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Global and regional climate models (GCM and RCM respectively) are the current mathematical tools used to project alterations on precipitation regimes given different greenhouse gases emissions scenarios. However, these models have specific resolutions, physical equations and numerical approaches that provide a diverse set of performances across different regions and spatial–temporal scales. In South America, most hydrological impact studies have used the Eta RCM to yield precipitation projections without a proper uncertainty analysis. It is important to acknowledge its uncertainties prior to any hydrological assessment to adequately support climate change investigations and related water decision making. Therefore, we aim to investigate how Eta extreme precipitation biases vary in different spatial–temporal scales from a hydrological perspective. Thus, we evaluate the extreme precipitation generated by the Eta RCM driven by four different GCMs. It is investigated Eta biases across different temporal (3 hr–5 days) and spatial scales (0.2–1.0°) and how those errors affect river streamflow simulations. It is used local intensity–duration–frequency (IDF) curves and gridded precipitation datasets (MSWEP and ERA5‐Land) as references for Eta assessment. In general, Eta underestimates subdaily extreme precipitation across South America, regardless of the driven GCM. The median bias of a 10‐year return period daily precipitation is −36 mm (1st and 3rd quantiles −58 and −17 mm) compared to MSWEP and −26 mm (1st and 3rd quantiles −45 and −11 mm) compared to ERA5‐Land. However, the relative errors reduce with temporal and spatial aggregation. For example, the average bias of extreme precipitation decreases 8.4 and 5.4 percentage points from 1‐ to 5‐day duration compared to MSWEP and ERA5‐Land, respectively. The negative biases observed for precipitation (≈20%) are propagated to the flood discharges (≈40%), and these errors reduce with the drainage area. In general, there are greater biases in extreme discharges for small basins, but these errors considerably reduce for basins larger than 30,000 km2 compared to MGB‐MSWEP simulations. Compared to MGB‐ERA5‐Land simulations, MGB‐Eta presents relatively similar errors for basins of different sizes, probably due to the high negative bias for not only extreme but average precipitation as well. [ABSTRACT FROM AUTHOR]

The anomalous entrance of water into groundwater systems can affect storage throughout long periods and normally relies on infrequent and irregular pulses of groundwater recharge defined by the term episodic recharge. Recently there was a groundwater recharge of large magnitude with unknown circumstances in the Caiuá aquifer. This unique event was explored in detail here and allowed to better understand the occurrence of such events in humid subtropical climates in South America. For this study, groundwater monitoring daily data from the Integrated Groundwater Monitoring Network was used combined with a specific yield obtained from geophysical wireline logging to obtain groundwater recharge rates. To improve the investigation, we also used a baseflow separation method to obtain the groundwater contribution into local rivers. The groundwater storage variations were also assessed by remote sensing with the GRACE data. Results showed the importance of high soil moisture storage on the occurrence of large episodic recharge events. We estimated that the groundwater recharger volumes derived from 1 year that included the unique episodic recharge observed (total of 866 mm for April 2015–March 2016) were comparable with the sum of 7 years of groundwater recharge (total of 867 mm). Atypical rainfall in winter periods were responsible for the increase in soil moisture that explained that unique event. GRACE‐based GWS showed concordance detecting the occurrence of the unique episodic recharge. However, the variation in terms of volumes obtained by GRACE does not represent the behaviour observed in the aquifer by the WTF method. The results also indicated that changes in aquifer storage caused by episodic recharge events directly affect low flows in rivers over long periods. The main knowledge gap addressed here relates to exploring a unique episodic recharge event quite rare to observe with its long‐term impacts on hydroclimatic variability over a humid subtropical portion of the Caiuá aquifer. [ABSTRACT FROM AUTHOR]

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 105 m3 /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. [ABSTRACT FROM AUTHOR]

Abstract: 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 ( [ABSTRACT FROM AUTHOR]

The current benchmark approach for mathematical modelling of floodplain hydrologic regime consists of dynamically coupling one-dimensional (1D) and two-dimensional (2D) models for flow routing along the main channel and the floodplain, respectively. For large-scale sites, floodplain inundation may spread over hundreds of square kilometres and may last for many months and even influence seasonal floods in following years. This paper aims at evaluating the effect of vertical water balance representation on modelling a large-scale floodplain. The Pantanal wetland (140 000 km2; Brazil) is simulated using a 1D/2D coupled model approach, which also considers the representation of vertical water processes over the floodplain. Four scenarios are simulated: Baseline (the reference scenario), NoVertBal (in which the vertical water balance over floodplain is turned off) and ETp+1 and ETp−1 scenarios, characterized by artificially increasing or decreasing daily potential evapotranspiration (ETp) by 1 mm, respectively. The results showed that the effect of the vertical water processes scenarios on channel flow is directly dependent on the lateral exchange of water between the channel and floodplain in the upstream river reach. This influence is stronger when there is a gain of water from the floodplain to the channel. The inclusion of these vertical water processes into floodplain modelling was essential to represent the process of wetting and drying, this effect being more relevant for areas not directly connected to main channels, which is a characteristic of the Pantanal region. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Digital filters are useful tools for assessing the contribution of groundwater to total river flow. Several of those filters have been proposed in the last decades. One of the last contributions on this subject was given by Ekchardt (2005) who proposed a more general form of a digital baseflow filter and showed that some of the most used filters are special cases of this general form. This new filter has the inconvenience of having two parameters, one of them may be obtained directly from recession analysis, but the other (maximum baseflow index (BFImax)) is routinely estimated by a priori defined values according to the predominant geological characteristics of the drainage basin. In this short communication, we propose a method to estimate BFImax by a backwards filtering operation. The method was applied using data from 15 gauging stations in Brazil, with a varied range of groundwater contribution to streamflow. Results of the new estimation method for the BFImax parameter are coherent with the values which would be adopted by considering geological characteristics of the river basins. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, a hydrologic/hydrodynamic modeling of the Amazon River basin is presented using the MGB-IPH model with a validation using remotely sensed observations. Moreover, the sources of model errors by means of the validation and sensitivity tests are investigated, and the physical functioning of the Amazon basin is also explored. The MGB-IPH is a physically based model resolving all land hydrological processes and here using a full 1-D river hydrodynamic module with a simple floodplain storage model. River-floodplain geometry parameters were extracted from the SRTM digital elevation model, and the model was forced using satellite-derived rainfall from TRMM3B42. Model results agree with observed in situ daily river discharges and water levels and with three complementary satellite-based products: (1) water levels derived from ENVISAT altimetry data; (2) a global data set of monthly inundation extent; and (3) monthly terrestrial water storage (TWS) anomalies derived from the Gravity Recovery and Climate Experimental mission. However, the model is sensitive to precipitation forcing and river-floodplain parameters. Most of the errors occur in westerly regions, possibly due to the poor quality of TRMM 3B42 rainfall data set in these mountainous and/or poorly monitored areas. In addition, uncertainty in river-floodplain geometry causes errors in simulated water levels and inundation extent, suggesting the need for improvement of parameter estimation methods. Finally, analyses of Amazon hydrological processes demonstrate that surface waters govern most of the Amazon TWS changes (56%), followed by soil water (27%) and ground water (8%). Moreover, floodplains play a major role in stream flow routing, although backwater effects are also important to delay and attenuate flood waves. [ABSTRACT FROM AUTHOR]

A key aspect of large river basins partially neglected in large-scale hydrological models is river hydrodynamics. Large-scale hydrologic models normally simulate river hydrodynamics using simplified models that do not represent aspects such as backwater effects and flood inundation, key factors for some of the largest rivers of the world, such as the Amazon. In a previous paper, we have described a large-scale hydrodynamic approach resultant from an improvement of the MGB-IPH hydrological model. It uses full Saint Venant equations, a simple storage model for flood inundation and GIS-based algorithms to extract model parameters from digital elevation models. In the present paper, we evaluate this model in the Solimões River basin. Discharge results were validated using 18 stream gauges showing that the model is accurate. It represents the large delay and attenuation of flood waves in the Solimões basin, while simplified models, represented here by Muskingum Cunge, provide hydrographs are wrongly noisy and in advance. Validation against 35 stream gauges shows that the model is able to simulate observed water levels with accuracy, representing their amplitude of variation and timing. The model performs better in large rivers, and errors concentrate in small rivers possibly due to uncertainty in river geometry. The validation of flood extent results using remote sensing estimates also shows that the model accuracy is comparable to other flood inundation modelling studies. Results show that (i) river-floodplain water exchange and storage, and (ii) backwater effects play an important role for the Amazon River basin hydrodynamics. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The paper compares forecasts of mean monthly water levels up to six months ahead at Ladário, on the Upper Paraguay River, Brazil, estimated from two long-range dependence models. In one of them, the marked seasonal cycle was removed and a fractionally differenced model was fitted to the transformed series. In the other, a seasonal fractionally differenced model was fitted to water levels without transformation. Forecasts from both models for periods up to six months ahead were compared with forecasts given by simpler "short-range dependence" Box-Jenkins models, one fitted to the transformed series, the other a seasonal autoregressive moving average (ARMA) model. Estimates of parameters in the four models (two "long-range dependence", two "short-range dependence") were updated at six-monthly intervals over a 20 year period, and forecasts were compared using root mean square errors (rmse) between water-level forecasts and observed levels. As judged by rmse, performances of the two long-range dependence models, and of the ARMA (1,1) short-range dependence model, were very similar; all three out-performed the seasonal short-range dependence ARMA model. There was evidence that all models performed better during recession periods, than on the hydrograph rising limb. [ABSTRACT FROM AUTHOR]

This paper discusses issues arising when Tropical Rainfall Measuring Mission (TRMM) estimates of rainfall characteristics are calculated for the sparsely gauged Brazilian Amazon. The particular issue considered is the calculation of statistical uncertainty in (1) comparisons between TRMM estimates of rainfall characteristics and their corresponding rain gauge estimates and (2) interpolated estimates of rainfall characteristics, which are conditional on local TRMM estimates near ungauged sites. Three characteristics selected for particular comparison are (1) mean annual rainfall, 1998-2005, (2) mean value, over these years, of the 95% quantile of within-year daily rainfall, and (3) mean number of days in the year with rainfall of 2 mm or more. The paper demonstrates how positive spatial correlation leads to underestimation of the uncertainty in the comparisons (i.e., the standard errors of differences), so that the significance of differences, when observed, is likely to be overestimated if spatial correlation is ignored. For the three characteristics mentioned, the Matérn spatial correlation function with shape parameter = 1/2, giving an exponential correlation function, was found to be adequate for modeling spatial correlation. It is also argued that the statistic 1 − b, where b is the slope of the regression of a rain gauge estimate of a rainfall characteristic on its counterpart derived from satellite instrumentation, is a measure of the errors in the satellite (spatially averaged) estimates. Finally, although issues of spatial correlation are discussed with particular reference to rainfall, it is argued that the same issues arise whenever satellite-derived estimates of a component of the water cycle must be combined with ground-based measurements. [ABSTRACT FROM AUTHOR]

For large-scale sites, difficulties for applying coupled one-dimensional (1D)/2D models for simulating floodplain inundation may be encountered related to data scarcity, complexity for establishing channel-floodplain connections, computational cost, long duration of floods and the need to represent precipitation and evapotranspiration processes. This paper presents a hydrologic simulation system, named SIRIPLAN, developed to accomplish this aim. This system is composed by a 1D hydrodynamic model coupled to a 2D raster-based model, and by two modules to compute the vertical water balance over floodplain and the water exchanges between channel and floodplain. Results are presented for the Upper Paraguay River Basin (UPRB), including the Pantanal, one of the world's largest wetlands. A total of 3965 km of river channels and 140 000 km of floodplains are simulated for a period of 11 years. Comparison of observed and calculated hydrographs at 15 gauging stations showed that the model was capable to simulate distinct, complex flow regimes along main channels, including channel-floodplain interactions. The proposed system was also able to reproduce the Pantanal seasonal flood pulse, with estimated inundated areas ranging from 35 000 km (dry period) to more than 120 000 km (wet period). Floodplain inundation maps obtained with SIRIPLAN were consistent with previous knowledge of Pantanal dynamics, but comparison with inundation extent provided by a previous satellite-based study indicates that permanently flooded areas may have been underestimated. The results obtained are promising, and further work will focus on improving vertical processes representation over floodplains and analysing model sensitivity to floodplain parameters, time step and precipitation estimates uncertainty. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper presents an improved algorithm for deriving drainage networks for coarse-gridded distributed hydrological models based on relatively fine resolution digital elevation models. The proposed algorithm aims to reproduce actual drainage networks more closely when applied in regions with meandering rivers running in parallel and for cell sizes of the order of 10 kilometers. To achieve this goal, the COTAT algorithm of Reed (2003) was improved, introducing another parameter related to the minimum upstream flow path into the cell besides the area threshold. The proposed algorithm was tested by applying it to the catchments of the rivers Tapajos (530,000 km2) and Grande (145,000 km2) in South America. Results show that drainage networks are generally improved by the proposed algorithm, needing only minor manual corrections. [ABSTRACT FROM AUTHOR]

This paper describes a procedure for predicting seasonal flow in the Rio Uruguay drainage basin (area 75,000 km2, lying in Brazilian territory), using sequences of future daily rainfall given by the global climate model (GCM) of the Brazilian agency for climate prediction (Centro de Previsão de Tempo e Clima, or CPTEC). Sequences of future daily rainfall given by this model were used as input to a rainfall-runoff model appropriate for large drainage basins. Forecasts of flow in the Rio Uruguay were made for the period 1995-2001 of the full record, which began in 1940. Analysis showed that GCM forecasts underestimated rainfall over almost all the basin, particularly in winter, although interannual variability in regional rainfall was reproduced relatively well. A statistical procedure was used to correct for the underestimation of rainfall. When the corrected rainfall sequences were transformed to flow by the hydrologic model, forecasts of flow in the Rio Uruguay basin were better than forecasts based on historic mean or median flows by 37% for monthly flows and by 54% for 3-monthly flows. [ABSTRACT FROM AUTHOR]