Abstract
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.
Highlights
IntroductionDroughts are considered a serious natural hazard, especially in semi-arid regions where devastating and catastrophic damages are recorded [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15], and have been mainly categorized (on the basis of duration, impact and recovery rate) into meteorological (defined by a lack of precipitation over a certain period of time for a certain region), agricultural
In this2 work, the study area selected across East Africa covers an area of about 4.32 milmillion km from 11°43′52.58′′S to 14°52′46.32′′N and 24°7′17.6′′E to 51°25′1.34′′E comprislion km2 from 11◦ 430 52.58” S to 14◦ 520 46.32” N and 24◦ 70 17.6” E to 51◦ 250 1.34” E comprising of Rwanda, Uganda, South Sudan, Tanzania, Ethiopia, Kenya, Somalia, and Burundi ing of Rwanda, Uganda, South Sudan, Tanzania, Ethiopia, Kenya, Somalia, and Burundi (Figure 1)
The Detrended Fluctuation Analysis (DFA) approach measures the direct and indirect changes which are very hard to be explained by an ordinary least square regression model (Figure 7)
Summary
Droughts are considered a serious natural hazard, especially in semi-arid regions where devastating and catastrophic damages are recorded [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15], and have been mainly categorized (on the basis of duration, impact and recovery rate) into meteorological (defined by a lack of precipitation over a certain period of time for a certain region), agricultural. Global estimates on the impacts of drought indicate that a total of 642 drought events were recorded globally between 1900 and 2013 resulting in the death of about 12 million people, directly affecting a population of over 2 billion, with estimated economic damage of about USD 135 billion [20,21]. It is considered necessary to continue investigations into better methods of understanding drought occurrence within the East Africa region as a critical step towards building resilience and adaptability among the population of the region, and other semi-arid regions in other parts of Africa [30,31,32]
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