INFLUENCE OF WEATHER AND CLIMATE INFORMATION SERVICES AND CLIMATE-SMART TECHNOLOGIES ON BEAN PRODUCTIVITY AND HOUSEHOLD RESILIENCE AMONG SMALLHOLDER FARMERS IN HOMA BAY TOWN SUB-COUNTY, KENYA

Abstract

Climate change and variability continue to constrain smallholder agricultural productivity and resilience in sub-Saharan Africa. Weather and Climate Information Services (WCIS) and Climate-Smart Technologies (CSTs) are promoted as primary adaptation strategies. Yet, there is no comprehensive empirical evidence on the combined effects of these strategies on the productivity and resilience of common bean farmers. Common bean was selected because it promotes food security, household nutrition and income among smallholder farmers in Kenya, including Homa Bay Town-Sub-County; however, it is highly sensitive to climate variability. This study broadly assessed how WCIS affects the adoption of CSTs and its implications for common bean productivity and the resilience of farmers in Homa Bay County, Kenya. A mixed-methods design that is quasi-experimental and a cross-sectional survey was adopted, involving a sample size of 157 bean farmers previously subjected to WCIS training conducted over a defined period before this study, after which no further training was conducted. A quasi-experimental design was used to compare CST adopters (n=25) and non-adopters of CST (n=25) with the remaining 107 farmers involved in a cross-sectional survey. The structured questionnaires and observation checklists were used to obtain data, which were analyzed through descriptive statistics, log-linear regression and the Structural Equation Model (SEM). All the respondents reported access to WCIS, and 59.2% of the farmers reported that key farm decisions were made using the WCIS and that CSTs were adopted because of the WCIS. The most commonly adopted CSTs were intercropping (54.1%) and organic manure application (49.7%). Farmers' adoption of weather-informed farming practices was high, with 96.2% changing planting dates and 95.5% using early-maturing bean varieties. Nearly 84.7% of farmers reported higher common bean production, and 78.3% reported lower losses. The intensity of CST adoption was significantly associated with higher common bean productivity, with mean yields ranging from 135.8 kg acre⁻¹ for non-adopters to 348.2 kg acre⁻¹ for adopters. Log-linear regression analysis revealed that for every increment in the level of adoption of CST, common bean yields increased significantly by 41.8% (β = 0.349, P ≤ 0.003). The results from SEM showed that the adoption of CST was significantly affected by WCIS (β = 0.447, P ≤ 0.001) and that common bean productivity also had a significant positive effect on household resilience (β = 0.341, P ≤ 0.001). Unreliable weather forecasts, insufficient information and lack of confidence in providers were the most common obstacles. The present study found that the use of reliable WCIS coupled with CSTs could significantly boost common bean productivity and enhance smallholders' resilience to climate change. Based on these findings, the study recommends strengthening access to timely and reliable weather and climate information services, alongside promoting the adoption of climate-smart technologies through enhanced extension services, farmer training, and supportive policy frameworks.