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.
