Associated Farm and Farmer-Specific Factors for Climate-Smart Agriculture Adaptation in the Dry Zone: A Case from Vavuniya, Sri Lanka

Climate-Smart Agriculture (CSA) technologies have been introduced to mitigate adverse climate change impacts. However, the adaptation of CSA technologies by farmers is relatively low in the dry zone of Sri Lanka. This study focuses on how farmers’ adaptation behavior for CSA technologies varies with household characteristics, economic status, and farm characteristics. Data on 94 farmers were collected using a pre-tested questionnaire. A score was developed for each farmer on the adaptation of CSA technologies under 4 broad categories namely: water and energy-smart, nutrient and soil-smart, carbon and weather-smart, and knowledge and yieldsmart. A generalized linear model (GLM) was employed to identify the factors that influence farmers’ adaptation and the level of adaptation. According to GLM results, income increases the adaptation of water and energy-smart technologies, while land ownership and managing livestock compared to labour decrease the adaptation. Adaptation of nutrient and soil-smart technologies were positively influenced by experience, and training while negatively influenced by labor use and managing livestock compared to crops. Adaptation of carbon and weather-smart technologies were positively influenced by income, cost of transport, higher education levels, managing both crop and livestock compared to only crop, and training while negatively influenced by the gender of the household head and household size, source of income, and land ownership. Knowledge and yield-smart technologies were positively influenced by income, level of education, and training while negatively influenced by only managing livestock compared to crops. Overall, the results suggest the importance of providing training and facilitating knowledge dissemination in addition to understanding the subtle issues that act as barriers to the adaptation of CSA technologies in dry zone farming.