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.
Highlights
East African (EA) countries (Uganda, Kenya, Tanzania, Rwanda, and Burundi) are prone to climate and weather extreme events that usually expose their population to risks and vulnerability (Kilavi et al 2018)
Results showed that the total number of rainy days index (Rn=1.0mm) in most parts of EA including rainfall zone 4,6,7 and Western Kenya towards Mount Elgon, experienced more numbers of rainy days ranging from 118 to 180 days in a year (Fig.3a)
In reference to the pattern of consecutive dry days, (CDD) the entire Uganda, Rwanda and Burundi, Western Kenya to northwestern Kenya, Mountain Kenya areas extending to most parts of rainfall zone 2, and the coastal area along rainfall zone 5 experienced the lowest number of dry days (CDD) ranging from 17 to 91 days, while northeastern Kenya in rainfall zone 1(R1), and most of Southwestern, Western and Central parts of Tanzania, covering a large proportion of rainfall zone 5 (R5)
Summary
East African (EA) countries (Uganda, Kenya, Tanzania, Rwanda, and Burundi) are prone to climate and weather extreme events that usually expose their population to risks and vulnerability (Kilavi et al 2018). The rains are highly variable and frequently associated with extremes events such as flash floods (Indeje et al 2000; Nicholson 2017), and droughts (Gamoyo et al 2015) These events continue to increase great stress on many EA countries by disrupting food production and distribution channels in the region (FAO 2017). The impact of some climate extreme events such as frequent flash floods, long dry spells, frequent droughts usually result in damages to socio-economic infrastructure, food insecurity, and loss of lives (Schlenker and Lobell 2010; Adhikari et al 2015; Onyutha 2016; Pereira 2017). For example; Uganda has experienced alternating episodes of floods, droughts, or dry spells in eastern and northeastern which have resulted in frequent loss of human lives, livestock, as well as the destruction of socio-economic infrastructure (Onyutha 2016).
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