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.