This study investigated the trends and variability of seasonal and annual rainfall and temperature data over southern Ethiopia using time series analysis for the period 1983–2016. Standard Anomaly Index (SAI), Coefficient of Variation (CV), Precipitations Concentration Index (PCI), and Standard Precipitation Index (SPI) were used to examine rainfall variability and develop drought indices over southern Ethiopia. Temporal changes of rainfall trends over the study period were detected using Mann Kendall (MK) trend test and Sen’s slope estimator. The results showed that the region experienced considerable rainfall variability and change that resulted in extended periods of drought and flood events within the study period. Results from SAI and SPI indicated an inter-annual rainfall variability with the proportions of years with below and above normal rainfall being estimated at 56% and 44% respectively. Results from the Mann Kendall trend test indicated an increasing trend of annual rainfall, Kiremt (summer) and Bega (dry) seasons whereas the Belg (spring) season rainfall showed a significant decreasing trend (p < 0.05). The annual rate of change for mean, maximum and minimum temperatures was found to be 0.042 °C, 0.027 °C, and 0.056 °C respectively. The findings from this study can be used by decision-makers in taking appropriate measures and interventions to avert the risks posed by changes in rainfall and temperature variability including extremes in order to enhance community adaptation and mitigation strategies in southern Ethiopia.

Climate change has the greatest negative impact on low-income countries, which burdens agricultural systems. Climate change and extreme weather events have caused Ethiopia’s agricultural production to decline and exacerbated food insecurity over the last few decades. This study investigates whether farmers’ awareness and perceptions of climate change play a role in climate change adaptation using climate-smart agricultural practices. To collect data, 385 households in Southern Ethiopia were sampled using a multistage sampling. A Heckman probit two-stage selection model was applied to investigate the factors influencing farmers’ perceptions to climate change and adaptation measures through adoption of climate-smart agriculture practices, complemented with key informant interviews and focused group discussions. The results indicated that most farmers (81.80%) perceived that the local climate is changing, with 71.9% reporting increased temperature and 53.15% reporting decreasing rainfall distribution. Therefore, farmers attempted to apply some adaptation practices, including soil and water conservation with biological measures, improved crop varieties, agroforestry, improved breeds, cut and carry system, controlled grazing, and residue incorporation. The empirical results revealed that farmers adaptation to climate change through adoptions of CSA practices was significantly influenced by education, family size, gender, landholding size, farming experience, access to climate information, training received, social membership, livestock ownership, farm income and extension services. The study found that farmers’ perceptions of climate change and variability were significantly influenced by their age, level of education, farming experience, and access to climate information, hence, the need to focus on enhancing the accuracy of weather information, strengthening extension services, and considering a gender-sensitive adaptation approach toward improving farmers’ knowledge and aspirations. Agricultural policies should support the efforts of farmers to increase the reliance on climate risk and alleviate farmers’ difficulties in adopting climate-smart agriculture practices.

It is critical to develop technologies that simultaneously improve agricultural production, offset impacts of climate change, and ensure food security in a changing climate. Within this context, considerable attention has been given to climate-smart agricultural practices (CSA). This study was conducted to investigate the effects of integrating different CSA practices on crop production, soil fertility, and carbon sequestration after being practiced continuously for up to 10 years. The CSA practices include use of soil and water conservation (SWC) structures combined with biological measures, hedgerow planting, crop residue management, grazing management, crop rotation, and perennial crop-based agroforestry systems. The landscapes with CSA interventions were compared to farmers’ business-as-usual practices (i.e., control). Wheat (Triticum sp.) yield was quantified from 245 households. The results demonstrated that yield was 30–45% higher under CSA practices than the control (p < 0.05). The total carbon stored at a soil depth of 1 m was three- to seven-fold higher under CSA landscapes than the control. CSA interventions slightly increased the soil pH and exhibited 2.2–2.6 and 1.7–2.7 times more total nitrogen and plant-available phosphorus content, respectively, than the control. The time series Normalized Difference Water Index (NDWI) revealed higher soil moisture content under CSA. The findings illustrated the substantial opportunity of integrating CSA practices to build climate change resilience of resource-poor farmers through improving crop yield, reducing nutrient depletion, and mitigating GHG emissions through soil carbon sequestration.

This study investigated the impacts of climate change on the hydrology of the Upper Awash Basin, Ethiopia. A soil and water assessment tool (SWAT) model was calibrated and validated against observed streamflow using SWAT CUP. The Mann–Kendall trend test (MK) was used to assess climate trends. Meteorological drought (SPEI) and hydrological drought (SDI) were also investigated. Based on the ensemble mean of five global climate models (GCMs), projected increases in mean annual maximum temperature over the period 2015–2100 (compared with a 1983–2014 baseline) range from 1.16 to 1.73 °C, while increases in minimum temperature range between 0.79 and 2.53 °C. Increases in mean annual precipitation range from 1.8% at Addis Ababa to 45.5% over the Hombole area. High streamflow (Q₅) declines at all stations except Ginchi. Low flows (Q₉₀) also decline with Q₉₀ equaling 0 m³ s⁻¹ (i.e., 100% reduction) at some gauging stations (Akaki and Hombole) for individual GCMs. The SPEI confirmed a significant drought trend in the past, while the frequency and severity of drought will increase in the future. The basin experienced conditions that varied from modest dry periods to a very severe hydrological drought between 1986 and 2005. The projected SDI ranges from modestly dry to modestly wet conditions. Climate change in the basin would enhance seasonal variations in hydrological conditions. Both precipitation and streamflow will decline in the wet seasons and increase in the dry seasons. These changes are likely to have an impact on agricultural activities and other human demands for water resources throughout the basin and will require the implementation of appropriate mitigation measures.

Climate change impacts on agriculture have become evident, and threaten the achievement of global food security. On the other hand, the agricultural sector itself is a cause of climate change, and if actions are not taken, the sector might impede the achievement of global climate goals. Science-policy engagement efforts are crucial to ensure that scientific findings from agricultural research for development inform actions of governments, private sector, non-governmental organizations (NGOs) and international development partners, accelerating progress toward global goals. However, knowledge gaps on what works limit progress. In this paper, we analyzed 34 case studies of science-policy engagement efforts, drawn from six years of agricultural research for development efforts around climate-smart agriculture by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Based on lessons derived from these case studies, we critically assessed and refined the program theory of the CCAFS program, leading to a revised and improved program theory for science-policy engagement for agriculture research for development under climate change. This program theory offers a pragmatic pathway to enhance credibility, salience and legitimacy of research, which relies on engagement (participatory and demand-driven research processes), evidence (building scientific credibility while adopting an opportunistic and flexible approach) and outreach (effective communication and capacity building).

This paper analyses the impact of climate-smart agriculture (CSA) technologies on household dietary diversity and food insufficiency as indicators of food and nutrition security in Kenya. Using a combination of Propensity Score Matching and endogenous treatment effect approaches, we found that adoption of stress-tolerant varieties of several crops (such as bean, pigeon pea, cowpea, maize and sorghum) improved household dietary diversity score by 40% and reduced food insufficiency by 75%. Adoption of improved and resilient livestock breeds (including Red Maasai sheep and Galla goats) improved household dietary diversity by 38% while reducing household food insufficiency by 90%. We also found that stress-tolerant crop varieties were more effective in improving food security outcomes among households with large landholdings and with more educated and younger to middle-age heads. Effects of resilient livestock breeds on household food security were much stronger for households with large landholdings and with young and/or much older heads that have low levels of education. Given the large, demonstrated benefits from the use of the CSA technologies, policies and programs aimed at their promotion should apply appropriate targeting to ensure wider uptake of the technologies and maximum returns on investment.