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Trends and zonal variability of extreme rainfall events over East Africa during 1960–2017

Author

Listed:
  • Moses A. Ojara

    (Nanjing University of Information Science and Technology
    Nanjing University of Information Science and Technology
    Uganda National Meteorological Authority)

  • Lou Yunsheng

    (Nanjing University of Information Science and Technology
    Nanjing University of Information Science and Technology)

  • Hassen Babaousmail

    (Nanjing University of Information Science and Technology
    Nanjing University of Information Science and Technology)

  • Peter Wasswa

    (Makerere University College of Geoinformation, Environment and Climate Sciences)

Abstract

East African countries (Uganda, Kenya, Tanzania, Rwanda, and Burundi) are prone to weather extreme events. In this regard, the past occurrence of extreme rainfall events is analyzed for 25 stations following the Expert Team on Climate Change Detection and Indices (ETCCDI) regression method. Detrended fluctuation analysis (DFA) is used to show the future development of extreme rainfall events. Pearson’s correlation analysis is performed to show the relationship of extreme rainfall events between different rainfall zones and their association with El Niño-Southern Oscillation (ENSO) and Indian Ocean dipole Mode Index (DMI). The results revealed that the consecutive wet days (CWD) index experienced a decreasing trend in 72% of the stations analyzed. Moreover, the consecutive dry days (CDD) index also indicated a positive trend in 44% of the stations analyzed. Heavy rainfall days index (R10mm) showed a positive trend at 52% of the stations and was statistically significant at a few stations. In light of the extremely heavy rainfall index (R25mm), 56% of the stations revealed a decreasing trend for the index and statistically significant trend at some stations. Further, a low correlation coefficient of extreme rainfall events between the regions (r2 = − 0.27 to r2 = 0.38) and between rainfall extreme indices with the atmospheric teleconnection indices [Dipole Mode Index (DMI) and Nino 3.4] ranging from r2 = − 0.1 to r2 = 0.35 was exhibited. Most rainfall zones showed a positive correlation between the R95p index and DMI, while 5/8 of the rainfall zones experienced a negative correlation between Nino 3.4 index and the R95p Index. In light of the highly variable trends of extreme rainfall events, we recommend planning adaptation and mitigation measures that consider the occurrence of such high variability. Measures such as rainwater harvesting, storage, and use during needs, planned settlement, and improved drainage systems management supported by accurate climate and weather forecasts are highly advised.

Suggested Citation

  • Moses A. Ojara & Lou Yunsheng & Hassen Babaousmail & Peter Wasswa, 2021. "Trends and zonal variability of extreme rainfall events over East Africa during 1960–2017," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(1), pages 33-61, October.
    • Handle: RePEc:spr:nathaz:v:109:y:2021:i:1:d:10.1007_s11069-021-04824-4
    DOI: 10.1007/s11069-021-04824-4
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    References listed on IDEAS

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    1. Hezron Mogaka & Samuel Gichere & Richard Davis & Rafik Hirji, 2009. "Climate Variability and Water Resources in Kenya : The Economic Cost of Inadequate Management," World Bank Publications - Reports 11736, The World Bank Group.
    2. Moses A. Ojara & Yunsheng Lou & Lawrence Aribo & Silvia Namumbya & Md. Jalal Uddin, 2020. "Dry spells and probability of rainfall occurrence for Lake Kyoga Basin in Uganda, East Africa," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 100(2), pages 493-514, January.
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