A field survey was conducted in Kitui County, Kenya, to assess farmers’ vulnerability to climate variability and extreme climate events in selected agroecological zones. Primary data was collected through the administration of questionnaires to 341 respondents. Rainfall data for the study was obtained from the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall dataset while temperature data was obtained from the Climatic Research Unit gridded Time Series (CRU TS) dataset. The study used the indicator approach to calculate the overall household vulnerability index. Principal Component Analysis (PCA) was used to allocate weights to indicators of exposure, sensitivity, and adaptive capacity. Vulnerability results indicated that the arid zone had the highest vulnerability index (17.29) followed by the transitional (1.63) and semi-arid (1.49) zones while the semi-humid zone had the least (-2.65). Additionally, results from one-way Analysis of Variance (ANOVA) indicated a statistically significant difference in the vulnerability index and its components’ indices across the four agroecological zones. The study established that adaptive capacity was the most important component in reducing households’ vulnerability to climate variability and extreme climate events and can thus be influenced by policy to enhance households’ resilience to climatic shocks. Policy measures and climate change adaptation programs should therefore aim at enhancing the adaptive capacity of households. 

 

Key words: Vulnerability index, principal component analysis, adaptive capacity, arid and semi-arid lands (ASALs), households.