Understanding the occurrence of natural disasters in regions where the occurrence is high is very important, it is known that the occurrence of disasters associated with intense rains are a source of research in different locations around the globe, being important not only for increasing accuracy of weather forecasting models, but important information for civil defense, where lives can be saved. The increase in the occurrence of natural disasters related to extreme rainfalls has become a problem of large urban centers, such as the city of Rio de Janeiro (CRJ). Thus, the identi cation of homogeneous regions for rainfall distribution (HRRD) becomes essential to identify regions at risks of oods and mass movements. The aim of this research was to identify HRRD in CRJ associated to the risk of natural disasters. The identi cation of homogeneous regions was carried out with the use of monthly rainfall data from 14 pluviometric stations spatially distributed in the study area between 1997 and 2018.Rainfall data were submitted to descriptive statistical analysis, and subsequently to Cluster Analysis.Cluster analysis identi ed 4 homogeneous groups regarding annual rainfall distribution. The result showed relevance regarding physiographic aspects that characterize the rainfall dynamics in CRJ, highlighting areas favorable to the occurrence of natural disasters.

Understanding the occurrence of natural disasters in regions where the occurrence is high is very important, it is known that the occurrence of disasters associated with intense rains are a source of research in different locations around the globe, being important not only for increasing accuracy of weather forecasting models, but important information for civil defense, where lives can be saved. The increase in the occurrence of natural disasters related to extreme rainfalls has become a problem of large urban centers, such as the city of Rio de Janeiro (CRJ). Thus, the identification of homogeneous regions for rainfall distribution (HRRD) becomes essential to identify regions at risks of floods and mass movements. The aim of this research was to identify HRRD in CRJ associated to the risk of natural disasters. The identification of homogeneous regions was carried out with the use of monthly rainfall data from 14 pluviometric stations spatially distributed in the study area between 1997 and 2018. Rainfall data were submitted to descriptive statistical analysis, and subsequently to Cluster Analysis. Cluster analysis identified 4 homogeneous groups regarding annual rainfall distribution. The result showed relevance regarding physiographic aspects that characterize the rainfall dynamics in CRJ, highlighting areas favorable to the occurrence of natural disasters.