Water balance in the amazon basin from a land surface model ensemble
Water balance in the amazon basin from a land surface model ensemble
Despite 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 3.26mmday-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.
Amazon region, Hydrologic models, Land surface model, Runoff
2586-2614
Getirana, Augusto C.V.
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Dutra, Emanuel
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Guimberteau, Matthieu
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Kam, Jonghun
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Li, Hong Yi
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Decharme, Bertrand
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Zhang, Zhengqiu
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Ducharne, Agnes
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Boone, Aaron
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Balsamo, Gianpaolo
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Rodell, Matthew
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Toure, Ally M.
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Xue, Yongkang
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Peters-Lidard, Christa D.
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Kumar, Sujay V.
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Arsenault, Kristi
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Drapeau, Guillaume
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Leung, L. Ruby
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Ronchail, Josyane
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Sheffield, Justin
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2014
Getirana, Augusto C.V.
bf7518cc-80a4-4441-9ced-ad0177643405
Dutra, Emanuel
7324810e-fd8c-4469-8f05-ed454254c3da
Guimberteau, Matthieu
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Kam, Jonghun
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Li, Hong Yi
6877457e-bf1a-4b93-9619-e66f3abb105c
Decharme, Bertrand
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Zhang, Zhengqiu
a7f2e402-2f87-40c5-9cc0-d67656bc9fde
Ducharne, Agnes
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Boone, Aaron
bdb9e6cb-430e-4da6-9b54-8338d8cabb1d
Balsamo, Gianpaolo
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Rodell, Matthew
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Toure, Ally M.
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Xue, Yongkang
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Peters-Lidard, Christa D.
ec52af50-c979-4df9-a8ee-0232a9d79878
Kumar, Sujay V.
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Arsenault, Kristi
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Drapeau, Guillaume
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Leung, L. Ruby
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Ronchail, Josyane
8db43b09-7d0b-4c73-8049-c2767bd3bd48
Sheffield, Justin
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Getirana, Augusto C.V., Dutra, Emanuel, Guimberteau, Matthieu, Kam, Jonghun, Li, Hong Yi, Decharme, Bertrand, Zhang, Zhengqiu, Ducharne, Agnes, Boone, Aaron, Balsamo, Gianpaolo, Rodell, Matthew, Toure, Ally M., Xue, Yongkang, Peters-Lidard, Christa D., Kumar, Sujay V., Arsenault, Kristi, Drapeau, Guillaume, Leung, L. Ruby, Ronchail, Josyane and Sheffield, Justin
(2014)
Water balance in the amazon basin from a land surface model ensemble.
Journal of Hydrometeorology, 15 (6), .
(doi:10.1175/JHM-D-14-0068.1).
Abstract
Despite 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 3.26mmday-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.
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Published date: 2014
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Publisher Copyright:
© 2014 American Meteorological Society.
Keywords:
Amazon region, Hydrologic models, Land surface model, Runoff
Identifiers
Local EPrints ID: 480792
URI: http://eprints.soton.ac.uk/id/eprint/480792
ISSN: 1525-755X
PURE UUID: 6b309901-66e0-431b-9f33-788b42756534
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Date deposited: 09 Aug 2023 17:14
Last modified: 17 Mar 2024 03:40
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Contributors
Author:
Augusto C.V. Getirana
Author:
Emanuel Dutra
Author:
Matthieu Guimberteau
Author:
Jonghun Kam
Author:
Hong Yi Li
Author:
Bertrand Decharme
Author:
Zhengqiu Zhang
Author:
Agnes Ducharne
Author:
Aaron Boone
Author:
Gianpaolo Balsamo
Author:
Matthew Rodell
Author:
Ally M. Toure
Author:
Yongkang Xue
Author:
Christa D. Peters-Lidard
Author:
Sujay V. Kumar
Author:
Kristi Arsenault
Author:
Guillaume Drapeau
Author:
L. Ruby Leung
Author:
Josyane Ronchail
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