Rainfall is a complex phenomenon with high spatiotemporal variability. Identification of homogeneous rainfall zones to better analyse the rainfall intensity and extent is of vital significance for water resources management and mitigation of potential hazards from extreme events, i.e. droughts and floods. Appropriate zoning of homogeneous rainfall regions may give better understanding of rainfall patterns by resolving small scale variations. Although homogeneous rainfall zones have been established at country scale based on climatological mean behaviour, there has been little attempt to identify zones over broader scale with consistently homogeneous rainfall variability. This study employed K-means and Hierarchical clustering methods to establish homogeneous rainfall zones in the East Asia monsoon region (20°N–50°N, 103°E–149°E) using 30 years (1978–2007) monthly rainfall data at 0.5° grid resolution. Various cluster validation indices were used to assess the optimal number of homogeneous rainfall zones. The comparison of K-means and Hierarchical clustering showed that although both methods were able to define the homogeneous rainfall zones well with spatial contiguity, the K-means clustering outperformed the Hierarchical clustering in identifying more distinct zones with diverse rainfall characteristics. Mann-Kendall and linear regression tests were used for seasonal and annual rainfall trend analysis in the homogeneous rainfall zones. The study revealed that the region experiences distinct rainfall regimes over different zones. Furthermore, significant increasing and decreasing trends were observed over different zones with strong seasonal variation that indicate the aggravated stress of climate induced disasters, i.e. droughts and floods over the East Asia monsoon region.
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