Comparison of greenhouse gas emission estimates from six hydropower reservoirs using modeling versus field surveys

Abstract

As with most aquatic ecosystems, reservoirs play an important role in the global carbon (C) cycle and emit greenhouse gases (GHG) as carbon dioxide (CO₂) and methane (CH₄). However, GHG emissions from reservoirs are poorly quantified, especially in temperate systems, resulting in high uncertainty. We compared reservoir C emission estimates and uncertainty of diffusive, ebullitive, and degassing pathways in six hydropower reservoirs in the southeastern United States among four data sources: two field-based surveys and two models (including the GHG Reservoir “G-res” Tool). We found that CH₄ diffusion was most similar across data sources (modeled minus observed, bias = − 21 g CO_2-eq m⁻² y⁻¹) and had low relative uncertainty (coefficient of variation, CV = 0.98). On the other hand, CO₂ diffusion was least consistent across data sources (bias = − 518 g CO_2-eq m⁻² y⁻¹). Both field surveys indicated strong negative CO₂ diffusion (i.e., CO₂ uptake) at all reservoirs, while G-res estimated positive CO₂ diffusion. By extension, total C emissions showed similar discrepancies, leading to high uncertainty in upscaling and interpreting reservoir source-sink dynamics. Finally, CH₄ ebullition had the highest relative uncertainty (CV = 2.77) due to high variability across sites. We discuss limitations of field surveys and these models, including temperature-based annualization methods, varying definitions of ebullition zones, low sampling resolution, and lack of dynamism. Future field efforts focused on capturing variability in CO₂ diffusion and CH₄ ebullition will be especially valuable in reducing uncertainty and improving models to advance our understanding reservoir GHG emissions.