The study aims to analyze climate variability and farmers’ perception in Southern Ethiopia. Gridded annual temperature and precipitation data were obtained from the National Meteorological Agency (NMA) of Ethiopia for the period between 1983 and 2014. Using a multistage sampling technique, 403 farm households were surveyed to substantiate farmers’ perceptions about climate variability and change. The study applied a nonparametric Sen’s slope estimator and Mann–Kendall’s trend tests to detect the magnitude and statistical significance of climate variability and binary logit regression model to find factors influencing farm households’ perceptions about climate variability over three agroecological zones (AEZs). The trend analysis reveals that positive trends were observed in the annual maximum temperature, 0.02°C/year (p<0.01) in the lowland and 0.04°C/year (p<0.01) in the highland AEZs. The positive trend in annual minimum temperature was consistent in all AEZs and significant (p<0.01). An upward trend in the annual total rainfall (10 mm/year) (p<0.05) was recorded in the midland AEZ. Over 60% of farmers have perceived increasing temperature and decreasing rainfall in all AEZs. However, farmers’ perception about rainfall in the midland AEZ contradicts with meteorological analysis. Results from the binary logit model inform that farmers’ climate change perceptions are significantly influenced by their access to climate and market information, agroecology, education, agricultural input, and village market distance. Based on these results, it is recommended to enhance farm households’ capacity by providing timely weather and climate information along with institutional actions such as agricultural extension services.

The study aims to assess trends in extremes of surface temperature and precipitation through the application of the World Meteorological Organization’s (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) on datasets representing three agroecological zones in Southern Ethiopia. The indices are applied to daily temperature and precipitation data. Nonparametric Sen’s slope estimator and Mann–Kendall’s trend tests are used to detect the magnitude and statistical significance of changes in extreme climate, respectively. All agroecological zones (AEZs) have experienced both positive and negative trends of change in temperature extremes. Over three decades, warmest days, warmest nights, and coldest nights have shown significantly increasing trends except in the midland AEZ where warmest days decreased by 0.017°C/year (p<0.05). Temperature extreme’s magnitude of change is higher in the highland AEZ and lower in the midland AEZ. The trend in the daily temperature range shows statistically significant decrease across AEZs (p<0.05). A decreasing trend in the cold spell duration indicator was observed in all AEZs, and the magnitude of change is 0.667 days/year in lowland (p<0.001), 2.259 days/year in midland, and 1 day/year in highland (p<0.05). On the contrary, the number of very wet days revealed a positive trend both in the midland and highland AEZs (p<0.05). Overall, it is observed that warm extremes are increasing while cold extremes are decreasing, suggesting considerable changes in the AEZs.

Background: Assessing the magnitude of smallholder farmers’ livelihood vulnerability to drought is an initial step in identifying the causal factors and proposing interventions that mitigate the impacts of drought. This study aimed to assess smallholders’ livelihood vulnerability to the drought in the upper Awash sub-basin, Ethiopia. Household (HH) and climate data were used for indicators related to sensitivity, exposure, and adaptive capacity that define vulnerability to drought. The vulnerability of farmers’ livelihood to drought was compared among the studies agroecological zone (AEZ) and farm typologies. Results: The result illustrated a diverse magnitude of vulnerability index (VI) ranging from −1.956 to −4.253 for AEZ. The highest magnitude of VI was estimated for livelihood in the lowland AEZ, while the lowest magnitude of VI was estimated in midland AEZ. This could be accounted for by the fact that lowland farmers shown the highest exposure (0.432) and sensitivity (0.420) and the lowest adaptive capacity (0.288). A closer look at farmers’ livelihood typology, in each of the AEZ, showed substantial diversity of farmers’ livelihood vulnerability to drought, implying potential aggregations at AEZ. Accordingly, the vulnerability index for livestock and on-farm-income-based livelihood and marginal and off-farm-income-based livelihood typologies were higher than the intensive-irrigation-farming-based smallholders’ livelihood typology. Conclusions: Based on the result, we concluded that procedures for smallholders’ livelihood resilience-building efforts should better target AEZ to prioritize the focus region and farmers’ livelihood typology to tailor technologies to farms. Although the result emphasizes the importance of irrigation-based livelihood strategy, the overall enhancement of farmers adaptive capacity needs to focus on action areas such as reducing the sensitivity and exposure of the households, improving farmers usage of technologies, diversify farmers’ livelihood options, and, hence, long-term wealth accumulation to strengthen farmers’ adaptive capacity toward drought impacts.

No abstract

In response to global food price volatility and trends toward increased global food demand, Ethiopian policy makers were forced to adopt strategies such as restricting food exports in order to protect domestic food security. However, these policies can have a disproportionate regional impact on domestic markets and can result in lost revenue from exports. For this reason, they have been criticized as inefficient from the perspective of economic development. Here, we examine the sub-national dynamics of a ban on food exports. We do this for the case of Ethiopia's ban on exports of teff, a staple grain in the country that has increasing global demand. We assess the impact of the ban and of proposed policies to relax the ban, across regions within the country and for various market actors along the teff value chain. Using a partial-equilibrium model developed with a detailed modeling of the agro-economic features of the country, we analyze the direct impacts on export revenue, producers' profits, transport patterns, and consumption across the disaggregated regions in Ethiopia due to changes to its teff export policy. In particular, we show that the immediate benefit due to significant increase in international revenue due to large teff export would be enjoyed primarily by food distributors and storage operators while the crop producers' profits increase only negligibly. Simulations also indicate that lifting the export ban would be expected to have significant impacts on domestic transportation of teff between regions (for example from Mekelle to Werder), and to reduce consumption of teff significantly in some regions (for example, Semera, Jijiga), an effect due to the lack of competition in the transportation sector. The granularity of the model helps us capture the possibility of such lopsided benefits which were not captured in earlier studies.