Determinants of farmers’ choice of adaptation strategies to climate change in Semen Bench District, Southwest Regional State, Ethiopia

Relevance. Climate change is a severe problem in Ethiopia as a whole, but especially in the study area, where people rely on subsistence rain-fed farming. Effective adaption changes in climatic conditions are critical to securing resilient farmers' livelihoods.

Methodology. As a result, this study investigated farmers' choices and factors influencing their adaptation strategies to climate change in Semen Bench District, Southwest Ethiopia, which is heavily impacted by climate change pressure. This study utilized a cross-sectional survey and time series data research design. A multistage stratified random sampling procedure collected from 216 randomly selected sample households using a pretested questionnaire survey. The supplementary data were collected from purposely-selected fifteen key informants; (twenty) focus group participants. Farmers' climate change adaptation techniques were described using descriptive statistics and an econometric model. To determine the characteristics influencing household adaptation methods to climate change, a multivariate probit model was used.

Results. The model results showed that the likelihood of families employing soil and water conservation (SWC), enhanced and diversified crops, tree planting and agroforestry, irrigation, and organic fertilizers were 47.8%, 38.9%, 54.1%, 63.4%, and 59.6%, respectively. Multivariate probit model were applied to identify factors that influence the farmer's decision to adapt to climate change. The MVP model confirmed that the factors had statistically significant (P<0.01, 0.05, and 0.1) effects on the choice of adaptation responses such as the household head's sex, age, education level, household size, farm size, farm income, ownership of tropical livestock, access to credit, extension visit, farmer-to-farmer extension, access to climate information, farmer experience, and the average distance from home to the farm.

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