Abstract. Waters impounded behind dams (i.e. reservoirs) are important sources of greenhouses gases, especially methane (CH₄), but their contribution is 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 inter-annual timescale. Acton Lake had cumulative areal emission rates of 40.6 ± 5.9 and 71.4 ± 4.2 g CH₄ m⁻² in 2017 and 2018, respectively, or 97.4 ± 14 and 171 ± 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 two weeks in the spring of 2018, which contributed 17 % of the total annual emissions, and was likely due to favourable sediment temperature and algal carbon substrate availability in 2018 compared to 2017. CH₄ emissions only displayed diurnal patterns 18.5 % of the monitoring period, suggesting that factors that do not follow a diurnal pattern (e.g. substrate availability) may be driving emissions. 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 T depended on location within the reservoir and observed a clear spatio-temporal 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 measurement of one water body versus 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-lake variability in assumptions about upscaling CH₄ emissions.

中文翻译：

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小型富营养化储层甲烷排放的时间模式和生物物理控制：两年涡流协方差监测的见解

摘要。坝后蓄积的水（即水库）是温室气体的重要来源，尤其是甲烷（CH ₄），但由于时空变化大，用于表征热点和高温时刻排放的监测方法的局限性，它们的贡献并未得到很好的限制，且研究排放量的昼夜，季节和年际模式的研究数量有限。在这项研究中，我们使用以下多种方法研究了小型富营养化水库Acton Lake的CH ₄排放的时间模式和生物物理驱动力：涡流协方差监测，连续暖季沸腾测量，空间排放调查以及关键测量CH _4的驱动程序生产和排放。我们使用人工神经网络填补了涡度协方差时间序列，并探讨了生物物理驱动器在年际时间尺度上的相对重要性。阿克顿湖在2017年和2018年的累积面积排放率分别为40.6±5.9和71.4±4.2 g CH ₄  m ^-2，或者在2017年和2018年在整个2.4 km ²区域中分别为97.4±14和171±10 Mg CH ₄湖的。年份之间的主要差异是2018年春季排放量持续增加不到两周的时期，占年度总排放量的17％，这很可能是由于与2017年相比，2018年的沉积物温度和藻类碳底物利用率高CH ₄排放量仅显示监测期内的日变化模式，占监测期间的18.5％，这表明不遵循日变化模式的因素（例如，底物可用性）可能正在推动排放。将空间广泛的测量与时间连续监视相结合，使我们能够量化CH ₄排放的时空变异性。我们发现CH ₄排放量与沉积物T之间的关系取决于储层内的位置，并观察到最大CH ₄排放量随储​​层深度的变化存在明显的时空偏移。这些结果表明在CH一个强的空间图案₄这个相对小的（2.4公里内生物地球化学²）水库。为了满足对水库温室气体排放的更好理解的需要，在一个水体的密集测量与许多水体中的短期和/或空间有限的测量之间需要权衡取舍。像这样的多年的，连续的，空间上广泛的研究得出的见解可用于从空间或时间上有限的结果中为研究设计和排放量增加提供信息，特别是在关于CH升高的假设中，营养状态和湖内变异性的重要性₄排放。