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Water Balance in the Amazon Basin from a Land Surface Model EnsembleDespite recent advances in land surfacemodeling and remote sensing, estimates of the global water budget are still fairly uncertain. This study aims to evaluate the water budget of the Amazon basin based on several state-ofthe- art land surface model (LSM) outputs. Water budget variables (terrestrial water storage TWS, evapotranspiration ET, surface runoff R, and base flow B) are evaluated at the basin scale using both remote sensing and in situ data. Meteorological forcings at a 3-hourly time step and 18 spatial resolution were used to run 14 LSMs. Precipitation datasets that have been rescaled to matchmonthly Global Precipitation Climatology Project (GPCP) andGlobal Precipitation Climatology Centre (GPCC) datasets and the daily Hydrologie du Bassin de l'Amazone (HYBAM) dataset were used to perform three experiments. The Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme was forced with R and B and simulated discharges are compared against observations at 165 gauges. Simulated ET and TWS are compared against FLUXNET and MOD16A2 evapotranspiration datasets andGravity Recovery and ClimateExperiment (GRACE)TWSestimates in two subcatchments of main tributaries (Madeira and Negro Rivers).At the basin scale, simulated ET ranges from 2.39 to 3.26 mm day(exp -1) and a low spatial correlation between ET and precipitation indicates that evapotranspiration does not depend on water availability over most of the basin. Results also show that other simulated water budget components vary significantly as a function of both the LSM and precipitation dataset, but simulated TWS generally agrees with GRACE estimates at the basin scale. The best water budget simulations resulted from experiments using HYBAM, mostly explained by a denser rainfall gauge network and the rescaling at a finer temporal scale.
Document ID
20160008398
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Getirana, Augusto C. V.
(Maryland Univ. Greenbelt, MD, United States)
Dutra, Emanuel
(European Centre for Medium-Range Weather Forecasts Reading, United Kingdom)
Guimberteau, Matthieu
(Institut Pierre-Simon Laplace (IPSL) France)
Kam, Jonghun
(Princeton Univ. NJ, United States)
Li, Hong-Yi
(Pacific Northwest National Lab. Richland, WA, United States)
Decharme, Bertrand
(Centre National de Recherches Meteorologiques Toulouse, France)
Zhang, Zhengqiu
(California Univ. Los Angeles, CA, United States)
Ducharne, Agnes
(Institut Pierre-Simon Laplace (IPSL) France)
Boone, Aaron
(Centre National de Recherches Meteorologiques Toulouse, France)
Balsamo, Gianpaolo
(European Centre for Medium-Range Weather Forecasts Reading, United Kingdom)
Rodell, Matthew
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Toure, Ally M.
(Universities Space Research Association Greenbelt, MD, United States)
Xue, Yongkang
(California Univ. Los Angeles, CA, United States)
Peters-Lidard, Christa D.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Kumar, Sujay V.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Arsenault, Kristi
(Science Applications International Corp. Greenbelt, MD, United States)
Drapeau, Guillaume
(Universite Paris Diderot Paris, France)
Leung, L. Ruby
(Pacific Northwest National Lab. Richland, WA, United States)
Ronchail, Josyane
(Universite Paris Diderot Paris, France)
Sheffield, Justin
(Princeton Univ. NJ, United States)
Date Acquired
July 1, 2016
Publication Date
December 2, 2014
Publication Information
Publication: Journal of Hydrometeorology
Publisher: American Meteorological Society
Volume: 15
Issue: 6
ISSN: 1525-755X
e-ISSN: 1525-7541
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN33463
Funding Number(s)
CONTRACT_GRANT: NNG15HQ01C
CONTRACT_GRANT: NNX12AD03A
CONTRACT_GRANT: DE-AC05-76RLO1830
Distribution Limits
Public
Copyright
Other
Keywords
GPCP
Amason Basin
Negro Rivers

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