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Updated: Oct 8, 2025

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses
Published on: October 21, 2016
Modeling the spatial and temporal variability in surface water CO2 and CH4 concentrations in a newly created complex
Felipe Rust1, Pascal Bodmer1, Paul Del Giorgio1
1Groupe de Recherche Interuniversitaire en Limnologie, Département des Sciences Biologiques, Université du Québec à Montréal, Canada.
Abstract:
Hydroelectric reservoirs emit carbon dioxide (CO2) and methane (CH4) to the atmosphere, yet there is still much uncertainty concerning the magnitude and drivers of these greenhouse gas (GHG) emissions. This uncertainty is particularly large over the initial years after flooding and in complex, cascade reservoir systems where studies are rare. We assessed the spatial and temporal patterns of CO2 and CH4 concentrations in the newly created La Romaine complex, which is composed of three consecutive reservoirs (RO1, RO2, RO3) along the La Romaine River. Dissolved CO2 and CH4 concentrations were intensively measured over three seasons for four years. Results show elevated CH4 and especially CO2 concentrations in surface waters of all three reservoirs upon flooding, with strong seasonality and high spatial heterogeneity within reservoirs. There was a strong seasonal decoupling of surface water CO2 and CH4 concentrations. Contrary to expectations, surface water CO2 and CH4 concentrations were relatively stable over the initial years of flooding, with exception of the decrease in CO2 concentrations in the shallower RO1 reservoir. Further, individual reservoir characteristics, notably reservoir morphometry and pre-flood land cover, together with climatic factors were the main drivers of CO2 and CH4 concentrations, and the reservoir position in the cascade played a minor role. Models differed for CO2 and CH4, and also between reservoirs highlighting the need to capture these specificities in reservoir functioning. We establish a modeling framework to effectively fill the spatial and temporal gaps that inevitably exist in the sampling coverage of large and heterogeneous reservoirs, which combined with appropriately modeled gas transfer velocities, will serve as a platform to derive robust estimates of diffusive fluxes. This modeling framework can be transposed to other reservoirs, and will contribute to more accurate and representative estimates of diffusive carbon emissions from hydroelectric reservoirs.
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