@article{fdi:010090001,
  title = {{A} long-term monthly surface water storage dataset for the {C}ongo basin from 1992 to 2015},
  author = {{K}itambo, {B}. {M}. and {P}apa, {F}abrice and {P}aris, {A}. and {T}shimanga, {R}. {M}. and {F}rappart, {F}. and {C}almant, {S}t{\'e}phane and {E}lmi, {O}. and {F}leischmann, {A}. {S}. and {B}ecker, {M}. and {T}ourian, {M}. {J}. and {O}liveira, {R}. {A}. {J}. and {W}ongchuig, {S}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he spatio-temporal variation of surface water storage ({SWS}) in the {C}ongo {R}iver basin ({CRB}), the second-largest watershed in the world, remains widely unknown. {I}n this study, satellite-derived observations are combined to estimate {SWS} dynamics at the {CRB} and sub-basin scales over 1992-2015. {T}wo methods are employed. {T}he first one combines surface water extent ({SWE}) from the {G}lobal {I}nundation {E}xtent from {M}ulti{S}atellite ({GIEMS}-2) dataset and the long-term satellite-derived surface water height from multi-mission radar altimetry. {T}he second one, based on the hypsometric curve approach, combines {SWE} from {GIEMS}-2 with topographic data from four global digital elevation models ({DEM}s), namely the {T}erra {A}dvanced {S}paceborne {T}hermal {E}mission and {R}eflection {R}adiometer ({ASTER}), {A}dvanced {L}and {O}bserving {S}atellite ({ALOS}), {M}ulti{E}rror-{R}emoved {I}mproved {T}errain ({MERIT}), and {F}orest {A}nd {B}uildings removed {C}opernicus {DEM} ({FABDEM}). {T}he 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 similar to 101 +/- 23 km(3). {T}he {M}iddle {C}ongo sub-basin shows a higher mean annual amplitude ( similar to 71 +/- 15 km(3)). {T}he comparison of {SWS} derived from the two methods and four {DEM}s shows an overall fair agreement. {T}he {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). {W}e further characterize the spatial distribution of the major drought that occurred across the basin at the end of 2005 and in early 2006. {T}he {SWS} estimates clearly reveal the widespread spatial distribution of this severe event ( similar to 40% deficit as compared to their long-term average), in accordance with the large negative anomaly observed in precipitation over that period. {T}his new {SWS} long-term dataset over the {C}ongo {R}iver basin is an unprecedented new source of information for improving our comprehension of hydrological and biogeochemical cycles in the basin. {A}s the datasets used in our study are available globally, our study opens opportunities to further develop satellitederived {SWS} estimates at the global scale. {T}he dataset of the {CRB}'s {SWS} and the related {P}ython 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 ({K}itambo et al., 2022b, 2023).},
  keywords = {{CONGO} {CUVETTE} ; {CONGO} {COURS} {D}'{EAU}},
  booktitle = {},
  journal = {{E}arth {S}ystem {S}cience {D}ata},
  volume = {15},
  numero = {7},
  pages = {2957--2982},
  ISSN = {1866-3508},
  year = {2023},
  DOI = {10.5194/essd-15-2957-2023},
  URL = {https://www.documentation.ird.fr/hor/fdi:010090001},
}