@article{fdi:010088254,
  title = {{A} copula-supported {B}ayesian framework for spatial downscaling of {GRACE}-derived terrestrial water storage flux},
  author = {{T}ourian, {M}. {J}. and {S}aemian, {P}. and {F}erreira, {V}. {G}. and {S}neeuw, {N}. and {F}rappart, {F}. and {P}apa, {F}abrice},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he {GRACE} and {GRACE}-{FO} satellite missions provide mass variations as a fundamentally new observation type for a broad spectrum of novel applications in {E}arth science disciplines, including oceanography, geophysics, hydrology, and hydrometeorology. {D}espite all the key findings in hydrology, the utility of {GRACE}-derived {T}errestrial {W}ater {S}torage {A}nomaly ({TWSA}) and its time derivative {T}errestrial {W}ater {S}torage {F}lux ({TWSF}) have mainly been limited to large catchments due to their coarse spatial resolution. {H}ere, we propose a method to downscale {TWSF} by incorporating available finer-resolution data. {W}e determine the downscaled {TWSF} and its uncertainty within a proposed {B}ayesian framework by incorporating the fine-scale data of {TWSF} and {S}oil {M}oisture {C}hange ({SMC}) from different available sources. {F}or the {B}ayesian ingredients, we rely on {GRACE} data to obtain the prior and rely on copula models to obtain nonparametric likelihood functions based on the statistical relationship between {GRACE} {TWSF} with fine-scale {TWSF} data and {SMC}. {W}e apply our method to the {A}mazon {B}asin and assess the performances of our products from various fine-scale input datasets of {TWSF}s and {SMC}s. {G}iven the lack of ground truth for {TWSF}, we validate our results against space-based {S}urface {W}ater {S}torage {C}hange ({SWSC}) in the {A}mazon river system and also against the {V}ertical {C}rustal {D}isplacements {R}ate ({VCDR}) observed by the {G}lobal {P}ositioning {S}ystem ({GPS}). {O}verall, the results show that the proposed method is able to estimate a downscaled {TWSF}, which is informed by {GRACE} and fine-scale data. {V}alidation shows that our downscaled products are better anticorrelated with {VCDR} (-0.81) than fine-scale {TWSF} (-0.73) and show a mean relative {RMSE} of 26% with {SWSC} versus 70% for fine-scale {TWSF}. {T}he proposed methodology can be extended to other coarse scale datasets, which are crucial for hydrological application at regional and local scales.},
  keywords = {{C}opula ; {B}ayesian framework ; {D}ownscaling ; {GRACE} ; {T}errestrial water ; storage flux ; {BRESIL} ; {AMAZONE} {BASSIN}},
  booktitle = {},
  journal = {{R}emote {S}ensing of {E}nvironment},
  volume = {295},
  numero = {},
  pages = {113685 [21 ]},
  ISSN = {0034-4257},
  year = {2023},
  DOI = {10.1016/j.rse.2023.113685},
  URL = {https://www.documentation.ird.fr/hor/fdi:010088254},
}