Long-term urban land use land cover change (LULCC) dynamics and climate change trends in Southwest Ethiopia's four urban centers were examined for 60 years. Remote sensing, aerial photos, and Landsat, temperature, and rainfall data were analyzed from a climate change perspective over the Jimma, Bedelle, Bonga, and Sokorru urban centers of southwest Ethiopia from 1953 to 2018. Based on geospatial analysis and maximum likelihood supervised image classification techniques to classify LULCC categories, the Mann-Kendall test was applied to perform trend analyses on temperature and rainfall. The LULCC analysis revealed that built-up areas over the urban centers had shown an increasing trend, with the highest increment by 2,360 hectares over Jimma, while vegetation, wetland, and cropland declined due to conversion of plain lands to built-up areas and other similar zones. The pronounced decline of vegetation coverage was 1,427, 185,116, and 32 hectares in Jimma, Bedelle, Bonga, and Sokorru, respectively. Mann-Kendall test results showed a significant sign of intra-seasonal and inter-annual variability of rainfall while the summer and annual rainfall patterns remained less variable compared to other seasons. This study's findings revealed that when the mean between the two climatic normals of 1953–86 is compared with 1987–2018, the temperature has significantly increased in the latter three decades. The rapid expansion of built-up areas coupled with a sharp decline of green space or vegetation and agricultural/croplands could lead to gradual changes in LULCC classes, which have contributed to the changing of the local climate, especially the surface temperature and rainfall over the urban centers of southwest Ethiopia. Therefore, we recommend that the local urban administrations emphasize sustainable urban development by integrating urban planning policies with land use to protect the environment by adopting local municipal adaptation and national climate change strategies. Restoration of the local environment and creation of climate-smart cities could be critical to the resilience of urban dwellers and ecosystems to the changing climate by enhancing grass-root climate services. To that end, we recommend further advanced research to understand how urban LULC-related changes and other factors contribute to local and regional climates, as urban areas of Southwest Ethiopia are undergoing a rapid transformation of their rural surroundings.

This study assesses the perceptions and vulnerability of the farming communities to climate change in the southwestern parts of Ethiopia. Climate change vulnerability assessment is a prerequisite to designing climate change adaptation strategies. A multistage cluster sampling technique was used to select four of the six zones from the southwestern parts of Oromia. Close-ended and open-ended questionnaires were used to assess household perceptions of climate change and the degree of vulnerability to climate change by using five household capitals: natural, social, financial, physical, and human capital. Data were collected from 442 households in 4 districts: Jimma Arjo, Bako Tibe, Chewaka, and Sekoru. The vulnerability of the farming communities was assessed using the households’ livelihood vulnerability index. A total of forty indicators from five capitals were applied to calculate household livelihood vulnerability to climate change. Household perceptions of climate change had a statistically significant relationship with changes in rainfall pattern (75.6%, p < 0.001), temperature pattern (69.7%, p < 0.001), drought (41.6%, p = 0.016), flood (44.1%, p = 0.000), and occurrence of early (53.2%, p < 0.001) and late rain (55.9%, p < 0.001). The results show that households in the Sekoru district were the most vulnerable (0.61), while households in the Jimma Arjo district were less vulnerable (0.47) to the effect of climate change. Household vulnerability to climate change is mainly related to the occurrence of drought, lack of much-needed infrastructure facilities, and weak institutional support. Links with financial organizations are also lacking in the household. The findings of this study will help policymakers to address the impact of climate change. To support disaster risk management on the one hand and increase the resilience of vulnerable societies to climate change on the other, we recommend a detailed assessment of the remaining districts of the region.

The impacts of various climatic conditions, such as temperature and rainfall variabilities, are very critical and sensitive to rain-fed crop production, particularly over the water stress arid and semi-arid regions of Ethiopia. This study was designed to evaluate the potential impact of climate variability and change on sorghum grain yield in the Babile district of eastern Ethiopia. The study was conducted based on observed and model-based simulated projected rainfall and temperature obtained from the Ethiopian Meteorological Institute and General Circulation Models (GCM) used by the Intergovernmental Panel on Climate Change (IPCC) of the Fifth Assessment Report CMIP5) and Agricultural Model Inter-comparison and Improvement Project (AgMIP). Three GCM models, namely GFDLESM2M, CanESM2, and HadGEM2-ES under RCP4.5, were considered to generate future climate projections for the near-term 21st century. Various univariate and multivariate statistical techniques were employed to compute and identify whether the impacts of climate variability and change on rain-fed sorghum crop performance were reasonably viable over the districts where grain yield is highly stable and productive under normal climate conditions. Our findings revealed that more stable and better rainfall performance from May to September, the season when sorghum crops are normally planted in the Babile district, was positively correlated, while the maximum and minimum temperatures of the season were negatively correlated with sorghum grain yield. A significant association has been detected between sorghum grain yield and its growing period rainfall, number of rainy days, and maximum and minimum temperature with multi-regression analysis. Thus, the variability of rainfall in August, June temperature, and the number of rainy days in September significantly impacted sorghum crop productivity. As a result, the multi-regression model adjusted R-squared indicated that 77% variance in annual sorghum yield performance was explained by rainfall and temperature conditions that prevailed during the crop growing period. During the past period, there was a significant increase in sorghum yields, which are projected to decline during the near term of the 21st century in the future. This revealed that declining and disturbed rainfall performance and increases in temperature are likely to reduce overall sorghum grain yield in the Babile district. We recommend that there is a need to enhance awareness for smallholder farmers on the adverse impact of climate variability and change on sorghum grain yield. In view of this, the farmers need to be geared toward employing climate-smart agriculture as a possible adaptation measure to reduce the negative impacts of climate variability and change on rain-fed crop production practices in the Babile district and other arid and semi-arid parts of eastern Ethiopia.

Projections of future climate change trends in four urban centers of southwest Ethiopia were examined under a high Representative Concentration Pathways (RCP8.5) scenario for near- (2030), mid- (2050), and long-term (2080) periods based on high-resolution (0.22⁰) Coordinated Regional Climate Downscaling Experiment (CORDEX) for Africa data. The multi-model ensemble projects annual maximum and minimum temperatures increasing by 0.047 °C per year (R² > 0.3) and 0.038 °C per year (R² > 0.7), respectively, with the rates increased by a factor of 10 for decadal projections between the 2030s and 2080s. The monthly maximum temperature increase is projected to be 1.41 °C and 2.82 °C by 2050 and 2080, respectively. In contrast, the monthly minimum temperature increase is projected to reach +3.2 °C in 2080. The overall seasonal multi-model ensemble average shows an increment in maximum temperature by +1.1 °C and +1.9 °C in 2050 and 2080, with the highest change in the winter, followed by spring, summer, and autumn. Similarly, the future minimum temperature is projected to increase across all seasons by 2080, with increases ranging from 0.4 °C (2030s) to 3.2 °C (2080s). All models consistently project increasing trends in maximum and minimum temperatures, while the majority of the models projected declining future precipitation compared to the base period of 1971–2005. A two-tailed T-test (alpha = 0.05) shows a significant change in future temperature patterns, but no significant changes in precipitation were identified. Changes in daily temperature extremes were found in spring, summer, and autumn, with the largest increases in extreme heat in winter. Therefore, our results support proactive urban planning that considers suitable adaptation and mitigation strategies against increasing air temperatures in urban centers in southwest Ethiopia. Future work will examine the likely changes in temperature and precipitation extremes.

Drought is an extreme event that causes great economic and environmental damage. The main objective of this study is to evaluate sensitivity, characterization and propagation of drought in the Upper Blue Nile. Drought indices: standardized precipitation index (SPI) and the recently developed standardized reconnaissance drought index (RDIst) are applied for five weather stations from 1980 to 2015 to evaluate RDIst applicability in the Upper Blue Nile. From our analysis both SPI and RDIst applied for 3-, 6-, 12 month of time scales follow the same trend, but in some time steps the RDIst varies with smaller amplitude than SPI. The severity and longer duration of drought compared with others periods of meteorological drought is found in the years 1984, 2002, 2009, 2015 including five weather stations and entire Upper Blue Nile. For drought relationships the correlation analysis is made across the time scales to evaluate the relationship between meteorological drought (SPI), soil moisture drought (SMI), and hydrological drought (SRI). We found that the correlation between three indices (SPI, SMI and SRI) at different time scales the 24-month time scale is dominant and are given by 0.82, 0.63 and 0.56.