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• W2996317202 abstract "Abstract. Reservoirs are important sources of greenhouse gases (GHGs) to the atmosphere, and their number is rapidly increasing, especially in tropical regions. Accurately predicting their current and future emissions is essential but hindered by fragmented data on the subject, which often fail to include all emission pathways (surface diffusion, ebullition, degassing, and downstream emissions) and the high spatial and temporal flux variability. Here we conducted a comprehensive sampling of Batang Ai reservoir (Malaysia), and compared field-based versus modelled estimates of its annual carbon footprint for each emission pathway. Carbon dioxide (CO2) and methane (CH4) surface diffusion were higher in upstream reaches. Reducing spatial and temporal sampling resolution resulted in up to a 64 % and 33 % change in the flux estimate, respectively. Most GHGs present in discharged water were degassed at the turbines, and the remainder were gradually emitted along the outflow river, leaving time for CH4 to be partly oxidized to CO2. Overall, the reservoir emitted 2475 gCO2eqm-2yr-1, with 89 % occurring downstream of the dam, mostly in the form of CH4. These emissions, largely underestimated by predictions, are mitigated by CH4 oxidation upstream and downstream of the dam but could have been drastically reduced by slightly raising the water intake elevation depth. CO2 surface diffusion and CH4 ebullition were lower than predicted, whereas modelled CH4 surface diffusion was accurate. Investigating latter discrepancies, we conclude that exploring morphometry, soil type, and stratification patterns as predictors can improve modelling of reservoir GHG emissions at local and global scales." @default.
• W2996317202 created "2019-12-26" @default.
• W2996317202 creator A5000010237 @default.
• W2996317202 creator A5085077807 @default.
• W2996317202 date "2020-01-31" @default.
• W2996317202 modified "2023-10-10" @default.
• W2996317202 title "The carbon footprint of a Malaysian tropical reservoir: measured versus modelled estimates highlight the underestimated key role of downstream processes" @default.
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• W2996317202 doi "https://doi.org/10.5194/bg-17-515-2020" @default.
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