Stage-discharge rating curves based on satellite altimetry and modeled discharge in the Amazon basin

Adrien Paris 1, 2, 3 Rodrigo Dias de Paiva 2 Joecila Santos da Silva 4, 3, 5 Daniel Medeiros Moreira 1, 3, 6 Stéphane Calmant 1, 3 Pierre-André Garambois 7 Walter Collischonn 8, 3 Marie-Paule Bonnet 3, 9 F. Seyler 10, 3
1 LEGOS - Laboratoire d'études en Géophysique et océanographie spatiales
2 UFRGS - Universidade Federal do Rio Grande do Sul [Porto Alegre]
3 LMI-OCE - Laboratoire Mixte International Observatoire des Changements Environnementaux
4 LMTG - Laboratoire des Mécanismes et Transfert en Géologie
5 CESTUAv - Centro de Estudos do Tropico Umido
6 UFRJ - Universidade Federal do Rio de Janeiro
7 ICube - Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie
8 IPH - Instituto de Pesquisas Hidraulicas
9 GET - Géosciences Environnement Toulouse
10 UMR 228 Espace-Dev, Espace pour le développement
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 ( urn:x-wiley:00431397:media:wrcr22024:wrcr22024-math-0001) of 0.68. When the MGB discharge uncertainties were less than 5%, the urn:x-wiley:00431397:media:wrcr22024:wrcr22024-math-0002 value increased to 0.81 (mean). A comparison with the in situ discharge resulted in an urn:x-wiley:00431397:media:wrcr22024:wrcr22024-math-0003 value of 0.71 for the validation samples (and 0.77 for calibration). The urn:x-wiley:00431397:media:wrcr22024:wrcr22024-math-0004 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 urn:x-wiley:00431397:media:wrcr22024:wrcr22024-math-0005 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.
Keywords : optimization large basin model discharges altimetry Amazon rating curve
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Adrien Paris, Rodrigo Dias de Paiva, Joecila Santos da Silva, Daniel Medeiros Moreira, Stéphane Calmant, et al.. Stage-discharge rating curves based on satellite altimetry and modeled discharge in the Amazon basin. Water Resources Research, American Geophysical Union, 2016, 52 (5), pp.3787-3814. ⟨10.1002/2014WR016618⟩. ⟨hal-02136144⟩

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