INFLUENCE OF SEASONAL RAINFALL FORECASTS ON MAIZE YIELD IN TONGAREN SUB-COUNTY, BUNGOMA COUNTY, KENYA

Abstract

The two main seasonal rainfall forecasts that are important for maize production in the Tongaren Sub-County are the March, April, May (MAM) and the June, July, August, September (JJAS). The main objective of this study was to examine the influence of seasonal rainfall forecasts on maize yield in Tongaren Sub- County in Bungoma County. The specific objectives were to; determine the trends of seasonal variability of rainfall in Tongaren Sub-County, evaluate the factors influencing utilization of seasonal rainfall forecasts and assessment of the benefits of using seasonal rainfall forecasts on maize crop yield in Tongaren Sub-County. Multi-stage sampling was applied to determine the sample size of 395 maize farmers and descriptive and inferential statistics were used to analyze the data. The research design adopted was descriptive survey. The unit of analysis was individual maize farmer household at the farm level. Excel, SPSS and XL STAT data analysis tools were used in the analysis of the data. The primary data was collected using questionnaires for households’ interview, key informant interviews, focus group discussions and observation checklists. Secondary data comprising monthly precipitation of Tongaren for the period spanning between 1985 and 2022 was sourced from Kenya Meteorological Department while the yearly maize yield was provided by Bungoma County Department of Agriculture. Time series plots were done and the trends analyzed by Mann Kendall trend analysis to determine whether the trends were significant or not. Results show that there is significant inter annual and intra-seasonal rainfall variability. Rainfall variability during MAM and JJAS was found to be 20.7% and 20.6%, respectively. Further results show that there exist varied factors that determine access to and usability of seasonal rainfall forecasts. Among them are; lack of awareness, lack of relevant downscaled climate information, lack of capacity to interpret climate information and late delivery of climate information among others. The result of the correlation analysis showed that rainfall amount had positive relationship with maize yields (correlation of 0.53 for JJAS, 0.4 for March to September and 0.05 for MAM). The study concluded that there was significant rainfall variability which could be linked to fluctuations in maize yields and had the potential to affect future maize production in the study area. The study recommends the following; there should be close collaboration between climate information providers and the users, co-production of climate information, enhancement of timely and accurate weather forecasts and that the climate information availed to the users should be accompanied by agronomic advice.