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Drought poses significant threats to humans and ecosystems, underscoring the need for robust and efficient monitoring systems for informed decision making and adaptive management. This study assessed the effectiveness of five indices in detecting historical droughts and low-flow periods in the upper and lower sub-basins of the Great Ruaha River Basin, Tanzania using hydrometeorological data (1981–2022). Historical droughts were obtained from government reports and scientific literature. The indices included the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Precipitation Actual Evapotranspiration Index (SPAEI), Standardized Streamflow Index (SSI) and Water Scarcity Index (WSI). The standardized indices were calculated using basin monthly precipitation, evapotranspiration and discharge data at 3-, 6-, and 12-month timescales while the WSI was used to define low-flows based on a threshold of 0.001 m 3 /s, computed from the 10th percentile of daily discharge data. Drought characteristics were investigated using the run theory approach. The SPI captured 70–90% of historical droughts, SPEI identified 80–90%, SPAEI detected 50–60%, while SSI, and WSI each identified 80%. The SPI, SPEI and SSI classified majority of these events as severe while SPAEI identified them as moderate. The WSI was the most effective in detecting low flows, whereas all the standardized indices performed poorly. Between 1981 and 1989, discharge never fell below 0.001 m 3 /s. However, from 1990, lower discharges occurred almost every year, indicating a major shift in the hydrological system. Based on our research findings, we recommend using the SPI, SPEI, SSI and WSI for drought monitoring and more specific, the WSI for low flow analysis. Therefore, by using appropriate drought indices, water managers can achieve sustainable management of droughts and water resources in the basin.
Mukama et al. (Mon,) studied this question.