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Multi‐Scale Analysis of July (Hamle) Rainfall Failure as an Indicator of Drought and El Niño Events in Ethiopia: A Case Study of Borkena Watershed, Awash Basin.

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Bibliographic Details
Title: Multi‐Scale Analysis of July (Hamle) Rainfall Failure as an Indicator of Drought and El Niño Events in Ethiopia: A Case Study of Borkena Watershed, Awash Basin.
Authors: Lakew, Haileyesus Belay1,2 (AUTHOR) h.lakew@cgiar.org, Taye, Meron Teferi1 (AUTHOR), Seid, Abdulkarim Hussien1 (AUTHOR)
Source: International Journal of Climatology. Mar2026, Vol. 46 Issue 3, p1-14. 14p.
Subject Terms: *Droughts, *Drought forecasting, *Water management, *Watersheds, El Niño, Rainfall reliability, Ethiopians
Geographic Terms: Ethiopia
Abstract: Drought has severe consequences for the livelihoods and economies of countries reliant on rainfed agriculture, such as Ethiopia. The Awash Basin, which experiences frequent droughts and water scarcity, requires effective water resource management. Identifying reliable drought indicators is crucial for early warning and mitigation. This study aims to determine the most relevant rainfall‐based indicator of historical meteorological drought in relation to El Niño events across multiple spatial and temporal scales. Using historical precipitation data from the CHIRPS dataset (1981–2021), the study analyses rainfall patterns at three spatial scales: the Awash Basin (110,000 km2), the Borkena sub‐basin (3250 km2), and local livelihood zones (36–927 km2). Monthly and dekadal (10‐day) temporal scales are considered, with rainfall classified into three dekads per month. Signal Detection Theory (SDT) metrics of True Positive Rate (TPR), False Positive Rate (FPR) and Competence (C) are used to evaluate the ability of total rainfall failure to detect historical droughts and El Niño years. Results indicate that July's total rainfall failure consistently aligns with historical droughts and El Niño events, achieving high detection performance (TPR > 70%, FPR < 30%, C > 40%) across all spatial scales. In the Borkena watershed, detection improves when focusing on the second and third dekads of July and the first dekad of August, corresponding to the Ethiopian month of Hamle, with maximum performance (TPR = 90%, FPR = 10%, C = 80%). These findings demonstrate that July rainfall failure, especially during Hamle, can serve as an in‐season early‐warning signal for meteorological drought, supporting timely response and water management. [ABSTRACT FROM AUTHOR]
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Abstract:Drought has severe consequences for the livelihoods and economies of countries reliant on rainfed agriculture, such as Ethiopia. The Awash Basin, which experiences frequent droughts and water scarcity, requires effective water resource management. Identifying reliable drought indicators is crucial for early warning and mitigation. This study aims to determine the most relevant rainfall‐based indicator of historical meteorological drought in relation to El Niño events across multiple spatial and temporal scales. Using historical precipitation data from the CHIRPS dataset (1981–2021), the study analyses rainfall patterns at three spatial scales: the Awash Basin (110,000 km2), the Borkena sub‐basin (3250 km2), and local livelihood zones (36–927 km2). Monthly and dekadal (10‐day) temporal scales are considered, with rainfall classified into three dekads per month. Signal Detection Theory (SDT) metrics of True Positive Rate (TPR), False Positive Rate (FPR) and Competence (C) are used to evaluate the ability of total rainfall failure to detect historical droughts and El Niño years. Results indicate that July's total rainfall failure consistently aligns with historical droughts and El Niño events, achieving high detection performance (TPR > 70%, FPR < 30%, C > 40%) across all spatial scales. In the Borkena watershed, detection improves when focusing on the second and third dekads of July and the first dekad of August, corresponding to the Ethiopian month of Hamle, with maximum performance (TPR = 90%, FPR = 10%, C = 80%). These findings demonstrate that July rainfall failure, especially during Hamle, can serve as an in‐season early‐warning signal for meteorological drought, supporting timely response and water management. [ABSTRACT FROM AUTHOR]
ISSN:08998418
DOI:10.1002/joc.70227