Investigation of the pressing impacts of climate change on drought is vital for sustainable societal and ecosystem functioning. The magnitude of how much the drought will change and the way how droughts would affect society and the environment are inadequately addressed over East Africa. This study aimed at assessing future drought changes using an ensemble of five Global Climate Models (GCMs) in the Coupled Model Intercomparison Project (CMIP5) over East Africa. To this end, drought characteristics were investigated under the Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5 in the near term (the 2020s; 2011–2040), midcentury (2050s; 2041–2070), and end of century (2080s; 2071–2,100). The changes of the Standardized Precipitation Index (SPI) and Standardized Precipitation‐Evapotranspiration Index (SPEI) were first compared, and the SPEI was used for measuring future droughts as it showed stronger changes due to its inclusion of temperature effects. Drought area in East Africa is likely to increase at the end of the 21st century by 16%, 36%, and 54% under RCP 2.6, 4.5, and 8.5, respectively, with the areas affected by extreme drought increasing more rapidly than severe and moderate droughts. Spatially, drought event, duration, frequency and intensity would increase in Sudan, Tanzania, Somalia, and South Sudan, but generally decrease in Kenya, Uganda, and Ethiopian highlands. Results also confirm that drought changes over East Africa follow the “dry gets drier and wet gets wetter” paradigm. The findings provide important guidance for improving identification of causes, minimizing the impacts and enhancing the resilience to droughts in East Africa.

The national economy and food security of many sub-Saharan countries relies on rain-fed agriculture, hence the impact of rainfall variability is highly significant. The intent of this study is to characterize rainfall variability and trend in Awash River Basin for agricultural water management using standard rainfall statistical descriptors. Long-term climate data of 12 stations were analyzed. Onset and cessation dates, length of growing period (LGP) and probability of dry spell occurrences were analysed using INSTAT Plus software. The Mann–Kendall test and the Sen's slope method were used to assess the statistical significance of the trend. The results show high variability of rainfall (38–73%), LGP (30–38 days) and high probability of dry spell occurrence (up to 100%) during the Belg season (the short rainy season from March to May) compared with the Kiremt season (the main rainy season from June to September) in all stations. Belg season showed a non-significant decline trend in most of the stations, whereas the Kiremt season indicated the contrary. The finding also revealed that supplementary irrigation is vital, especially in the Belg season to cover up to 40% of the crop water requirement deficit.

Land degradation is a global negative environmental process that causes the decline in the productivity of land resources’ capacity to perform their functions. Though soil and water conservation (SWC) technologies have been adopted in Geshy subcatchment, their effects on soil quality were limitedly studied. The study was conducted to evaluate the effects SWC measures on soil quality indicators in Geshy subcatchment, Gojeb River Catchment, Ethiopia. A total of 54 soil samples (two treatments–farmlands with and without SWC measures ∗ three slope classes ∗ three terrace positions ∗ three replications) were collected at a depth of 20 cm. Statistical differences in soil quality indicators were analyzed using multivariate analysis of variance (ANOVA) following the general linear model procedure of SPSS Version 20.0 for Windows. Means that exhibited significant differences were compared using Tukey’s honest significance difference at 5% probability level. The studied soils are characterized by low bulk density, slightly acidic with clay and clay loam texture. The results revealed that farmlands with SWC measures had significantly improved soil physical (silt and clay fractions, and volumetric soil water content (VSWC)) and chemical (pH, SOC, TN, C : N ratio, and Av. phosphorus) quality indicators as compared with farmlands without SWC measures. The significantly higher VSWC, clay, SOC, TN, C : N ratio, and Av. P at the bottom slope classes and terrace positions could be attributed to the erosion reduction and deposition effects of SWC measures. Generally, the status of the studied soils is low in SOC contents, TN, C : N ratio, and Av. P (deficient). Thus, integral use of both physical and biological SWC options and agronomic interventions would have paramount importance in improving soil quality for better agricultural production and productivity.

Vegetation dynamics have been visibly influenced by climate variability. The Normalized Difference Vegetation Index (NDVI) has been the most commonly used index in vegetation dynamics. The study was conducted to examine the effects of climatic variability (rainfall) on NDVI for the periods 1982–2015 in the Gojeb River Catchment (GRC), Omo-Gibe Basin, Ethiopia. The spatiotemporal trend in NDVI and rainfall time series was assessed using a Theil–Sen (Sen) slope and Mann–Kendall (MK) statistical significance test at a 95% confidence interval. Moreover, the residual trend analysis (RESTREND) method was used to investigate the effect of rainfall and human induction on vegetation degradation. The Sen’s slope trend analysis and MK significant test indicated that the magnitude of annual NDVI and rainfall showed significant decrement and/or increment in various portions of the GRC. The concurrent decrement and/or increment of annual NDVI and rainfall distributions both spatially and temporarily could be attributed to the significant positive correlation of the monthly (RNDVI-RF = 0.189, P≤0.001) and annual (RNDVI-RF = 0.637, P≤0.001) NDVI with rainfall in almost all portions of the catchment. In the GRC, a strongly negative decrement and strong positive increment of NDVI could be derived by human-induced and rainfall variability, respectively. Accordingly, the significant NDVI decrement in the downstream portion and significant increment in the northern portion of the catchment could be attributed to human-induced vegetation degradation and the variability of rainfall, respectively. The dominance of a decreasing trend in the residuals at the pixel level for the NDVI from 1982, 1984, 2000, 2008 to 2012 indicates vegetation degradation. The strong upward trend in the residuals evident from 1983, 1991, 1998 to 2007 was indicative of vegetation improvements. In the GRC, the residuals may be derived from climatic variations (mainly rainfall) and human activities. The time lag between NDVI and climate factors (rainfall) varied mainly from two to three months. In the study catchment, since vegetation degradations are mainly caused by human induction and rainfall variability, integrated and sustainable landscape management and climate-smart agricultural practices could have paramount importance in reversing the degradation processes.

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