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Stage‐discharge rating curves based on satellite altimetry and modeled discharge in the Amazon basin
Abstract
In this study, rating curves (RCs) were determined by applying satellite altimetry to a poorly gauged basin. This study demonstrates the synergistic application of remote sensing and watershed modeling to capture the dynamics and quantity of flow in the Amazon River Basin, respectively. Three major advancements for estimating basin‐scale patterns in river discharge are described. The first advancement is the preservation of the hydrological meanings of the parameters expressed by Manning's equation to obtain a data set containing the elevations of the river beds throughout the basin. The second advancement is the provision of parameter uncertainties and, therefore, the uncertainties in the rated discharge. The third advancement concerns estimating the discharge while considering backwater effects. We analyzed the Amazon Basin using nearly one thousand series that were obtained from ENVISAT and Jason‐2 altimetry for more than 100 tributaries. Discharge values and related uncertainties were obtained from the rain‐discharge MGB‐IPH model. We used a global optimization algorithm based on the Monte Carlo Markov Chain and Bayesian framework to determine the rating curves. The data were randomly allocated into 80% calibration and 20% validation subsets. A comparison with the validation samples produced a Nash‐Sutcliffe efficiency ( ) of 0.68. When the MGB discharge uncertainties were less than 5%, the value increased to 0.81 (mean). A comparison with the in situ discharge resulted in an value of 0.71 for the validation samples (and 0.77 for calibration). The values at the mouths of the rivers that experienced backwater effects significantly improved when the mean monthly slope was included in the RC. Our RCs were not mission‐dependent, and the value was preserved when applying ENVISAT rating curves to Jason‐2 altimetry at crossovers. The cease‐to‐flow parameter of our RCs provided a good proxy for determining river bed elevation. This proxy was validated against Acoustic Doppler current profiler (ADCP) cross sections with an accuracy of more than 90%. Altimetry measurements are routinely delivered within a few days, and this RC data set provides a simple and cost‐effective tool for predicting discharge throughout the basin in nearly real time.
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“In practice, prior discharge information from in situ networks28,42 or distributed calibrated hydrological and/or hydraulic models24–26,43–47 can be used to optimize robust stage-discharge rating curves with altimetric data.”
From Global scale river discharge and mean depth from radar altimetry and model (2026) · cites this paper as [26]
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“and has since been confirmed in various regional studies applying ARC methods with daily satellite altimetry and modeled discharge as inputs26,46,52.”
From Global scale river discharge and mean depth from radar altimetry and model (2026) · cites this paper as [26]
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“evidencing that the a and b coefficients of the ARC estimated at the global scale from monthly discharge reanalysis follow the findings made with different datasets and for varying types of rivers by refs. 26,64.”
From Global scale river discharge and mean depth from radar altimetry and model (2026) · cites this paper as [26]
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“The AHG coefficients generally follow a consistent linear trend along the river course as suggested by refs. 26,64.”
From Global scale river discharge and mean depth from radar altimetry and model (2026) · cites this paper as [26]
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“This makes it well-suited for Bayesian calibration of the low-dimensional parameter space (a, b, z0) while naturally enabling uncertainty quantification26.”
From Global scale river discharge and mean depth from radar altimetry and model (2026) · cites this paper as [26]
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Cited by
Global scale river discharge and mean depth from radar altimetry and model
Paris, A., Garambois, P.-A., Gal, L., Cerbelaud, A., Larnier, K., David, C. H., Jucá Oliveira, R. A., Correa, S. W., Tourian, M. J., & Calmant, S. (2026) · Nature Communications · doi:10.1038/s41467-026-78275-5
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Metadata
- Authors
- Paris, A., Dias de Paiva, R., Santos da Silva, J., Medeiros Moreira, D., Calmant, S., Garambois, P., Collischonn, W., Bonnet, M., & Seyler, F.
- Affiliations
- IPH/UFRGS, Avenida Bento Gonçalves Porto Alegre Rio Grande do Sul Brazil
- LMI OCE IRD/UNB Campus Darcy Ribeiro Brasilia Brazil
- LEGOS, Université de Toulouse, CNRS, CNES, IRD, UPS Toulouse France
- INSA Strasbourg, ICUBE–UMR7357, Fluid Mechanics Team Strasbourg France
- Venue
- Water Resources Research
- Publisher
- American Geophysical Union (AGU)
- Published
- 2016-05
- Volume
- 52
- Issue
- 5
- Pages
- 3787-3814
- ISSN
- 0043-1397
- 1944-7973
- Cited by
- 156
- References
- 0
- Language
- en
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