Abstract:
Crop farming is crucial to the livelihoods of communities living in the rural areas of Kenya. The
sector largely depends on climatic variables such as rainfall for optimum crop output. This article
presents the analysis, interpretation and discussion of the research findings based on the
objective of assessing the climate variability of mean annual rainfall and its impact on crop
farming (maize output) in Nyandarua County. To achieve this objective, the researcher sought to
analyse rainfall amount and fluctuations in Nyandarua County for 21 years and correlate the
variable with crop output (maize) over the same period. The variability of rainfall and maize
output was analysed using descriptive statistics of mean, standard deviation and coefficient of
variance. Simple line trends and scatter graphs were used to show this variation. The inferential
statistics of regression and correlation analysis were used to establish the relationship between
the rainfall factor and the selected crop output. The null hypothesis associated to this objective
was tested using results of the correlation and regression analysis. Evidence of the study
indicated that the annual average rainfall had increased from 1999 to 2006. However, the last
fifteen years preceding the study, the mean annual rainfall had significantly fluctuated between
the peaks of 117 mm and off peaks of 67 mm. The utmost variation in the rainfall amount was
experienced between the years 2013 and 2007. Referring to the 21-year period of annual crop
output records, the output of maize greatly fluctuated between 2019 and 1999 with an average
tonnes of 29,145.76. Rainfall variability was concluded to have greatly influenced the changes in
maize output (r=0.688). The regression line for rainfall variability and maize output produced a
slope that was described by the equation y=463x - 11100 + ?. The regression value (R2 =
0.47189 showed that 47.19% of the fluctuation in maize output was as a result of the disparity in
rainfall amount and distribution. In conclusion, results of the study implied that rainfall amount
and distribution was highly erratic and unpredictable. Therefore this scenario exhibited much
uncertainty to the small scale farmers in the region. For better planning of the effect of climate
variability, the study recommended that policymakers and other relevant stakeholders should
come up with awareness programs through the provision of useful information that assimilate the
small holder farmer indigenous knowledge and perception and its effects on their livelihoods
with the accurate meteorological scientific data. |
