Analysis of Changes in Rainfall Concentration over East Africa

Author:

Babaousmail Hassen12,Ayugi Brian Odhiambo3ORCID,Onyutha Charles4ORCID,Kebacho Laban Lameck5ORCID,Ojara Moses6,Ongoma Victor7ORCID

Affiliation:

1. School of Atmospheric Science and Remote Sensing, Wuxi University, Wuxi 214105, China

2. Wuxi Institute of Technology, Nanjing University of Information Science & Technology, Wuxi 214105, China

3. Department of Civil Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea

4. Department of Civil and Environmental Engineering, Kyambogo University, Kampala P.O. Box 1, Uganda

5. Physics Department, College of Natural and Applied Sciences, University of Dar es Salaam, Dar es Salaam 35063, Tanzania

6. Uganda National Meteorological Authority, Clement Hill Road, Kampala P.O. Box 7025, Uganda

7. International Water Research Institute, Mohammed VI Polytechnic University, Lot 660, Hay Moulay Rachid, Ben Guerir 43150, Morocco

Abstract

Understanding the spatial and temporal distribution of precipitation is important in agriculture, water management resources, and flood disaster management. The present study analyzed the changes in rainfall concentration over East Africa (EA). Three matrices—the precipitation concentration index (PCI), the precipitation concentration degree (PCD), and the precipitation concentration period (PCP)—were used to examine the changes in rainfall during 1981–2021. The changes in spatial variance annually and during two seasons, namely, “long rains” (March to May [MAM]) and “short rain” (October to December [OND]), were estimated using an empirical orthogonal function (EOF). The study employed the robust statistical metrics of the Theil–Sen estimator to detect the magnitude of change and modified Mann–Kendall (MMK) to examine possible changes in rainfall concentration. The localized variation of the power series within the series for PCI, PCD, and PCP variability was performed using the continuous wavelet transform. The findings showed that the concentration of rainfall patterns of EA occurred in four months of the total months in a year over most parts, with the western sides experiencing uniform rainfall events throughout the year. The EOF analysis revealed a homogeneous negative pattern during the MAM season over the whole region for PCD, PCI, and PCP for the first mode, which signified reduced rainfall events. Moreover, the MMK analysis showed evidence of declining trends in the PCD annually and during the MAM season, while the opposite tendency was noted for the OND season where an upward trend in the PCD was observed. Interestingly, areas adjacent to Lake Victoria in Uganda and Lake Tanganyika in Tanzania showed increasing trends in the PCD for annual and seasonal time scales. The analysis to characterize the rainfall cycle and possible return period, considering the indices of PCD, PCI, and PCP, showed higher variability during the year 2000, while much variability was presented in the PCP for the annual period. During the MAM and OND seasons, a 1-year band as a dominant period of variability was observed in all the indices. Overall, the findings of the present study are crucial in detecting the observed changes in rainfall concentration for avoiding the loss of life and property, as well as for coping with potential changes in water resources.

Funder

Ministry of Science and ICT through the National Research Foundation of Korea

Publisher

MDPI AG

Subject

Atmospheric Science,Environmental Science (miscellaneous)

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