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THE LIVELIHOOD VULNERABILITY AND ADAPTATION STRATEGIES OF SMALLHOLDER FARMERS TO THE CLIMATE CHANGE AND VARIABILTY IN MAREKA DISTRICT, DAWURO ZONE, SOUTH WEST ETHIOPIA
(2024-10-23) GIRMA MITA ABDETA
Ethiopia is among the most susceptible countries in the world due to climatic variability and change, which can lead to flooding and drought. Climate change occurs by high temperature, scarce rainfall, and high amount of rainfall variability reduces crop yield and shortage of food security in low income and economies that based on agriculture. The main objective of this study was to explore and analyze Livelihood Vulnerability of smallholder Farmers to the Climate Change and Variability in Mareka District, South West Region, and Ethiopia. Both qualitative and quantitative methods were used for this research data collection and analysis. Primary data were collected from 117 randomly selected farming households from three kebeles using structured questionnaires, interviews, focus group discussions and observations. Data on rainfall and temperature from 1992 to 2022 as well as Mann- Kendall test and regression analysis was used to detect trends and variability. A modified form of Sustainable Livelihoods Framework combined with Livelihood Vulnerability Index was employed to estimate livelihood vulnerability. According to the survey results, about 79.5% of the respondents perceive that the rainfall amount in the study area is decreasing. But the results are not supported by, long-term recorded rainfall data showed that the annual rainfall is increasing by the rate of 4.6206 mm annually over the past 31 years despite being statistically non-significant, the mean annual rainfall was 1316 mm with 25% of the coefficient of variation which is moderately variable based on the degree of variability. Similarly, 80% of interviewed farmers said that temperature is an increasing trend, which confirms the results from the analysis of long-term recorded data by NMA that indicated the mean average minimum and maximum temperatures are increasing by 0.069 0C and 0.027 0C per annum respectively. The result from the analysis of vulnerability to climate change indicated that about 22% of farmer's livelihoods were highly vulnerable to climate change and variability, 48% were medium vulnerable and 29.9% were least vulnerable to climate change and variability due to high exposure, low adaptive capacity, and high sensitivity in the study area. Furthermore, the study revealed that the farmers of mareka district took a number of measures to adapt to climate change within their capacity. These adaptation strategies include planting early maturing varieties, planting high-yielding varieties, changing crop variety, crop diversification, soil and water conservation, Emphasis on live stock keeping instead of crop cultivation, practicing crop rotation and practicing agro forestry. The main barriers to adaptation to climate change are t h e economic status of households, poor infra structural development, poor farming system, lack of credit access, low educational level of households, and lack of labor. Therefore, government should be trains and teach farmers on the issue of climate change to create awareness ,upscale the local adaptation strategies and support to overcome the vulnerability to climate change and constraints in which they face in using adaptation strategies to climate change and so that ensure sustainable livelihoods
FARMER’S PERCEPTION ON CLIMATE CHANGE AND THEIR ADAPTATION STRATEGIES IN KĀLU DISTRICT SOUTH WOLLO ZONE ETHIOPIA
(2025-11-19) ALI JEMAL YIMER
Climate Change is causing the greatest environmental, social and economic threats to all of humankind and across borders of many countries. However, developing countries are the most adversely affected by the impacts of Climate induced events because of their low levels of adaptation. This study was intended to answer how farmers perceive climate change and to compare their perception with its climate change variability of historical data of the past 30 years (1987-2016). The study also assessed factors influencing farmer’s perception and adaptation strategies to cope with potential impacts of climate change. The study was conducted in three kebeles of Kalu district in south Wollo Zone of Amahara Regional state. It relied on qualitative and quantitative methods of data collection. The primary data were collected using household survey, FGDs, and field observation. Mann-Kendall’s test and Sen’s Slope estimator were used to detect the trend and its magnitude. Standard rainfall anomaly precipitation concentration index and coefficient of variations were used to describe of rainfall variability. 152 households were interviewed, besides focus group discussion and key informants interview were utilized to triangulate and substantiate the findings from household survey. Data was analyzed using descriptive statistics and econometric models. The result showed age, gender education and distance to the local market, had positive and significant influence on farmer’s perception on climate change. However, wealth, agro-ecology and land size had an inverse and significant influence on the perception of farmer is to climate change. Land holding size, education, wealth, distance to the local market climate information and gender had positive and significant influence on choice of adaptation strategies. The finding of the result showed that Bleg season total rainfall exhibited statistically significant declined trend 36.9 mm per decades. The annual maximum rainfall were 1362 mm in 2016 while the lowest annual records were 725 mm in 1987 with the range of 637 mm. the average mean annual rainfall of the last three decades were 1033.88mm with standard deviation of about 159.99 where these much amount rainfall deviated from the mean. The annual average maximum temperature were increased by 1.3oc , durning Belg season before 30 years were 25.5oc, after 30 years the maximum-minimum temperature recorded was 29.3oc in 2016 it increases 3.8oc for the last three decades indicated that there was high inter-seasonal temperature and rainfall variability.