Key Points: Remote sensing validation of a hydrologic‐hydrodynamic model of the Amazon Uncertainty of precipitation and river‐floodplain parameters cause model errors Importance of floodplains and backwater effects on flood waves traveling
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.
To trace the origin of branched glycerol dialkyl glycerol tetraethers (brGDGTs), their distribution in soils and suspended particulate matter (SPM) of Amazonian rivers and floodplain lakes (várzeas) was studied. Differences in distribution between river SPM and surrounding (lowland) soils suggests an additional brGDGT source to eroded soils in the lowland drainage basin. Erosion of high Andean soils (above 2500 m in altitude) has no major influence because its brGDGT distribution differs substantially from that in river SPM. Furthermore, SPM in the Tapajós River, a tributary that does not derive from the Andes, has a virtually identical brGDGT distribution to that of the Amazon main stem. The higher proportion of phospholipid‐derived brGDGTs in river SPM compared to soils indicates that in situ production in the Amazon is an additional source for riverine brGDGTs. This affects the methylation and cyclization index of brGDGTs (MBT‐CBT), resulting in slightly lower MBT‐CBT‐derived temperatures and slightly higher CBT‐derived pH values, i.e., between the pH of the basin soil and that of the river. Since the difference between MBT‐CBT‐derived temperatures of Amazon River SPM and the surrounding soils is relatively small (2°C) compared to other aquatic systems (for lakes a difference of ∼ 10°C has been observed), it might still be possible to trace large climate changes in the Amazon basin with the MBT‐CBT using river fan cores. However, variations in in situ production of brGDGTs in the Amazon River over time and space have to be evaluated in the future. Likewise, in situ production may affect the application of the MBT‐CBT paleothermometer in other river systems. Our results also show that crenarchaeol is primarily produced in the Amazon River and that its varying production influences the branched vs. isoprenoid tetraether (BIT) index. This indicates that the BIT index not only represents the input of soil organic carbon to the river but is also affected by in situ production of brGDGTs and crenarchaeol.