Hydroelectric reservoirs generate energy without significant combustion of fossil fuels. However, these systems can, potentially, emit greenhouse gases (GHG's) at a rate which may be significant at the global scale, and, possible, co-equal, per kilowatt-hour, to that from conventional coal or oil-fired systems. Although much of the new construction of hydroelectric reservoirs is in the tropics, most of the data on GHG emissions comes from temperate regions. Further, much of the existing data on reservoir gas emissions comes from single sites, usually near the terminal dams. Large tropical reservoirs often involve the impoundments of river systems with complex morphology which in turn can cause spatial heterogeneity in gas flux. We evaluated spatial and seasonal variability in CO 2 concentrations and gas flux for five large (50-1,400 km 2 ) reservoirs in the Cerrado region of Brazil. Most of data set (87% of all measurements) showed CO 2 supersaturation and net efflux to the atmosphere. There was as much or more variation in pCO 2 over space and among seasons. The large studied reservoirs showed different zones in terms of CO 2 emission because those fluxes are dependent on flooded biomass, watershed input of organic matter and dam operation regime. Here we demonstrate that the reservoirs in the Brazilian Cerrado have low rates of CO 2 emissions compared to existing global comparisons. Our results suggest that ignoring the spatial variability can lead to more than 25% error in total system gas flux.

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Abstract. Abundant research has been devoted to understanding the complexity of the biogeochemical and physical processes that are responsible for greenhouse gas (GHG) emissions from hydropower reservoirs. These systems may have spatially complex and heterogeneous GHG emissions due to flooded biomass, river inflows, primary production and dam operation. In this study, we investigated the relationships between the water-air CO 2 fluxes and the phytoplanktonic biomass in the Funil Reservoir, which is an old, stratified tropical reservoir that exhibits intense phytoplankton blooms and a low partial pressure of CO 2 (pCO 2 ). Our results indicated that the seasonal and spatial variability of chlorophyll concentrations (Chl) and pCO 2 in the Funil Reservoir are related more to changes in the river inflow over the year than to environmental factors such as air temperature and solar radiation. Field data and hydrodynamic simulations revealed that river inflow contributes to increased heterogeneity during the dry season due to variations in the reservoir retention time and river temperature. Contradictory conclusions could be drawn if only temporal data collected near the dam were considered without spatial data to represent CO 2 fluxes throughout the reservoir. During periods of high retention, the average CO 2 fluxes were 10.3 mmol m −2 d −1 based on temporal data near the dam versus −7.2 mmol m −2 d −1 with spatial data from along the reservoir surface. In this case, the use of solely temporal data to calculate CO 2 fluxes results in the reservoir acting as a CO 2 source rather than a sink. This finding suggests that the lack of spatial data in reservoir C budget calculations can affect regional and global estimates. Our results support the idea that the Funil Reservoir is a dynamic system where the hydrodynamics represented by changes in the river inflow and retention time are potentially a more important force driving both the Chl and pCO 2 spatial variability than the in-system ecological factors.

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Tropical hydroelectric reservoirs generally constitute an appreciable source of CH4 (methane), a potent greenhouse gas. In this letter, we investigate the statistical characteristics of methane ebullition fluxes in hydroelectric reservoirs. To this end, we use CH4 flux measurements obtained in Manso (wet season, 2004) and Corumbá (dry and wet seasons, 2005) reservoirs, located respectively in Mato Grosso and Goiás, Brazil. Methane ebullition fluxes were measured using open dynamic chambers, connected to an infrared photo‐acoustic trace gas analyzer (TGA). Our main result indicates that when properly rescaled, all methane ebullition data collapse into a single statistic well described by a Generalized Pareto distribution, with shape parameter well above zero. The approach presented here, which combines high‐frequency CH4 ebullition data and Extreme Value theory analytical tools, shows that, although bubbling patterns appear to be highly complex and unpredictable, they may still be described by a rather simple (but non trivial) dynamics.

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