In the Congo Basin, the elevated vulnerability of the food security and water supply implicates that the sustainable development strategies must take into account the climate change impacts. However, there are only a limited number of studies focusing on climate change impacts for the Congo basin, mainly due to the lack of observational climate and hydrological data. Recent improvements in remote sensing technology provide more data than ever before to support hydrological studies in tropical regions. In this work, 130 time series of water level in major rivers of the Congo basin are extracted using ENVISAT altimetry over the period 2002-2010. This dataset offers an unprecedented distributed view of the spatio-temporal variations of river stage throughout the basin. In order to provide valuable indications to improve the understanding of the dominant physical phenomena in the Congo Basin, we performed a K-Means cluster analysis of the altimeter-derived river level height variations to identify groups of hydrologically similar catchments. Each group is represented through a parsimonious set of morphometric (location, elevation and distance to the mouth) and hydrologic variables (amplitude), including also indexes that attempt to synthesize the variability (dates of low and high stages) and correlation properties (lag-1, Hurst exponent). This analysis revealed nine distinct regions. For each region the seasonal and interannual variabilities of the mean river level are discussed and compared to the TRMM rainfall data and to ordinary climate indices such as MEI, TNA, TSA and IOD. This analysis allowed us to identify the most sensitive subregions to climate change of the Congo Basin.