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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]

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]

• An algorithm for automated endmember selection was assessed in geeSEBAL. • A sensitivity analysis of the automated calibration was conducted. • New set of quantiles were proposed to increase E T accuracy in humid climates. • Impacts of global meteorology in geeSEBAL were also assessed. The application of energy balance models for estimation of evapotranspiration (E T) still has challenges to be addressed for large scale applications. The algorithm for automated calibration using inverse modeling at extreme conditions (CIMEC) is based on the definition of endmembers that represent the extreme conditions of the E T spectrum, between hot (dry and sparse vegetation) and cold (wet and dense vegetation) surfaces, with pre-defined quantiles for the endmember selection. The main goal was to assess geeSEBAL algorithm uncertainties related to the (i) automated calibration, including the use of additional filters (land cover, homogeneity, and domain area) and (ii) the use of a global climate grid as input data. Based on a sensitivity analysis, we defined new set of quantiles to increase the accuracy of E T estimates in subtropical humid climates, since the default quantiles were adjusted to semiarid climates with dry summers. To validate our E T estimates we used eddy covariance measurements from five flux towers located in the South of Brazil. Processing 132 Landsat cloud free images and using adjusted quantiles, we found a root mean square error (RMSE) of 0.91 mm d −1 and a coefficient of determination (R²) of 0.82 with geeSEBAL driven by meteorological measurements. Using the pre-defined quantiles, we found an RMSE of 1.16 mm d −1 (27% higher) and R² of 0.75. The upscaling instantaneous E T to daily E T resulted in an underestimation of the daily E T using the pre-defined quantiles, while the optimized quantiles corrected the daily estimates. Furthermore, our results suggested a low sensitivity of geeSEBAL to meteorological inputs, since RMSE slightly increased to 1.04 mm d −1 (14.3% higher) and R² decreased to 0.76 (8.5% smaller) when driven by global climate data. For data scarce areas, geeSEBAL is a feasible alternative for cropland E T estimation and water resources management in subtropical humid climates. [ABSTRACT FROM AUTHOR]