Abstract:
Climate change has severe impacts on natural resources, food production and consequently
on food security especially in developing countries. Likely accentuated by climate change, flooding
is one of the disasters that affects people and destroies agricultural land and products. At different
governance levels and scales, appropriate responses are needed. Cluster analysis using scaled
at-site characteristics was used to determine homogeneous rainfall regions. A methodology for
detecting change was applied to heavy daily rainfall of 34 stations across the Ouémé basin, Benin,
in order to assess potential change in its characteristics. The spatial variability of the detected
changes in return periods was analyzed using the kriging interpolation method. For this analysis,
up to 92 years (1921–2012) of rainfall data were used. Three homogeneous regions were found
by the cluster analysis. For all studied return periods, 82% of the stations showed statistically
significant change in daily precipitation, among which 57% exhibited a positive change and 43%
negative change. A positive change is associated with an increase in heavy rainfall over the area
of concern. An analysis of the interpolated change in heavy rainfall of different return periods
revealed an east-west gradient from negative to positive along the lower Ouémé basin (Region 2).
From the middle to the upper Ouémé (Region 1 and 3), a decreasing tendency of heavy rainfall is
dominant mainly for the non-homogeneous period. This result of the complex pattern of changes
could be veritable information for decision makers and consequently for development of appropriate
adaptation measures.
