Evaluation of satellite based rainfall estimates and drought monitoring linked to climate indices in Genale Dawa Basin, Ethiopia

Droughts severely impact agriculture, food security, and water resources, particularly in data scarce regions like the Genale Dawa River Basin (GDRB). This study evaluates the performance of five satellite rainfall products including CHIRPSv2.0, RFE2.0, TAMSATv3.1, PERSIANN-CDR, and ARC2 over 2001-2020 using metrics such as Mean Bias, Absolute Error (MAE), Root Mean Square Error (RMSE), Correlation Coefficient (CC), Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI). Furthermore, the studies examined the relationship between climate indices including the Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), El Niño Southern Oscillation (ENSO), and Atlantic Multidecadal Oscillation (AMO) and drought variability. CHIRPSv2.0 demonstrated the highest accuracy, especially at Ginir (CC = 0.98) and Chewbet (CC = 0.75), and the lowest errors at Teferekella (MAE = 45, RMSE = 65). Based on a multi-criterion ranking approach, CHIRPSv2.0 was identified as the most reliable satellite-based product for daily rainfall estimation across the entire basin, exhibiting strong performance metrics (Lp = 0.433, CC = 0.84, POD = 0.85, CSI = 0.46). CHIRPSv2.0 was used to analyze drought spatiotemporal patterns using SPI-3 and SPI-6. Drought severity, frequency, and duration were highest in the west-central and northern GDRB, with major events occurring in 1988, 1991-1993, 2000, 2004, 2011, and 2012. Climate index analysis showed that AMO and NAO positive phases were associated with wetter conditions, while negative PDO and ENSO phases corresponded with drier periods, especially in central and eastern areas. These findings highlight CHIRPSv2.0's reliability for drought monitoring and its value for early warning and mitigation planning in the GDRB.