Chere et al. (2025) Earth observation-based drought studies in Ethiopia: a review on current state and future research directions

Identification

• Journal: Modeling Earth Systems and Environment
• Year: 2025
• Date: 2025-10-06
• Authors: Zerihun Chere, Aberaw Kefyalew, Moges Gtachew
• DOI: 10.1007/s40808-025-02629-z

Research Groups

• Dire Dawa University, Dire Dawa, Ethiopia
• Woldia University, Weldiya, Ethiopia
• Oda Bultum University, Chiro, Ethiopia

Short Summary

This review synthesizes Earth observation (EO)-based drought studies in Ethiopia from 2011 to 2022, revealing an increasing trend in publications, a prevalence of agricultural drought studies, and the widespread use of CHIRPS rainfall, MODIS vegetation products, and SPI/VCI indices, with most studies including validation.

Objective

• To systematically review and synthesize Earth observation (EO)-based drought studies in Ethiopia from 2011 to 2022, identifying current trends, methodologies, challenges, and future research directions to enhance drought monitoring and resilience.

Study Configuration

• Spatial Scale: Review covers studies across Ethiopia, from zonal to national levels. Spatial resolutions of reviewed studies range from 30 meters to 27 kilometers.
• Temporal Scale: Review period: 2011–2022. Reviewed studies often used data spanning up to 30 years. Temporal resolutions of reviewed studies include seasonal (Kiremt), multiple temporal scales, and decadal.

Methodology and Data

• Models used: Standardized Precipitation Index (SPI), Vegetation Condition Index (VCI), Vegetation Health Index (VHI), Normalized Difference Vegetation Index (NDVI) anomaly, Standardized Precipitation Evapotranspiration Index (SPEI), Temperature Condition Index (TCI), Combined Drought Indicator for Ethiopia (CDI-E), Actual Evapotranspiration (AET) anomaly, Soil Moisture Deficit Index (SMDI), precipitation anomaly index. Retrieval methods primarily involve static arithmetic formulations and linear weighted combinations; limited use of traditional machine learning (CART, Cubist regression trees).
• Data sources: Satellite precipitation products (e.g., CHIRPS, TRMM, TAMSAT), satellite vegetation products (e.g., MODIS, SPOT-VGT, AVHRR, Landsat), thermal sensors, soil moisture data, evapotranspiration data, water indices. Validation data sources include in-situ rainfall data, crop yield data, and EM-DAT.

Main Results

• EO-based drought publications in Ethiopia have significantly increased, with 74% of reviewed articles published in the last five years of the study period (2018-2022).
• Agricultural drought studies are the most prevalent (44.1%), followed by meteorological drought (29.4%), and combined agricultural/meteorological drought (26.5%).
• CHIRPS rainfall products (31.1% of sensors) and MODIS vegetation products (23% of sensors) are the most frequently reported satellite sensors for drought monitoring. Multi-sensors are the most popular category (50.8%).
• Rainfall products are the most common input data for drought indices (47.5%), followed by vegetation-related indices (37%).
• The Standardized Precipitation Index (SPI) (25.8%) and Vegetation Condition Index (VCI) (24.2%) are the most widely applied drought indices in Ethiopia.
• Most studies (44%) utilize a seasonal (Kiremt) time scale for drought monitoring, with only 9% using high temporal resolution (decadal) data. Long-term studies (over 30 years) are rare.
• 67.6% of publications validated their drought products, primarily using in-situ rainfall data (32.4%) and crop yield data (23.5%).
• Current drought index retrieval methods overwhelmingly rely on static, arithmetic formulations and fixed empirical equations, with limited adoption of advanced machine learning or deep learning frameworks, hyperparameter tuning, or uncertainty quantification.

Contributions

• Presents the first systematic review specifically focused on Earth observation (EO)-based drought research within the Ethiopian context.
• Synthesizes the evolution of drought monitoring and management in Ethiopia, from conventional methods to advanced technologies, evaluating their strengths and limitations.
• Identifies emerging trends, significant research gaps (e.g., lack of advanced machine/deep learning applications, underutilization of microwave remote sensing, limited multi-sensor integration), and proposes integrated strategies for future research.
• Delivers actionable insights for drought monitoring stakeholders, including researchers and decision-makers, to advance the design of sustainable resilience strategies with enhanced efficacy.

Funding

No funding was obtained for this investigation.

Citation

@article{Chere2025Earth,
  author = {Chere, Zerihun and Kefyalew, Aberaw and Gtachew, Moges},
  title = {Earth observation-based drought studies in Ethiopia: a review on current state and future research directions},
  journal = {Modeling Earth Systems and Environment},
  year = {2025},
  doi = {10.1007/s40808-025-02629-z},
  url = {https://doi.org/10.1007/s40808-025-02629-z}
}