Abstract:
In Burundi, agriculture engages for approximatively 80% of the economically
active population and it remains a very important economic sector. In this part of
the world rainfed agriculture is largely dominant; food security and income of
rural populations are vulnerable to rainfall variability. Therefore, rainfall being an
important climatic factor in crop production, the main objective of this research
was to analyze the spatial and temporal variability of rainfall in Burundi.
For this purpose, 16 meteorological stations with 30 years of data record have
been used. Investigation of monthly, seasonal and annual rainfall variability using
different methods reveals that there is spatial variability of rainfall in Burundi.
Spatial analysis shows that the entire country can be classified into four
homogeneous zones depending upon their moisture availability index. The
results indicated that distribution of annual rainfall didn't show significant change
within the period considered. The seasonal variability analysis shows that the
temporal distribution of the
·
asons is variable from year to year. From
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monthly rainfall variabi ·
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alysis,·· ttie--1 nths of May, June, July, August,
September and Oct .' � a/;: characterized y high variability in rainfall data
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series indicating low eliability of r�,Lnfall: dy_ · g these periods. The remaining
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months of the years wed Iess-tomoderet variability. Another observation is 7. ............
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that rainfall variation in �afe����__tb.e·-t�Ef' comes shorter, i.e. the variability is
higher when evaluated on.�o'.a!bJY_Ji�rfthan on annual basis. Trend detection
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analysis conducted using Mann-Kendall non-parametric test on monthly rainfall
series with high variability showed negative trend indicating the decrease in
precipitation, but this trend was statistically significant for some months and
stations. Because of variability of rainfall in space within the study area, the
future research should increase the spatial coverage by including more number
of stations. Moreover, it is also suggested to extend the analysis to other time
scales such as daily or ten days period in order to see the effect of rainfall
variability over short time intervals on crop production. Further studies are also
recommended to predict the future monthly and seasonal distribution of rainfall.
