The contribution of artificial reservoirs to greenhouse gas (GHG) emissions has been emphasized in previous studies. In the present study, we collected and updated data on GHG emission rates from reservoirs at the global scale, and applied a new classification method based on the hydrobelt concept. Our results showed that CH₄ and CO₂ emissions were significantly different in the hydrobelt groups (p < 0.01), while no significant difference was found for N₂O emissions, possibly due to their limited measurements. We found that annual GHG emissions (calculated as C or N) from global reservoirs amounted to 12.9 Tg CH₄-C, 50.8 Tg CO₂-C, and 0.04 Tg N₂O-N. Furthermore, GHG emissions (calculated as CO₂ equivalents) were also estimated for the 1950–2017 period based on the cumulative number and surface area of global reservoirs in the different hydrobelts. The highest increase rate in both the number of reservoirs and their surface area, which occurred from 1950 to the 1980s, led to an increase in GHG emissions from reservoirs. Since then, the increase rate of reservoir construction, and hence GHG emissions, has slowed down. Moreover, we also examined the potential impact of reservoir eutrophication on GHG emissions and found that GHG emissions from reservoirs could increase by 40% under conditions in which total phosphorus would double. In addition, we showed that the characteristics of reservoirs (e.g., geographical location) and their catchments (e.g., surrounding terrestrial net primary production, and precipitation) may influence GHG emissions. Overall, a major finding of our study was to provide an estimate of the impact of large reservoirs during the 1950–2017 period, in terms of GHG emissions. This should help anticipate future GHG emissions from reservoirs considering all reservoirs being planned worldwide. Besides using the classification per hydrobelt and thus reconnecting reservoirs to their watersheds, our study further emphasized the efforts to be made regarding the measurement of GHG emissions in some hydrobelts and in considering the growing number of reservoirs.

Reservoirs are active reactors for the biogeochemical cycling of carbon (C) and nutrients (nitrogen: N, phosphorus: P, and silica: Si), however, our in-depth understanding of C and nutrient cycling in reservoirs is still limited by the fact that it involves a variety of closely linked and coupled biogeochemical and hydrological processes. In this study, the updated process-based Barman model was applied to three reservoirs of the Seine Basin during 2019-2020, considering the variations of carbon dioxide (CO₂) concentrations and key water quality variables. The model simulations captured well the observed seasonal variations of water quality variables, although discrepancies remained for some variables. According to the model, we found that: (1) the three reservoirs are autotrophic ecosystems and showed high removal efficiency of dissolved inorganic carbon and nutrients during 2019-2020; (2) phytoplankton assimilation, benthic denitrification, precipitation and dissolution of calcium carbonate, and gas exchange at the water-air interface are the dominant processes for water quality variations in reservoirs; (3) based on scenarios results, trophic state and mean water depth of reservoir would impact the biogeochemical processes and the retention efficiency of nitrate and dissolved silicate. Finally, we expect that the successful application of Barman model in the reservoirs of the Seine Basin could provide a useful tool for simulating reservoir water quality changes and thus evaluating the impacts of reservoirs on downstream water quality.

The impact of reservoirs on downstream water quality has received widespread attention, but most current studies are based on short-term data only, and less attention has been paid to the impact of reservoirs on downstream carbon dioxide (CO2) concentrations. In the present study, we assessed the nutrient budgets (DIN: dissolved inorganic nitrogen, PO43-: orthophosphate, DSi: dissolved silica) of the reservoirs (Marne, Aube, Seine, and Pannecière reservoirs) in the Seine Basin using long-term dataset (1998-2018), and we also evaluated the reservoir effect on downstream partial pressure of carbon dioxide (pCO2) based on field measurements during 2019-2020. The mean annual retention rates accounted for 16%-53%, 26%-48%, and 22%-40%of the inputs of DIN, PO43-, and DSi in the four reservoirs during the period 1998 to 2018, respectively, showing that the four reservoirs play important roles in nutrient retentions. We further identified that three reservoirs (Marne, Aube, and Seine reservoirs) significantly changed downstream water quality during the emptying period, increasing the concentrations of dissolved organic carbon (DOC) and biodegradable DOC, while lowering the concentrations of DIN, DSi, PO43-, and total alkalinity. Interestingly, we found that the three reservoirs notably decreased downstream pCO2(24%-37%) and enhanced the gas transfer coefficient of CO2 (21%) in downstream rivers compared to the upstream ones, during the emptying period, which highlights the necessity to consider the potential impact of reservoirs on downstream riverine not only for water quality variables, but also for CO2 emissions. Finally, the findings of this study highlight the importance of the combination of biogeochemical and hydrological characteristics to understand the biogeochemical functioning of reservoirs to downstream rivers.