Assessing the potential of maize growing seasons for Western Kenya using agro-climatic indices

Abstract

Kenya relies mainly on rain-fed agriculture for crop production, which has major limitations arising from seasonal variability of rainfall, onset, cessation and growing length. In this study, the growing season characteristics for Lake Victoria basin were studied with the aim of providing information for rain-fed agriculture planning. The study evaluated various criteria for determining growing season onset and cessation dates using soil water balance simulation techniques in addition to indigenous knowledge. Results indicate that frequently used traditional indicators in the region as modes of rainfall forecasting include: trees, migratory birds, winds, clouds and lightning among others. Initial evaluation of some key indicators around Eldoret area, through monitoring before onset of long rains suggest good agreement between indigenous and scientific climate knowledge and forecasting systems. Onset simulation results reveal that accumulated rainfall depth criterion of 40 mm in 4 days can be used as an operational criterion for wet sowing method. Integrating indigenous and scientific climate knowledge together with forecasting systems provides a means of aiding farmers in their decision making on when to dry sow within the established onset window. For each station in the basin probability of exceedance levels for: onset date, cessation date and growing season length were calculated. Individual station values for the entire study area were converted into surface maps using interpolation techniques to capture spatial variations for agricultural planning. Results indicate that there exists organized progression of rainfall onset within the study area with the long rains showing a southerly progression.