A long-term monthly surface water storage dataset for the Congo basin from 1992 to 2015

Abstract. The spatio-temporal variation of surface water storage (SWS) in the Congo River basin (CRB), the second largest watershed in the world, remains widely unknown. In this study, satellite-derived observations are combined to estimate SWS dynamics at the CRB and sub-basin scales over 1992–2015. Two methods are employed. The first one combines surface water extent (SWE) from the Global Inundation Extent from Multi-Satellite (GIEMS-2) dataset and the long-term satellite-derived surface water height from multi-mission radar altimetry. The second one, based on the hypsometric curve approach, combines SWE from GIEMS-2 with topographic data from four global Digital Elevation Models (DEMs), namely The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Observing Satellite (ALOS), Multi-Error-Removed Improved-Terrain (MERIT) and Forest And Buildings removed Copernicus DEM (FABDEM). The results provide SWS variations at monthly time step from 1992 to 2015 characterized by a strong seasonal and interannual variability with an annual mean amplitude of ~101 ± 23 km³. Middle-Congo sub-basin shows higher mean annual amplitude (~71 ± 15 km³). The comparison of SWS derived from the two methods and four DEMs shows an overall fair agreement. The SWS estimates are evaluated against satellite precipitation data and in situ river discharge and, in general, a relatively good agreement is found between the three hydrological variables at the basin and sub-basin scales (linear correlation coefficient > 0.5). We further characterize the spatial distribution of the major drought that occurred across the basin at the end of 2005 and early 2006. The SWS estimates clearly reveal the widespread spatial distribution of this severe event (less than 40 % of the mean maximum), in accordance with the large negative anomaly observed in precipitation over that period. This new SWS long-term dataset over the Congo basin is an unprecedented new source of information for improving our comprehension of hydrological and biogeochemical cycles in the basin. As the datasets used in our study are available globally, our study opens opportunities to further develop satellite-derived SWS estimates at the global scale. The dataset of the CRB’s SWS is available for download at https://doi.org/10.5281/zenodo.7299823 (kitambo et al., 2022b).