It is vital to assess the regionalization of hydroclimatic variables such as flooding, evapotranspiration, and rainfall in order to optimize efficiency in design and reduce uncertainties.This study identified homogeneous rainfall regions using a combination of cluster analysis and the L-moments approach. The L-moments of heavy rainfall events of various durations (0.25, 1, 6, 12, 24, 48, 72, 96, and 120 h) were analyzed using seasonal (JuneSeptember) rainfall measurements at 47 meteorological stations over the period 20062016. In the primary phase of this study, the homogeneity of Mumbai as a single region was examined by statistical testing (based on L-moment ratios and variations of the L-moments). The K-means clustering approach was applied on the site characteristics to identify candidate regions. Based on the most appropriate distribution, these regions were subsequently tested using at-site statistics to form the final homogeneous regions. The results identified that for durations above 1h, regionalisation procedure delineated six clusters of similarly-behaved rain gauges, where each cluster represented one separate class of variables for the rain gauges. However, for durations, below 1h the regionalisation procedure has not been efficient in the sense of meeting the homogeneous regions for rainfall. Furthermore, the final clusters confirmed the spatial variation of rainfall as a result of the complex topography, which comprised flatlands (below or at mean sea level), urban areas with high rise buildings, and mountain and hilly areas.