Abstract. Waters impounded behind dams (i.e., reservoirs) are
important sources of greenhouses gases (GHGs), especially methane (CH4), but
emission estimates are not well constrained due to high spatial and temporal
variability, limitations in monitoring methods to characterize hot spot and
hot moment emissions, and the limited number of studies that investigate
diurnal, seasonal, and interannual patterns in emissions. In this study, we
investigate the temporal patterns and biophysical drivers of CH4
emissions from Acton Lake, a small eutrophic reservoir, using a combination
of methods: eddy covariance monitoring, continuous warm-season ebullition
measurements, spatial emission surveys, and measurements of key drivers of
CH4 production and emission. We used an artificial neural network to
gap fill the eddy covariance time series and to explore the relative
importance of biophysical drivers on the interannual timescale. We combined
spatial and temporal monitoring information to estimate annual
whole-reservoir emissions. Acton Lake had cumulative areal emission rates of
45.6 ± 8.3 and 51.4 ± 4.3 g CH4 m−2 in 2017 and 2018,
respectively, or 109 ± 14 and 123 ± 10 Mg CH4 in 2017 and
2018 across the whole 2.4 km2 area of the lake. The main difference
between years was a period of elevated emissions lasting less than 2 weeks
in the spring of 2018, which contributed 17 % of the annual emissions in
the shallow region of the reservoir. The spring burst coincided with a
phytoplankton bloom, which was likely driven by favorable precipitation and
temperature conditions in 2018 compared to 2017. Combining spatially
extensive measurements with temporally continuous monitoring enabled us to
quantify aspects of the spatial and temporal variability in CH4
emission. We found that the relationships between CH4 emissions and
sediment temperature depended on location within the reservoir, and we observed a clear
spatiotemporal offset in maximum CH4 emissions as a function of
reservoir depth. These findings suggest a strong spatial pattern in CH4
biogeochemistry within this relatively small (2.4 km2) reservoir. In
addressing the need for a better understanding of GHG emissions from
reservoirs, there is a trade-off in intensive measurements of one water body
vs. short-term and/or spatially limited measurements in many water
bodies. The insights from multi-year, continuous, spatially extensive
studies like this one can be used to inform both the study design and
emission upscaling from spatially or temporally limited results,
specifically the importance of trophic status and intra-reservoir
variability in assumptions about upscaling CH4 emissions.
Temporal trends in methane emissions from a small eutrophic reservoir: the key role of a spring burst
