Brazil hosts approximately 16% of the global freshwater and almost 50% of water resources in South America. However, the catchment-scale relationships between drivers and streamflow are still poorly understood. In this paper, the dominant hydrological processes for the Brazilian catchments were investigated. Additionally, were explored how these catchments can be categorized based on their hydrologic similarities, pointing the key climatic and landscape attributes influencing streamflow variability. There were used streamflow signatures and attributes of 735 catchments from the Catchment Attributes for Brazil (CABra) dataset along with machine learning techniques. The main results revealed six distinct similarity groups, primarily aligned with an aridity gradient ranging from the wettest to the driest. Climate emerged as the primary driver of hydrological behavior for the “dry” groups, highlighting the influence and importance of land-atmosphere interactions in Brazilian catchments. Conversely, catchments within the “wet” groups, characterized by high soil storage capacity and high precipitation, exhibit consistently high discharge levels throughout the year, primarily attributable to subsurface flux contributions. The findings obtained here may be useful to improve streamflow predictability by further understanding hydrological similarities and their signatures due to catchment landscape characteristics. Aside, this study may provide a significant step toward a unified global catchment-scale classification system, due to Brazil’s diverse hydroclimate and landscapes, the relatively easy and reproducible methodology, and clear metrics to weigh uncertainty.
