In:
Earth System Science Data, Copernicus GmbH, Vol. 15, No. 7 ( 2023-07-12), p. 2957-2982
Abstract:
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 steps from 1992 to 2015 characterized by a strong
seasonal and interannual variability with an annual mean amplitude of
∼101±23 km3. The Middle Congo sub-basin shows a 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 assessed against satellite
precipitation data and in situ river discharge and, in general, a relatively
fair 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 in early 2006. The SWS
estimates clearly reveal the widespread spatial distribution of this severe
event (∼40 % deficit as compared to their long-term
average), in accordance with the large negative anomaly observed in
precipitation over that period. This new SWS long-term dataset over the
Congo River 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 and the related Python code to
run the reproducibility of the hypsometric curve approach dataset of SWS are
respectively available for download at https://doi.org/10.5281/zenodo.7299823 and https://doi.org/10.5281/zenodo.8011607 (Kitambo et al., 2022b, 2023).
Type of Medium:
Online Resource
ISSN:
1866-3516
DOI:
10.5194/essd-15-2957-2023
DOI:
10.5194/essd-15-2957-2023-supplement
Language:
English
Publisher:
Copernicus GmbH
Publication Date:
2023
detail.hit.zdb_id:
2475469-9
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