Impact of Annual Temperature and Rainfall Anomalies on Maize Yields in Machakos County: An Analysis from 1993 To 2023

Purpose: To investigate the impact of Annual temperature and Rainfall Anomalies on Maize Yields in Machakos County from 1993 to 2023. Methodology: The study utilized qualitative and quantitative data, collected through structured questionnaires as primary data and a secondary time series data template for secondary data. The target population included households, agricultural officers, and administrative officers in Matungulu East, Kaani/Kaewa, Mwala/Makutano, Ikombe, and Kangundo East wards. The sampled administrative wards contained 36,976 maize farming households selected through purposive sampling. The population was determined using Yamane's formula, resulting in a sample size of 395 maize farmers (households). Maize farming households were identified using cluster random sampling. Results: The study found a statistically significant negative effect of temperature variability on maize yields (β=-0.054, p=0.000). This implies that a one-unit increase in temperature variability is associated with a 0.054 tones per hectare decrease in maize yields, highlighting the sensitivity of maize to temperature extremes. Conversely, rainfall variability showed a negative but statistically insignificant effect on maize yields (β=-0.020, p=0.946). This suggests that other factors, possibly adaptation strategies, may mitigate the impact of inconsistent rainfall on maize yields. Unique contribution to theory, policy and practice: The study underscores the differential impacts of temperature and rainfall variability on maize yields, emphasizing the need for targeted adaptation strategies to manage temperature fluctuations. Recommendations include promoting heat-resistant maize varieties, improving irrigation infrastructure, and enhancing water management practices. These insights contribute to agricultural planning and policy-making, aiming to enhance the resilience of farming households in Machakos County to climate variability.