Fuzzy Clustering for Regionalization of Drought Proneness in Peninsular Malaysia

In this study, the Gustafson-Kessel (GK) fuzzy clustering method is used to classify the 35 rainfall stations in Peninsular Malaysia into homogeneous regions. First, the GK fuzzy clustering algorithm is applied to identify the initial region. The next step is to test the discordancy and homogeneity of corresponding region. Finally, adjustment of region is done to obtain the homogeneous region. The results showed that, for thirty five rainfall stations studied, these stations could be grouped into six homogeneous regions. The first region covers the northwestern and northern of Peninsular Malaysia, region 2, 3 and 4 cover the western, region 5 covers the southwestern and region 6 covers the eastern. The study also indicates that, based on the average Standardized Precipitation Index (SPI) value for one-month time scale, region 2 experiences more frequent extreme drought condition. However, based on the SPI, drought events randomly occurred in all regions, moreover these regions experience drought events within a year. The results also showed that GK fuzzy clustering method could be applied to construct a homogeneous region.