groups

• Faculty of Meteorology and Hydrology, Water Technology Institute, Arba Minch University, Arba Minch, Ethiopia

Short Summary

This study comprehensively assessed meteorological, hydrological, and agricultural drought characteristics in Ethiopia's Abaya Chamo sub-basin from 1981-2021 using SPEI, SSI, and SSMI, revealing increasing aridity and severe to extreme drought intensities that varied spatially across catchments.

Objective

• To investigate the characteristics of meteorological, hydrological, and agricultural droughts in the Abaya Chamo sub-basin, Ethiopia, using multiple drought indices (Standardized Precipitation Evapotranspiration Index, Standardized Stream flow Index, and Standardized Soil Moisture Index) from 1981 to 2021.

Study Configuration

• Spatial Scale: Abaya Chamo sub-basin, Ethiopia (between 37°E-38°E longitude and 5°−8° N latitude, elevations from 1090 m to 3439 m above mean sea level). The sub-basin is divided into four regions: northern Bilate catchment, southwestern Lake Catchment, eastern Gidabo catchment, and southern Gelena catchment.
• Temporal Scale: 1981 to 2021 (41 years) for meteorological and agricultural drought; 1990 to 2020 for hydrological drought.

Methodology and Data

• Models used:
  • Standardized Precipitation Evapotranspiration Index (SPEI) for meteorological drought.
  • Standardized Stream flow Index (SSI) for hydrological drought.
  • Standardized Soil Moisture Index (SSMI) for agricultural drought.
  • Hargreaves method for Potential Evapotranspiration (PET) calculation.
  • Log-logistic probability distribution for SPEI normalization.
  • Log-normal distribution for SSI.
  • Empirical model based on Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) for SSMI.
  • Pearson’s correlation coefficient for drought propagation analysis.
  • ArcGIS Pro for map generation and spatial data processing.
  • Double-mass curve and Standard Normal Homogeneity (SNH) for data consistency and homogeneity analysis.
  • Inverse Distance Weighting (IDW) Method for missing data imputation.
• Data sources:
  • Monthly rainfall, maximum temperature, and minimum temperature data from 32 meteorological stations (1981–2021) provided by the Ethiopian Meteorology Institute (EMI).
  • Streamflow data from 10 gauging stations (1990–2020) obtained from the Ministry of Water and Energy (MoWE).
  • Monthly soil moisture data at a spatial resolution of 0.10 degrees (1981–2021) retrieved from the NASA GES DISC website.

Main Results

• All three drought indices (SPEI, SSI, SSMI) effectively captured historical drought episodes, showing only minor variations.
• The proportion of dry months significantly exceeded rainy months between 1981 and 2021, indicating an increase in aridity over the period.
• The sub-basin experienced maximum drought intensities with index values of -2.5 (SPEI), -2.8 (SSI), and -2.4 (SSMI).
• Spatially, the Gelana catchment experienced the most severe drought conditions, while the Bilate catchment faced less severe drought.
• Extreme to severe hydrological droughts were observed, with SSI values ranging from -2.8 to -1.7 across the sub-basin, for instance, -2.7 to -2.2 in the Kulfo River catchment.
• Agricultural drought periods (soil moisture deficit) accounted for 32.0% to 36.5% of the study duration across different catchments, consistently outnumbering wet periods.
• Extreme droughts frequently occurred during the rainy season (March-September), which is critical for crop production, severely impacting water availability for agriculture and livestock.
• A strong positive correlation (e.g., r = 0.72 in Bilate catchment) was found between short-term meteorological drought (SPEI-1) and soil moisture deficits (SPEI-3), demonstrating drought propagation.
• Drought propagation analysis indicated that meteorological drought drives agricultural drought with a lag of 3 to 6 months, while hydrological drought emerges with delays of 6 to 12 months.

Contributions

• Provides a comprehensive, multi-index assessment of meteorological, hydrological, and agricultural drought characteristics at a specific sub-basin level (Abaya Chamo), addressing the limitations of previous studies that often focused on single indices or larger geographical areas.
• Quantifies and maps the spatial variability of drought intensity and frequency across different catchments within the Abaya Chamo sub-basin.
• Identifies and analyzes the propagation of drought types (meteorological to agricultural to hydrological) and their lagged relationships, offering insights into the complex dynamics of drought.
• Offers specific, actionable findings and recommendations for drought planning, management, early warning systems, and adaptive measures to enhance water resource management and food security in the vulnerable Abaya Chamo sub-basin.

Funding

• Not explicitly stated in terms of projects, programs, or reference codes. The authors acknowledge the Ethiopian Meteorological Institute (EMI) and the Ministry of Water and Energy (MoWE) for providing data, and Arba Minch University for providing facilities.

Citation

@article{Gillo2025Integrated,
  author = {Gillo, Tamirat Tessema and Kenea, Tadesse Tujuba and Orke, Yoseph Arba and Demeke, Yared Godine},
  title = {Integrated assessment of meteorological, hydrological and agricultural drought in Abaya Chamo sub Basin, Ethiopia},
  journal = {Scientific Reports},
  year = {2025},
  doi = {10.1038/s41598-025-22809-2},
  url = {https://doi.org/10.1038/s41598-025-22809-2}
}

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