Reservoirs emit large amounts of methane (CH₄) to the atmosphere relative to their small surface area globally. Among the different pathways of reservoir CH₄ emissions, bubbling from the sediments (ebullition) and diffusion from the water surface are major contributors of CH₄ efflux. The magnitude of ebullition and diffusion can vary substantially over space and time in large reservoirs. However, it is unclear how the drivers of ebullition and diffusion vary along a reservoir's longitudinal gradient, particularly in small reservoirs. We measured ebullition, diffusion, and eight environmental driver variables at four transects along a longitudinal gradient within a small, eutrophic reservoir. We used time series modeling to examine how the drivers of ebullition and diffusion varied among transects. Sediment‐water interface temperature, inflow discharge, and wind speed were the most important drivers of CH₄ ebullition in upstream transects of the reservoir, while phytoplankton biomass was the most important driver of ebullition in the downstream transect closest to the dam. Strikingly, CH₄ ebullition dynamics were extremely well captured by the time series models, as the modeled rates for the furthest upstream transect closely matched the observed rates throughout the monitoring period. In contrast, CH₄ diffusion dynamics were harder to model, with phytoplankton biomass as the primary driver of diffusion across all transects. Our results indicate that multiple drivers affect CH₄ emissions along a small reservoir's longitudinal gradient and should be considered when upscaling site measurements to reservoir‐wide CH₄ emissions and ultimately regional or global estimates.

中文翻译：

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小型淡水水库纵向梯度甲烷散放和扩散的幅度和驱动力

相对于全球的小表面积，储层向大气排放大量甲烷（CH ₄）。在储层CH ₄排放的不同途径中，沉积物冒泡（沸腾）和水面扩散是CH _4的主要贡献者。外排。在大型水库中，沸腾和扩散的幅度可能会随时间和空间而变化。但是，尚不清楚白化和扩散的驱动力如何沿着储层的纵向梯度变化，特别是在小型储层中。我们在一个小的富营养化储层中，沿着纵向梯度在四个样点处测量了沸腾，扩散和八个环境驱动因素。我们使用时间序列建模来检验横断面中的磁化和扩散驱动力如何变化。沉积物-水界面温度，流入流量和风速是CH ₄的最重要驱动因素水库上游断面的沸腾，而浮游生物的生物量是最接近大坝的下游断面的沸腾的最重要驱动力。令人惊讶的是，时间序列模型很好地捕获了CH _4的动态变化，因为最远的上游样带的建模速率与整个监测期间的观测速率紧密匹配。相比之下，CH ₄扩散动力学更难建模，浮游植物生物量是所有样带扩散的主要驱动力。我们的结果表明，多个驱动因素会沿着小水库的纵向梯度影响CH ₄排放，在将现场测量规模扩大到整个水库CH ₄时应考虑 排放量以及最终的区域或全球估算值。