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Abstract. Waters impounded behind dams (i.e., reservoirs) areimportant sources of greenhouses gases (GHGs), especially methane (CH4), butemission estimates are not well constrained due to high spatial and temporalvariability, limitations in monitoring methods to characterize hot spot andhot moment emissions, and the limited number of studies that investigatediurnal, seasonal, and interannual patterns in emissions. In this study, weinvestigate the temporal patterns and biophysical drivers of CH4emissions from Acton Lake, a small eutrophic reservoir, using a combinationof methods: eddy covariance monitoring, continuous warm-season ebullitionmeasurements, spatial emission surveys, and measurements of key drivers ofCH4 production and emission. We used an artificial neural network togap fill the eddy covariance time series and to explore the relativeimportance of biophysical drivers on the interannual timescale. We combinedspatial and temporal monitoring information to estimate annualwhole-reservoir emissions. Acton Lake had cumulative areal emission rates of45.6 ± 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 and2018 across the whole 2.4 km2 area of the lake. The main differencebetween years was a period of elevated emissions lasting less than 2 weeksin the spring of 2018, which contributed 17 % of the annual emissions inthe shallow region of the reservoir. The spring burst coincided with aphytoplankton bloom, which was likely driven by favorable precipitation andtemperature conditions in 2018 compared to 2017. Combining spatiallyextensive measurements with temporally continuous monitoring enabled us toquantify aspects of the spatial and temporal variability in CH4emission. We found that the relationships between CH4 emissions andsediment temperature depended on location within the reservoir, and we observed a clearspatiotemporal offset in maximum CH4 emissions as a function ofreservoir depth. These findings suggest a strong spatial pattern in CH4biogeochemistry within this relatively small (2.4 km2) reservoir. Inaddressing the need for a better understanding of GHG emissions fromreservoirs, there is a trade-off in intensive measurements of one water bodyvs. short-term and/or spatially limited measurements in many waterbodies. The insights from multi-year, continuous, spatially extensivestudies like this one can be used to inform both the study design andemission upscaling from spatially or temporally limited results,specifically the importance of trophic status and intra-reservoirvariability in assumptions about upscaling CH4 emissions. 

Streams and rivers are significant sources of nitrous oxide (N₂O), carbon dioxide (CO₂), and methane (CH₄) globally, and watershed management can alter greenhouse gas (GHG) emissions from streams. We hypothesized that urban infrastructure significantly alters downstream water quality and contributes to variability in GHG saturation and emissions. We measured gas saturation and estimated emission rates in headwaters of two urban stream networks (Red Run and Dead Run) of the Baltimore Ecosystem Study Long-Term Ecological Research project. We identified four combinations of stormwater and sanitary infrastructure present in these watersheds, including: (1) stream burial, (2) inline stormwater wetlands, (3) riparian/floodplain preservation, and (4) septic systems. We selected two first-order catchments in each of these categories and measured GHG concentrations, emissions, and dissolved inorganic and organic carbon (DIC and DOC) and nutrient concentrations biweekly for 1 year. From a water quality perspective, the DOC : NO₃⁻ ratio of streamwater was significantly different across infrastructure categories. Multiple linear regressions including DOC : NO₃⁻ and other variables (dissolved oxygen, DO; total dissolved nitrogen, TDN; and temperature) explained much of the statistical variation in nitrous oxide (N₂O, r² =  0.78), carbon dioxide (CO₂, r² =  0.78), and methane (CH₄, r² =  0.50) saturation in stream water. We measured N₂O saturation ratios, which were among the highest reported in the literature for streams, ranging from 1.1 to 47 across all sites and dates. N₂O saturation ratios were highest in streams draining watersheds with septic systems and strongly correlated with TDN. The CO₂ saturation ratio was highly correlated with the N₂O saturation ratio across all sites and dates, and the CO₂ saturation ratio ranged from 1.1 to 73. CH₄ was always supersaturated, with saturation ratios ranging from 3.0 to 2157. Longitudinal surveys extending form headwaters to third-order outlets of Red Run and Dead Run took place in spring and fall. Linear regressions of these data yielded significant negative relationships between each gas with increasing watershed size as well as consistent relationships between solutes (TDN or DOC, and DOC : TDN ratio) and gas saturation. Despite a decline in gas saturation between the headwaters and stream outlet, streams remained saturated with GHGs throughout the drainage network, suggesting that urban streams are continuous sources of CO₂, CH₄, and N₂O. Our results suggest that infrastructure decisions can have significant effects on downstream water quality and greenhouse gases, and watershed management strategies may need to consider coupled impacts on urban water and air quality.