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It has been suggested that hydrograph skewness depends on the relative dominance between hillslope and channel network transport processes, where the former ones make the hydrograph positively skewed while the latter tends to make it negatively skewed. More recently, however, the role of river hydraulics in shaping the hydrograph has been highlighted. We present a set of numerical modeling experiments using a hydrodynamic model of river networks in which we investigate how channel hydraulics influence the shape of the hydrograph, particularly its skewness. We further investigate the influence of base flow, rainfall intensity, cross section geometry, and basin scale on unit hydrograph response. We show that river hydraulics has a decisive role because positively skewed hydrographs may occur even when water inputs to the river network are negatively skewed, and in catchments whose width function is also negatively skewed. We show additional results related to the effect of the degree of nonlinearity in the relationship between celerity and discharge, the effects of base flow and rainfall intensity. These further confirm that hydraulic factors may be decisive in determining hydrograph shape. Celerity‐discharge relationship at a cross section is an important driver of basin hydrograph skewnessPositive skewed form of hydrographs may be less related to hillslope processes and geomorphology as previously supposed and more to river hydraulicsBase flow discharge conditions prior to a rainfall event affect the hydrograph skewness associated with that event

Understanding hydrological processes occurring within a basin by looking at its outlet hydrograph can improve and foster comprehension of ungauged regions. In this context, we present an extensive examination of the roles that floodplains play on driving hydrograph shapes. Observations of many river hydrographs with large floodplain influence are carried out and indicate that a negative skewness of the hydrographs is present among many of them. Through a series of numerical experiments and analytical reasoning, we show how the relationship between flood wave celerity and discharge in such systems is responsible for determining the hydrograph shapes. The more water inundates the floodplains upstream of the observed point, the more negatively skewed is the observed hydrograph. A case study is performed in the Amazon River Basin, where major rivers with large floodplain attenuation (e.g., Purus, Madeira, and Juruá) are identified with higher negative skewness in the respective hydrographs. Finally, different wetland types could be distinguished by using this feature, e.g., wetlands maintained by endogenous processes, from wetlands governed by overbank flow (along river floodplains). A metric of hydrograph skewness was developed to quantify this effect, based on the time derivative of discharge. Together with the skewness concept, it may be used in other studies concerning the relevance of floodplain attenuation in large, ungauged rivers, where remote sensing data (e.g., satellite altimetry) can be very useful. River-floodplain interaction causes negative skewed hydrographsInverse relationship between flood wave celerity and discharge leads to negative skewnessPotential to characterize wetland types using river hydrograph shape

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 ( Ens) of 0.68. When the MGB discharge uncertainties were less than 5%, the Ensvalue increased to 0.81 (mean). A comparison with the in situ discharge resulted in an Ensvalue of 0.71 for the validation samples (and 0.77 for calibration). The Ensvalues 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 Ensvalue 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. Discharge can be obtained in near‐real‐time from altimetry and rating curveIncluding slope in rating curve allows adequate estimate of discharge in backwater conditionsRating curve parameters provide meaningful information on rivers characteristics

Recent developments in hydrological modelling of river basins are focused on prediction in ungauged basins, which implies the need to improve relationships between model parameters and easily-obtainable information, such as satellite images, and to test the transferability of model parameters. A large-scale distributed hydrological model is described, which has been used in several large river basins in Brazil. The model parameters are related to classes of physical characteristics, such as soil type, land use, geology and vegetation. The model uses two basin space units: square grids for flow direction along the basin and GRU—group response units—which are hydrological classes of the basin physical characteristics for water balance. Expected ranges of parameter values are associated with each of these classes during the model calibration. Results are presented of the model fitting in the Taquari-Antas River basin in Brazil (26 000 km2 and 11 flow gauges). Based on this fitting, the model was then applied to the Upper Uruguay River basin (52 000 km2), having similar physical conditions, without any further calibration, in order to test the transferability of the model. The results in the Uruguay basin were compared with recorded flow data and showed relatively small errors, although a tendency to underestimate mean flows was found.

This study presents an alternative model for hydrological tracking of surface waters designed to investigate multiyear storage and movement of water in large river basins. We coupled this model with a background solution from a large‐scale hydrological‐hydrodynamic model to study the fate of waters in the Amazon River basin (6 million km2) considering the following: (i) the surface water travel times, (ii) the role of large floodable areas (17% of the basin), and (iii) the relations between water composition and lithological sources. Through numerical experiments, we investigated the spatial distribution of in‐stream surface water travel time for the Amazon River Basin (relative to the outlet) and the role of floodplains in seasonal water storage. We estimate that surface water travel time is likely to be less than 90 days (median of 45 days), although about 20% of the flowing water passes through large floodplains. Our modeling exercises indicate that whole‐basin monthly water net balance between river and floodplain can reach up to magnitudes of 105m3/s; the water exchanged with floodplains during the annual floods can represent a large portion (up to 40%) of the basin discharge during low waters season. Finally, we took advantage of the tracking approach to study the hydrograph composition based on parent river lithology quantifying the role of major tributaries. Parallel to the development of global hydrology databases, new modeling approaches are also required to push advances in the discussion of renewal and travel times of surface waters in large river basins. Large‐scale water packet tracking simulation of the Amazon River BasinEstimates of surface water travel times in the Amazon River Basin (median of 45 days)Water composition based on temporal (seasonal and time travel content) and spatial features (source and floodplains)