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Digital elevation models (DEMs) have a wide range of applications and play a crucial role in many studies. Numerous public DEMs, frequently acquired using radar and optical satellite imagery, are currently available; however, DEM datasets tend to exhibit elevation values influenced by vegetation height and coverage, compromising the accuracy of models in representing terrain elevation. In this study, we developed a digital terrain model for South America using a novel methodology to remove vegetation bias in the Copernicus DEM GLO-30 (COPDEM) model using machine learning, Global Ecosystem Dynamics Investigation (GEDI) elevation data, and multispectral remote sensing products. Our results indicate considerable improvements compared to COPDEM in representing terrain elevation, reducing average errors (BIAS) from 9.6 m to 1.5 m. Furthermore, we evaluated our product (ANADEM) by comparison with other global DEMs, obtaining more accurate results for different conditions of vegetation fraction cover and land use. As a publicly available and open-source dataset, ANADEM will play a crucial role in advancing studies that demand accurate terrain elevation representations at large scales. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a key process linking surface and atmospheric energy budgets, yet its drivers and patterns across wetlandscapes are poorly understood worldwide. Here we assess the ET dynamics in 12 wetland complexes across South America, revealing major differences under temperate, tropical, and equatorial climates. While net radiation is a dominant driver of ET seasonality in most environments, flooding also contributes strongly to ET in tropical and equatorial wetlands, especially in meeting the evaporative demand. Moreover, significant water losses through wetlands and ET differences between wetlands and uplands occur in temperate, more water-limited environments and in highly flooded areas such as the Pantanal, where slow river flood propagation drives the ET dynamics. Finally, floodplain forests produce the greatest ET in all environments except the Amazon River floodplains, where upland forests sustain high rates year round. Our findings highlight the unique hydrological functioning and ecosystem services provided by wetlands on a continental scale. Wetlands can affect regional climate by altering surface-atmosphere interactions. This paper investigates drivers and patterns of evapotranspiration in South American wetlands, from the Amazon floodplains to the large Pantanal system. [ABSTRACT FROM AUTHOR]

Streamflow forecasts from continental to global scale hydrological models have gained attention, but their performance against operational forecasts at local to regional scales must be evaluated. This study assesses the skill of medium-range, weekly streamflow forecasts for 147 large Brazilian hydropower plants (HPPs) and compares their performance with forecasts issued operationally by the National Electric System Operator (ONS). A continental-scale hydrological model was forced with ECMWF medium-range forecasts, and outputs were corrected using quantile mapping (QM) and autoregressive model approaches. By using both corrections, the percentage of HPPs with skillful forecasts against climatology and persistence for 1–7 days ahead increased substantially for low to moderate (9% to 56%) and high (72% to 94%) flows, while using only the QM correction allowed positive skill mainly for low to moderate flows and for 8–15 days ahead (29% to 64%). Compared with the ONS, the corrected continental-scale forecasts issued for the first week exhibited equal or better performance in 60% of the HPPs, especially for the North and Southeast subsystems, the DJF and MAM months, and for HPPs with less installed capacity. The findings suggest that using simple corrections on streamflow forecasts issued by continental-scale models can result in competitive forecasts even for regional-scale applications. [ABSTRACT FROM AUTHOR]

In this work, the role of initial conditions (ICs) and boundary conditions (BCs) in the predictability of natural flows of large river basins (>1000 km2) in South America using the South American Large Basins Model (MGB-SA) was investigated. We proposed an analysis based on a simple metric: predictability was estimated by the number of days in which the streamflow forecasts performed above a given threshold. The role of ICs was assessed through null precipitation experiments and the role of BCs through climatological rainfall. For experiments with a Kling-Gupta efficiency metric and threshold of 0.95, the study shows that streamflow predictability from the ICs is relatively high (up to 40 days) in the main river reaches of flat-relief basins. The increase in predictability due to climatology-based BCs mostly occurs in areas with high predictability based on ICs. Basins with fast response present low streamflow predictability (up to three days). [ABSTRACT FROM AUTHOR]

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]

Defining river networks from a digital elevation model (DEM) is a critical step in many hydrological studies. Most methods rely on analyses of flow accumulation based on a single drainage area threshold value. Landscape heterogeneity hinders the definition of drainage pixels by exceeding a threshold. In this study, we propose a method that automatically accounts for variable drainage density in the definition of river networks from relatively coarse DEMs by using the topographic position index (TPI) as an auxiliary variable, therefore calling it the Topographic Position-based Stream definition (TPS). We tested the TPS method with the 90 m resolution MERIT-DEM (Multi-Error-Removed Improved-Terrain DEM) in Brazil, applying it to three river basins with contrasting landforms and climates. The method improved drainage representation in all analysed regions. It successfully represented stream networks with intra-basin variable drainage density by using a single DEM and three parameters, showing potential for hydrological applications at multiple spatial scales. [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]

This study provides a spatio-temporal analysis of the great floods that occurred in South America in 1983 using hydrometeorological data and outputs from a continental-scale hydrological-hydrodynamic model. In the extreme year 1983, there were three main flooding periods (February, June and July) in many South American river basins, such as the Araguaia, Tocantins, São Francisco, Uruguay, La Plata and its tributaries, resulting in high discharge of the Paraguay River for many months. Depth–area–duration curves show that 3-day precipitation events in northern regions of South America were among the largest 15 events in the period 1980–2015 but only for specific locations, whereas in southern areas, the most extreme events in the same period were for larger durations (≥7-day precipitation). Modelled total export of water volume to the oceans indicates that rivers draining to the South Atlantic reached an anomaly of 3.7 during 1983, followed by 1998 (1.9) and 1992 (1.1), all of them corresponding to El Niño years. [ABSTRACT FROM AUTHOR]

Large-scale hydrologic–hydrodynamic models are powerful tools for integrated water resources evaluation at the basin scale, especially in the context of flood hazard assessment. However, recent model developments have paid little attention to simulate reservoirs' hydrodynamics within river networks. This study presents an adaptation of the MGB model to simulate reservoirs as an internal boundary condition, enabling the explicit simulation of hydrodynamic processes along reservoirs and their interaction with upstream and downstream floodplains in large basins. A case study is carried out in the Itajaí-Açu River Basin in Brazil, which has periodic flood-related disasters and three flood control dams. The model was calibrated for the 1950–2016 period forced with daily observed precipitation. The adjustment was satisfactory, with Nash–Sutcliffe metrics between 0.54 and 0.84 for the 11 gauges analyzed and with flood frequency curves also well represented. Simulation scenarios with and without floodplains and reservoirs were performed to evaluate the relative role of these factors on flood control basin-wide through evaluation of simulated discharges, water levels and flood extent. Itajaí do Oeste tributary and Itajaí-Açu mainstem present major floodplain attenuation, while in Itajaí do Sul and Itajaí do Norte tributaries the main flood control occurs due to reservoir attenuation. Downstream from the dams, results indicated that the reservoirs reach their maximum discharge reduction capacity for 5- to 10-year floods, decreasing it for larger floods. The developed model may be very useful for operational uses as flood forecasting and coordinated reservoir operation studies, as well as to enhance the comprehension of flood dynamics at basin scale. [ABSTRACT FROM AUTHOR]

It has been proposed that linear regression curves can be used to estimate monthly climate variables from observed precipitation. This approach was explored by applying the MGB hydrological model to the Paraná Basin (Brazil). Linear regressions were obtained for 54 climate gauges, and most of them showed at least six months of significant correlation between monthly climate variables (sunlight hours and relative humidity) and precipitation. The regression equations were applied to 5201 raingauges to estimate monthly climate variables and evapotranspiration, and the results were compared with a scenario using long-term climate averages only. The main differences occurred in wetter periods, where negative correlations between monthly precipitation and evapotranspiration were obtained when using precipitation as a proxy. Long-term changes in the hydrological regime were assessed and showed that the effect of precipitation on relative humidity and sunlight hours seems to have a minor effect on the alterations observed in river discharge in the Paraná Basin. [ABSTRACT FROM AUTHOR]

An accurate comprehension of celerity (flood wave speed) dynamics is a key step for understanding flood wave propagation in rivers. We present the results of empirically estimated celerity values in 12 Brazilian rivers, and analyse the behaviour of celerity-discharge relationships (CxQ). Celerity was estimated with a reach-scale (RS) method, based on the peak travel time between stations; and with a local-scale (LS) method, based on the derivative of discharge-cross-section area relationships surveyed at gauging stations. The results indicate that the magnitudes of celerity values obtained by the methods are reasonably comparable, and can rarely be considered constant, varying with river discharge. Three reaches presented differing CxQ relationships at local and reach scales, which suggests that in situ cross-sections at gauging stations should not be extrapolated as representative of the whole reach for flood routing studies, and that CxQ relationship assessments might provide relevant insights for hydrological modelling. [ABSTRACT FROM AUTHOR]

Providing reliable estimates of streamflow and hydrological fluxes is a major challenge for water resources management over national and transnational basins in South America. Global hydrological models and land surface models are a possible solution to simulate the terrestrial water cycle at the continental scale, but issues about parameterization and limitations in representing lowland river systems can place constraints on these models to meet local needs. In an attempt to overcome such limitations, we extended a regional, fully coupled hydrologic-hydrodynamic model (MGB; Modelo hidrológico de Grandes Bacias) to the continental domain of South America and assessed its performance using daily river discharge, water levels from independent sources (in situ, satellite altimetry), estimates of terrestrial water storage (TWS) and evapotranspiration (ET) from remote sensing and other available global datasets. In addition, river discharge was compared with outputs from global models acquired through the eartH2Observe project (HTESSEL/CaMa-Flood, LISFLOOD and WaterGAP3), providing the first cross-scale assessment (regional/continental×global models) that makes use of spatially distributed, daily discharge data. A satisfactory representation of discharge and water levels was obtained (Nash-Sutcliffe efficiency, NSE > 0.6 in 55% of the cases) and the continental model was able to capture patterns of seasonality and magnitude of TWS and ET, especially over the largest basins of South America. After the comparison with global models, we found that it is possible to obtain considerable improvement on daily river discharge, even by using current global forcing data, just by combining parameterization and better routing physics based on regional experience. Issues about the potential sources of errors related to both global- and continental-scale modeling are discussed, as well as future directions for improving large-scale model applications in this continent. We hope that our study provides important insights to reduce the gap between global and regional hydrological modeling communities. [ABSTRACT FROM AUTHOR]

Providing reliable estimates of streamflow and hydrological fluxes is a major challenge for water resources management over national and transnational basins in South America. Global hydrological models and land surface models are a possible solution to simulate the terrestrial water cycle at the continental scale, but issues on parameterization and limitations in representing lowland river systems put into question their utility for basin-scale analysis and to deliver daily discharges to meet local needs. In an attempt to overcome such limitations, we extended a regional, fully coupled hydrologic–hydrodynamic model (MGB) to the continental domain of South America and assessed its performance using daily river discharges, water levels from independent sources (in situ, satellite altimetry), estimates of terrestrial water storage (TWS) and evapotranspiration (ET) from remote sensing and other available global datasets. In addition, river discharges were compared with outputs from global models acquired through the eartH2Observe project (HTESSEL/CaMa-Flood, LISFLOOD and WaterGAP3), providing the first cross-scale assessment (regional/continental × global models) that makes use of spatially consistent daily discharge data. A satisfactory representation of discharges and water levels was obtained (NSE > 0.6 in 55 % of the cases) and MGB was able to capture patterns of seasonality and magnitude of TWS and ET especially over the largest basins of South America. Continental-scale modeling significantly improved discharge estimates when compared with global models, which resulted in a large number of gauges with negative (or close to 0) NSE values. Models were largely affected by positive bias mainly over East/Northeast Brazil and Argentina as well as over regions of Sao Francisco and Parnaiba basins, while major issues on flow timing were observed in regions affected by floodplain processes such as the Amazon, La Plata, Tocantins–Araguaia, Orinoco and Magdalena basins. We state that efforts in calibrating rainfall-runoff parameters within large basins are necessary to simulate daily river discharges appropriately in this continent, but implementing a hydrodynamic routing component is also important. We hope that our study provides further insights about hydrological simulation in South America, helping to reduce the gap between global and regional hydrological modeling communities. [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]

Hydropower is the most important source of electricity in Brazil. It is subject to the natural variability of water yield. One building block of the proper management of hydropower assets is the short-term forecast of reservoir inflows as input for an online, event-based optimization of its release strategy. While deterministic forecasts and optimization schemes are the established techniques for short-term reservoir management, the use of probabilistic ensemble forecasts and multi-stage stochastic optimization techniques is receiving growing attention. The present work introduces a novel, mass conservative scenario tree reduction in combination with a detailed hindcasting and closed-loop control experiments for a multi-purpose hydropower reservoir in a tropical region in Brazil. The case study is the hydropower project Três Marias, which is operated with two main objectives: (i) hydroelectricity generation and (ii) flood control downstream. In the experiments, precipitation forecasts based on observed data, deterministic and probabilistic forecasts are used to generate streamflow forecasts in a hydrological model over a period of 2 years. Results for a perfect forecast show the potential benefit of the online optimization and indicate a desired forecast lead time of 30 days. In comparison, the use of actual forecasts of up to 15 days shows the practical benefit of operational forecasts, where stochastic optimization (15 days lead time) outperforms the deterministic version (10 days lead time) significantly. The range of the energy production rate between the different approaches is relatively small, between 78% and 80%, suggesting that the use of stochastic optimization combined with ensemble forecasts leads to a significantly higher level of flood protection without compromising the energy production. [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]

We present an assessment of climate change impacts on the hydrologic regime of the 600,000 km Upper Paraguay River basin, located in central South America based on predictions of 20 Atmospheric/Ocean General Circulation Models (AOGCMs). We considered two climate change scenarios from the Intergovernmental Panel on Climate Change (IPCC) and two 30-years time intervals centered at 2030 and 2070. Projected temperature and precipitation anomalies estimated by the AOGCMs for the study site are spatially downscaled. Time series of projected temperature and precipitation were estimated using the delta change approach. These time series were used as input to a detailed coupled hydrologic-hydraulic model aiming to estimate projected streamflow in climate change scenarios at several control points in the basin. Results show that impacts on streamflow are highly dependent on the AOGCM used to obtain the climate predictions. Patterns of temperature increase persist over the entire year for almost all AOGCMs resulting in an increase in the evapotranspiration rate of the hydrological model. The precipitation anomalies show large dispersion, being projected as either an increase or decrease in precipitation rates. Based on these inputs, results from the coupled hydrologic-hydraulic model show nearly one half of projections as increasing river discharge, and other half as decreasing river discharge. If the mean or median of the predictions is considered, no discernible change in river discharge should be expected, despite the dispersion among results of the AOGCMs that reached +/−10 % in the short horizon and +/− 20 % in the long horizon, at several control points. [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]

In planning routes for roads and canals, topography is often a significant constraint. Among the infinite number of possible trajectories between two points, the selected path should be a good approximation to the one with the least cost, and should avoid extremes of slopes. In the case of a canal, the number of uphill reaches of the trajectory should be minimised. This paper presents a least-cost-path algorithm developed to find the best path given the topography, the start and end-points of the linear feature (canal or road) and a function relating slope, distance and cost. The algorithm is based on dynamic programming techniques adapted to solve problems on the grid, or raster structure usually used in Geographical Information Systems. The algorithm was programmed and used to solve hypothetical problems. Although real cost functions were not used, the results were coherent and showed the algorithm's capabilities. [ABSTRACT FROM AUTHOR]

Hydrological models are useful tools for water resources studies, yet their calibration is still a challenge, especially if aiming at improved estimates of multiple components of the water cycle. This has led the hydrologic community to look for ways to constrain models with multiple variables. Remote sensing estimates of soil moisture are very promising in this sense, especially in large areas for which field observations may be unevenly distributed. However, the use of such data to calibrate hydrological models in a synergistic way is still not well understood, especially in tropical humid areas such as those found in South America. Here, we perform multiple scenarios of multiobjective model optimization with in situ discharge and the SMOS L4 root zone soil moisture product for the Upper Paraná River Basin in South America (drainage area > 900,000 km²), for which discharge data for 136 river gauges are used. An additional scenario is used to compare the relative impacts of using all river gauges and a small subset containing nine gauges only. Across the basin, the joint calibration (CAL-DS) using discharge and soil moisture leads to improved precision and accuracy for both variables. The discharges estimated by CAL-DS (median KGE improvement for discharge was 0.14) are as accurate as those obtained with the calibration with discharge only (median equal to 0.14), while the CAL-DS soil moisture retrieval is practically as accurate (median KGE improvement for soil moisture was 0.11) as that estimated using the calibration with soil moisture only (median equal to 0.13). Nonetheless, the individual calibration with discharge rates is not able to retrieve satisfactory soil moisture estimates, and vice versa. These results show the complementarity between these two variables in the model calibration and highlight the benefits of considering multiple variables in the calibration framework. It is also shown that, by considering only nine gauges instead of 136 in the model optimization, the model is able to estimate reasonable discharge and soil moisture, although relatively less accurately and with less precision than for the entire dataset. In summary, this study shows that, for poorly gauged tropical basins, the joint calibration of SMOS soil moisture and a few in situ discharge gauges is capable of providing reasonable discharge and soil moisture estimates basin-wide and is more preferable than performing only a discharge-oriented optimization process. [ABSTRACT FROM AUTHOR]

One of the main causes of water conflicts in transboundary watersheds all over the world is represented by the increasing water demand due to urban, industrial, and agricultural development. In this context, water scarcity plays a critical role since, during a drought period, water supply is not sufficient to cover the demand of all water uses. In this work, we have conceptualized and developed a new scenario-based framework able to improve the sustainability and equity of water allocation among two or more riparian countries. The proposed approach is in accordance with the United Nations Watercourses Convention. It considers a hydraulic/hydrologic model, a water-management model, and combines them with multi-criteria decision analysis (MCDA) and what if scenario analysis (WISA). The suggested framework was applied to the transboundary watershed of Cuareim/Quaraí river (Uruguay/Brazil) to tackle a real water-sharing conflict. It resulted in being very flexible in exploring various policy options and test and quantifying them with different scenarios to reach an objective and impartial decision in a water-sharing issue. This framework can effectively be applied to any other transboundary watershed to resolve any possible conflict related to water-allocation/water-management matter. [ABSTRACT FROM AUTHOR]