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.