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Droughts are ranked among the most devastating agricultural disasters that occur naturally in the world. East Africa is the most vulnerable and drought-prone region worldwide. In this study, four drought indices were used as input variables for drought assessment from 1982 to 2015. This work applied the SMDM algorithm to the integrated approach of OLR and Hurst exponent. The Detrended Fluctuation Analysis (DFA) and Ordinary Least Square (OLR) were merged to compute the trend and persistence (Hurst exponent) of the drought indices. Result indicates that the OLR at time scale 1, 6, and 12 shows a similar distribution with positive (negative) trends scattered in the Northwest (Northeast and Southern) parts of the study area which differs with the OLR aggregated at a 3-month time scale. The percentage pixel distribution for OLR-1, OLR-3, OLR-6, and OLR-12 is 18.2 (81.8), 72.5 (27.5), 32.9 (67.1), and 36.9 (63.1) for increasing (decreasing) trends respectively. Additionally, results indicate that DFA-1 is highly persistent with few random pixels scattered around Ethiopia, South Sudan and Tanzania, with percentage pixels as 88.7, 11.3 and 0.1 representing h > 0.5, h = 0.5, and h < 0.5, respectively. DFA-6 shows high (low) pixels representing h > 0.5 (h > 1), respectively. Meanwhile, for DFA-3 and DFA-12, the distribution shows persistence and a random walk, respectively. Drought conditions may eventually persist, reverse or vary drastically in an unpredictable manner depending on the driving forces. Overall, the drought risk map at 1-, 3-, and 6-month aggregates has shown severe degradation in Southern Kenya and Tanzania while noticeable improvements are seen in western Ethiopia and South Sudan. [ABSTRACT FROM AUTHOR]

Hydrological drought, a regular phenomenon that could heavily impact natural systems and human life, is aggravated by a water storage deficit. While Gravity Recovery and Climate Experiment (GRACE) satellite databased drought monitoring has been widely studied in East Africa (EA), drought recovery time and anthropogenic factors are still missing, which are prerequisite for drought management. Here, a water storage deficit index (WSDI) and modified WSDI are utilized for analyzing a holistic representation of drought. The results show that the drought events in recent times are well-identified and estimated using this approach over five lake basins in EA from 2002 to 2021. Although, the basin scale drought events are evaluated using the Pearson correlation coefficient (r) from 2002 to 2021. The results showed a significant correlation between WSDI, MWSDI, and the standardized precipitation-evapotranspiration index (SPEI) in all lake basins except in the Tana basin. We show that the presence of anthropogenic forcing has increased the highest peak deficits of -2.57, -3.25, -19.05, -87.2, and -99 km 3 over the Tana, Abaya-Chamo, Turkana, Victoria, and Tanganyika basins, respectively. The longest deficit period of 36 months and the highest severity value of -1140 were observed in the Turkana and Victoria basins. The average drought recovery time ranges from 2.4 to 11.2 months and from 1.4 to 12.6 months as obtained by WSDI and MWSDI, respectively. Our findings highlight the importance of the calculated WSD approach to evaluating the hydrological drought characterization and estimate the drought condition at the basin scale., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)