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Hydrological drought evaluation using GRACE satellite-based drought index over the lake basins, East Africa
Ayalkibet Mekonnen Seka1, Jiahua Zhang2, Da Zhang3
1Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Beijing 100049, China; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Arba Minch Water Technology Institute, Water Resources Research Center (AWTi), Arba Minch University, Ethiopia.
Abstract:
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 km3 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.
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