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Deconstructing methane emissions from a small NorthernEuropean river: Hydrodynamics and temperature as key drivers Daniel F. McGinnis, Nicole Bilsley, Mark Schmidt, Peer Fietzek, Pascal Bodmer, Katrin Premke, Andreas Lorke, and Sabine Flury Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b03268 • Publication Date (Web): 03 Oct 2016 Downloaded from http://pubs.acs.org on October 8, 2016

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Environmental Science & Technology

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Deconstructing methane emissions from a small Northern-

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European river: Hydrodynamics and temperature as key drivers

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Daniel F. McGinnis1,2,3.*, Nicole Bilsley4, Mark Schmidt3, Peer Fietzek3,5, Pascal Bodmer2,6,

4

Katrin Premke2, Andreas Lorke8, Sabine Flury2 1

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University of Geneva, Aquatic Physics, Department F.-A. Forel, Section of Earth and Environment Sciences, Faculty of Science, CH-1211 Geneva 4, Switzerland

2

Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Chemical Analytics and

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Biogeochemistry, 12587 Berlin, Germany 3

GEOMAR Helmholtz Centre for Ocean Research Kiel, RD2 Marine Biogeochemistry, 24148

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Kiel, Germany 4

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5

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Scripps Institution of Oceanography, La Jolla, California 92093, USA

8

Kongsberg Maritime Contros GmbH, 24148 Kiel, Germany

Institute of Biology, Freie Universität Berlin, 14195 Berlin, Germany

Institute for Environmental Sciences, Environmental Physics, University of Koblenz-Landau,

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76829 Landau, Germany

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AUTHOR INFORMATION

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Corresponding Author

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* Corresponding Author, [email protected], +41 22 379 0792

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University of Geneva, Uni Carl Vogt, 66 Blvd. Carl-Vogt, 1211 Geneva 4, Switzerland

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KEYWORDS

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Methane emissions, wetlands, river, climate change, ebullition, water flow rate, lateral exchange

1 ACS Paragon Plus Environment


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ABSTRACT

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Methane (CH4) emissions from small rivers and streams, particularly via ebullition, are currently

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under-represented in the literature. Here, we quantify the methane effluxes and drivers in a small,

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Northern European river. Methane fluxes are comparable to those from tropical aquatic systems,

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with average emissions of 320 mg CH4 m-2 d-1. Two important drivers of methane flux variations

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were identified in the studied system: 1) temperature-driven sediment methane ebullition and 2)

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flow-dependent contribution suspected to be hydraulic exchange with adjacent wetlands and

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small side-bays. This flow-dependent contribution to river methane loading is shown to be

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negligible for flows less than 4 m3 s-1, and greater than 50% as flows exceed 7 m3 s-1. While the

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temperature - ebullition relationship is comparable to other systems, the flow rate dependency

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has not been previously demonstrated. In general, we found that about 80% of the total emissions

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were due to methane bubbles. Applying ebullition rates to global estimates for fluvial systems,

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which currently are not considered, could dramatically increase emission rates to ranges from

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lakes or wetlands. This work illustrates that small rivers can emit significant methane, and

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highlights the need for further studies, especially the link between hydrodynamics and connected

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wetlands.

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TEXT

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INTRODUCTION

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Including both seasonal and permanent waterbodies (lakes, reservoirs, rivers and wetlands),

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earth’s land surface is covered with between ~6 to 15% freshwater.1 Recently, it was recognized

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that these freshwaters actively process and transform received organic carbon (C).2, 3 Currently,

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freshwaters are estimated to receive 3 Pg of C per year, of which about half (1.4 Pg C yr-1) is

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emitted to the atmosphere as carbon dioxide (CO2) and methane (CH4). The remainder is either

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transported to coastal oceans (~30%) or buried (~20%) in the freshwater sediments.3 In

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freshwaters, the degree of C sequestration, degradation pathways and contribution to the

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atmospheric greenhouse gas (GHG) budget are significantly impacted by sedimentation rates,4

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temperature,3, 5, 6 hydrodynamics,7 and waterbody alterations (i.e. impoundments).8, 9

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Emissions of methane from freshwaters are generally much lower than CO2, however

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methane has 28 times higher global warming potential on a per mass basis.10 As methane is a

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sparingly soluble gas (~27 times less soluble than CO2),11 it is estimated that about 50% of

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freshwater methane emissions (excluding wetlands) are due to methane bubbles, which accounts

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for ~10% of all global emissions.12, 13 Despite their importance for the global balance, ebullitive

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emissions from aquatic systems are still likely underestimated due to the stochastic nature of

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ebullition events.12, 14

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While methane emission from lakes and reservoirs are increasingly investigated,8, 12, 15, 16

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methane emission studies from streams17 and rivers,18 particularly via ebullition, are under-

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represented in the literature.19, 20 Streams and rivers can be significant sources of methane,

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however, and are particularly susceptible to both autochthonous and allochthonous carbon input

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and exchange with their bordering environments,21 including groundwater22 and adjacent



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wetlands.19, 23 Recent estimates of streams and rivers place emissions at ~27 Tg CH4 yr-1,20

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almost 20 times higher than the previous estimates.12 These estimates, however, do not include

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ebullitive fluxes.20 The key challenges in accurately assessing C budgets and methane emissions

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from these waterbodies are both the lack of data and measurement limitations. Methane

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emissions, particularly via ebullition, are heterogeneous and stochastic and thus require a large

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temporal and spatial coverage,14, 24 which is both time consuming and expensive.

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Small rivers are abundant worldwide and represent commonly found aquatic systems25-27, and

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there is a need to better assess the methane emissions, pathways and drivers. The goals of this

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study are therefore to 1) quantify the overall methane emissions and pathways from a small

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variably-flowing river located in a largely agricultural watershed, and 2) elucidate the key

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emission drivers (i.e. temperature and flow rate) with system analytical approaches. Using these

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results, we then 3) discuss the potential for future emissions under changing climate scenarios.

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MATERIAL AND METHODS Study site. The Schwentine River (Figure S1), located in eastern Schleswig Holstein

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(Germany) is ~70 km long and connects several primarily eutrophic lake-systems

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(www.schleswig-holstein.de). The river is the main drainage system of these lakes to the Baltic

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Sea and is dammed at its coastal outlet to the Kieler Fjord.28 The watershed is 726 km2 and

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consists of about 85% arable land.29 Flow rates during the study ranged from 1.3 to 16 m3 s-1.

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Water level was regulated so that fluctuations were less than ±3 cm [flow and water level data

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from Schleswig-Holstein Agency for Coastal Defense, National Park and Marine Conservation].

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Two upstream hydropower plants (Raisdorf 1 and 2) control the discharge into the lower reach of

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the Schwentine River, which then flows about ~6.5 km to the Kieler Fjord. In the furthest


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downstream ~3 km, the shoreline is extensively lined with inundated reed stands, wetlands,

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vegetation (estimated to cover >80% of the shore line), aquatic macrophytes, drainage ditches,

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small connected ponds and side-bays (from here on, collectively called wetlands; Figure S1).

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The downstream ~3 km stretch has an average width of ~35 meters and average depth of ~1 m.

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Campaign overview. Dissolved surface water methane was measured along the lower

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Schwentine River reach (see Figure S1). Between 9 and 10 discrete water (methane) samples

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(see SI Methods) were collected while floating downstream with a canoe (termed “longitudinal

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survey”). Six longitudinal surveys were performed in 2010 (21 July – 14 Sept) and 10

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longitudinal surveys in 2011 (5 July – 5 Aug).

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CH4 and CTD Sensors. Between 12 July to 28 Sept, 2011, a dissolved CH4 sensor (HydroC,

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KM Contros GmbH, Germany) and CTD (conductivity-temperature-depth; CTD-XR420, RBR

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Ltd., Canada) were mounted on a dedicated moored lander system at ~75 cm above sediment in

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~1.5 meter water depth (See Fig 1. in Fietzek et al.30), which was deployed laterally just before

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the discharge at the dam. CH4, temperature and conductivity were recorded every 1 minute. The

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CH4 sensor was calibrated before and after the deployment for a range of up to 3 µmol L-1. The

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data were post-processed to ensure data quality (See SI Methods).

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Water surface methane fluxes. Surface CH4 fluxes were measured using floating chambers

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in 2011 and 2013. Specifically, in 2011 surface flux measurements were performed August 17

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and August 18 using four anchored chambers located between 50 and 100 m upstream from the

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dam. The chamber gases were discretely sampled at time zero and every ~1 hour for

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approximately 2 hours to determine the total flux (ebullitive + diffusive).see 8 From 2 – 5 July,

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2013 fluxes were measured with a drifting chamber connected to a portable GHG analyzer

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(UGGA; Los Gatos Research, Inc.; see SI Methods) covering the downstream 2000 meters of the



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river and could separately resolve diffusive and ebullitive fluxes.31, 32 Briefly, fluxes were

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measured 30 times, and slopes obtained by determining the increase of chamber headspace CH4

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over approximately 10 minutes.

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Methane porewater sampling. Sediment porewater methane concentrations and fluxes were

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analyzed after the method described in Maeck et al..8 Push cores ~20 cm in length were taken 2

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km and 1 km upstream from the dam, and in the forebay near (~20 m) the dam in August 2011.

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Fluxes were estimated with Ficks’s First Law (See SI Methods).

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Mass Balance. The bubble dissolution contribution to the downstream methane loading was calculated with a mass balance on the downstream river stretch shown on Figure 1 where:

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= − + − +

(kg d-1)

(1)

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The left hand term is the change in methane mass (m, kg) with time (t). The masses denote the

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various sources (+) and sinks (-) in kg d-1 from the sediment (sed), surface diffusive flux (diff),

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and bubble dissolution (bub) within the water column. The average mass inflow and outflow of

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CH4 (in kg d-1) were calculated ( = ) using the campaign averaged discrete sampled

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CH4 concentrations at 2.5 km upstream and at the dam, respectively (See Table S1).

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Statistics. Statistical approaches are described in the Supporting Information (Methods). RESULTS

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Results I – discrete sampling.

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Sediment and surface fluxes. The average methane fluxes at the sediment-water interface

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(SWI) from the three cores is FSED = 2.0 ± 1.1 mmol m-2 d-1 (32.7 ± 18 mg m-2 d-1) at ~19 oC

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(Figure S2). Note that bubbles were observed in all cores, indicating gas oversaturation.


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Figure 1. Average dissolved methane concentration (white dots) in the river as a function of distance from the dam (3,200 m) from the 17 longitudinal surveys (error bars represent standard deviation; see Figure S3). The dashed grey line shows the linear regression, which shows on average an increase of 0.16 nmol L-1 per meter of river distance (R2 = 0.95). Also shown are the measured mass inflow and outflow (Table S1), measured sediment fluxes, water surface diffusive (2013) and average ebullitive fluxes (2011 and 2013), and estimated bubble dissolution to close the mass balance. Where appropriate, values are reported in both kg d-1 for the mass balance and as fluxes (mmol m-2 d-1). 130 131

Methane emission measured with the anchored chamber (2011: ebullitive + diffusive) was

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14.5 ± 20.4 mmol m-2 d-1 (232 ± 327 mg m-2 d-1; n = 28; average water temperature of 17.8 °C).

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With the drifting chamber (2013) the ebullitive methane flux was 15.8 ± 17.7 mmol m-2 d-1 (253

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± 283 mg m-2 d-1; n = 5; average water temperature of 18.2 °C), while the surface diffusive

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methane flux was 1.4 ± 1.0 mmol m-2 d-1 (22.4 ± 16 mg m-2 d-1; n = 8). As the water velocity was

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estimated to be 10 – 12 cm s-1, the anchored chambers may slightly bias the diffusive component

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of the fluxes due to turbulence induced artifacts.33 The combined techniques, however, suggest

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that diffusive fluxes are less than 10% of the total (ebullitive + diffusive) flux and the methods 7 ACS Paragon Plus Environment


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are comparable for determining total emissions. Using the average of the two methods gives an

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ebullition estimate of ~15 mmol m-2 d-1.

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Methane concentration along the river. The average (and standard deviation) of all 17

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longitudinal surveys are shown on Figure 1. The average water discharge and temperature for the

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surveys was 4.7 ± 1.6 m3 s-1 and 19.0 ± 2.2 oC. Individual survey results are shown on Fig S3

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and are summarized Table S1 (Sample locations on Figure S1). In general, the methane increased

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almost linearly approaching the dam and increased by about 100% along the measured river

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stretch. Linear fits to the concentrations measured along an individual survey resulted in R2 of

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0.9 – 0.99 (except transect 1 R2 = 0.38). The river was oxic during the measurements, with O2

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values of 68-103% saturation (mean 91%) during longitudinal surveys. The mass methane inflow

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(mCH4in = 3.8 kg d-1) and outflow (mCH4out = 6.5 kg d-1) are the averages from the longitudinal

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transects and calculated as m = Q x CCH4 (See Table S1).

Figure 2. Methane concentration at the dam as a function of discharge (a) and temperature (b) and mass discharge of methane as a function of discharge (and temperature) (c). Plot colors indicate the water temperature (or discharge Q) when each data point was obtained. Lines on plot c) show linear fits to data for selected temperature ranges.


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Results II – time series. The average methane concentration at the dam discharge was 860

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nmol L-1 (~260 times over saturated relative to atmospheric equilibrium) and covered a 6-fold

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range (300 – 1800 nmol L-1) (12 July – 28 Sept, 2011; Figure 2a and 2b and Figure 3a). While

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the methane concentration at the dam decreased with increasing flow, the rate of concentration

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decrease was proportionately slower than the increase of the flow rate (Fig 2a). For example, as

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the flow increased from 2 to 16 m3 s-1 (a factor of 8), the methane concentrations only decreased

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from about 1800 to 500 nmol L-1 (a factor of 3.6). The water temperature ranged from ~14 – 22

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o

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factor of 10, from ~2 to 20 kg d-1 (125 – 1250 mol d-1) (Figure 2c).

C and was correlated with discharge (discussed below). Methane mass discharge varied by a

2000

P1 P2

Power-spectral density (-)

CH4 (nmol L-1)

(a) 1500 1000 500 22

0.03 (b) T Q CH4

0.02 0.01 0.00

10-1

18

Co-spectral density (-)

T (oC)

20

16 14

Q (m3 s-1)

16 12 8

0.8

(c)

Q - CH4

100

T-Q T - CH4

0.4 0.0 -0.4 -0.8

4

10-1

0 7/12/2011 7/26/2011 8/9/2011 8/23/2011 9/6/2011 9/20/2011

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Frequency (day-1)

Figure 3 a) Time series of dissolved methane concentration (black is estimated sensor response time τ63= 15 min (flag 1), blue is estimated τ63= 25 min (flag 2); see SI Methods), temperature (T) and discharge (Q). P1 and P2 indicate the two contrasting flow regimes (see text). b) Variancepreserving power spectral density of temperature, discharge and dissolved CH4 concentration. c) Cospectral density of paired variables. For comparison, the spectra and co-spectra are normalized using the total variance and covariance, respectively.



160 161

DISCUSSION Bubble dissolution and mass balance. Discrete measurements are summarized on Figure 1,

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the only term to solve for is the internal loading due to the rising bubble dissolution.

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Using equation 1 and assuming steady state, the bubble contributions, mbub is solved for as:

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= − + − + = −3.8 + 6.5 − 3.4 + 1.9 = 1.2 kg d%& . The

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mass balance indicates that 1.2 kg d-1 (Fbub = 0.7 mmol m-2 d-1) of internal methane loading is

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due to bubble dissolution, or about 5% of the measured ebullitive surface flux (26 kg d-1). The

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5% dissolution would result from a bubble diameter of 5 mm released from 1 m depth.34

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Emissions – first estimate. Summing the total measured emissions presented on Figure 1,

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this lower reach of the Schwentine river releases 34.4 kg d-1 of CH4 (~19 mmol m-2 d-1 or 310 mg

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CH4 m-2 d-1) in total. Of this amount, about 8.4 kg d-1 (24%) escapes by diffusion and release at

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the dam, and 26 kg d-1 (76%) escape as bubbles. While the above only provides a snapshot of

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emissions, below we investigate temporal variability.

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Methane drivers: temperature and flow rate. A time-series analysis was performed to

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identify the roles of temperature and flow as drivers for internal methane loading and emissions.

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The analysis covered two distinct discharge regimes named P1 and P2 before and after 13

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August 2013, respectively (Figure 3a). This separation was chosen because P1 exhibited a lower

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average discharge (6.2 ± 1.5 m3 s-1) with well-pronounced periodic variations in all parameters

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(Q, T, and CH4) while P2 had a mean discharge nearly twice as large (11.2 ± 1.3 m3 s-1) with

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more irregular and lower amplitude variations.

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Considering both discharge regimes, CH4 concentration was positively linearly correlated

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with temperature (R2 = 0.56, p < 0.001) and negatively correlated with discharge (R2 = -0.67, p
10 days which may reflect the time

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scales of temperature change necessary to affect the methane oversaturated zone in the sediment

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(diffusive length scale for 10 days for heat is ~34 cm).

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System analysis. The dissolved methane concentrations in the downstream river stretch

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increase in a linear manner (Figure 1). A similar trend was observed in run-of-river Lake

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Wohlen16 and allows us to simplify a system-analysis approach by assuming spatially-constant,

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zero-order inputs of the various methane sources (Figure 1). Using the longitudinal survey data,

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the flow-dependent methane contribution (R) is separated from the temperature-driven ebullitive

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fluxes and subsequent bubble dissolution FbubA (A is the sediment surface area) for each survey.

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Equation 2 is solved to seek the methane loading FbubA + R (CH4loading, Table S1). In this

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analysis, only the lower 2500 m stretch is consider as all surveys covered this range. Tracking a

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1 x 1 m water parcel traveling down the river (see Figure S6 for model concept), the methane

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concentration can be expressed as

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'

( = ) * − ) * + +) * + ,-,

(mmol d-1, kg d-1)


(2)


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where V is the downstream water volume (35 m3). On average, the total CH4loading from

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equation 2 [FbubA + R] totals 2.8 kg d-1 (Table S1). The methane loading generally follows a

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linear trend with flow rate (R2 = 0.77, Figure 4a). Two outliers (not included in the regression)

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were observed (longitudinal surveys 1 and 2) when the flow was low (2 m3 s-1) and temperatures

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high (>20°C) suggesting that the river was perhaps more resembling a (hot) lake under these

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conditions. The outliers on Figure 4b generally followed periods of rapidly increasing flow rates

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(Figure S5), potentially indicating more extreme flushing of side-bays and adjacent wetlands.

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Additionally, we cannot rule out that high and rapidly accelerating flow rates may also disturb

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the sediments. The temperature also predicts the loading well, but only for flows < 6 m3 s-1

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(Figure 4b), and under-predicts the methane loading by a factor ~2 for flows > 6 m3 s-1. 6 (a)

(b)

11

14

14 2

2

2

10

10

1 0

R2 = 0.68

R2 = 0.77

3

-1

Q ≤ 6.0 m s 3 -1 Q > 6.0 m s

Surveys 3 - 17 Surveys 1 - 2

(c)

90 1

1

4 3

17

% Methane loading

Methane loading (kg d-1)

17

5

100

11

80

R² = 0.84

70 60 Ebullition R

50 40 30 20 10

1 2 3 4 5 6 7 8 910 15 20 25 3 -1 Discharge, Q (m s ) Temperature, T (°C)

0 2

3

4

5

6

7 3

Discharge, Q (m s-1)

Figure 4. Methane loading (FbubA + R) as a function of Q (a) and T (b). Red symbols were omitted from the regression analysis. Grey line on (b) is regression on data for Q ≤ 4.1 m3 s-1. (c) Fraction of loading estimated from bubble dissolution contribution and adjacent wetland fluxes. Curves are fits of 3rd degree polynomials. 12 ACS Paragon Plus Environment

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Deconstructing methane sources. The flow-related contribution, R, and the bubble

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contribution, FbubA, to the internal methane loading are estimated in the following steps:

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1) The ebullition can be considered as a measure of methane production rate in the

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sediment,35 and therefore we assume it can be described as a function of temperature. The

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dissolution fraction of a single bubble however does not significantly vary over the

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temperatures34 and was determined to be 5% for this system. The flow-driven methane

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contribution appears minimal when flow rates are low, and a linear relationship between methane

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loading and temperature shows an excellent fit (FbubA (kg d-1) = 0.39T – 5.08; R2 = 0.97, Fig 4b)

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when Q < 4.1 m3 s-1, while including data with Q > 4.1 m3 s-1 decreases the correlation. The

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temperature-ebullition loading equation is therefore used to estimate the temperature-driven

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ebullition loading over all of the measured longitudinal surveys (Table S1, Fbub).

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2) With the bubble dissolution contribution from step 1, the remaining loading is therefore

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flow-driven R, which increases by ~1.35 kg d-1 per 1 m3 s-1 of flow increase above 5 m3 s-1 (R2 =

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0.75).

230 231

With this approach the relative internal CH4 loading contribution is determined to reach a 50/50 split (bubble dissolution vs. flow-driven) at around 7 m3 s-1 (Figure 4c).

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Flow dependency on methane loading. Methane loading and discharge were tightly coupled

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with water flow rate (Figure 2c, 3c & 4b). To our knowledge, this has not been demonstrated for

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similar systems. The sediment flux, Fsed, was similar to fluxes reported for other systems.8, 16

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Note that the temperature differences measured at our site (range 15.8 – 24.4 °C) should only

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affect the diffusive fluxes across the sediment-water interface by about ± 15% around the mean

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(19°C).34, 36 However, as the water column is oxic, methane oxidizers at the sediment surface

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likely suppress diffusive methane fluxes to the water column.37 Bubble release could be



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exacerbated by high or variable flows, as it has been shown to be affected by bottom shear and

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pressure changes due to water level fluctionations.38 While we do not exclude this possibility, the

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net bubble and the sediment flux should not increase substantially with increasing flow rate,

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especially over longer timescales, and the hydrodynamics should not affect the rate of sediment

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methane production in cohesive sediments.

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The most likely explanation for this flow-dependent R term is the connection to the adjacent

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wetlands (and submerged macrophytes, side-bays, etc.). The Schwentine River shoreline in the

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final ~3 km reach is predominately submerged vegetation, stagnant side-bays as well as small,

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quiescent streams (see photos, Figure S1). Melack et al.39 showed an increase of methane

248

emissions with increasing water level in areas of aquatic macrophytes in the Amazon basin.

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Marin-Muniz et al.40 reported significantly higher methane emissions (more than double) during

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the higher water levels (wet season) than during the dry season in tropical wetlands and swamps.

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The authors attribute this to more reduced conditions in the sediment due to the increase in water

252

coverage of the land.

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In the Schwentine River, the internal loading of methane due to bubble dissolution vs. the

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presumed wetland exchange is ~50/50% at flows of 7 m3 s-1, with the wetland exchange as the

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major contributor to internal methane loading at higher flows. Carbon sources fueling CO2 and

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CH4 emissions from floodplain lakes and river channels have been attributed to input from

257

adjacent wetlands,25, 39, 41 and interaction between the hydrology, wetlands and rivers.42 Borges et

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al.25 for example also observed an increase in CH4 concentrations with increasing wetlands

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inundation in the catchment of sub-Saharan African rivers. Teodoru et al.43 report that the spatial

260

variability of GHGs on the Zambezi River (and tributaries) was related to the connectivity with


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wetlands and floodplains, with highest main-channel CH4 concentrations found just downstream

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of extensive floodplains and wetland.

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In addition to receiving suspended sediments from the main river, the autochthonous C input

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into wetlands is reported to be high as these systems can be very productive.44 Quiescent areas

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along rivers and impoundments are more likely to be productive, accumulate settled particulate

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matter45 and are known to be methane ebullition hotspots.24 While the methane loading

267

dependence on flow rate appears robust in this study, it is unclear if there exists a hysteresis or

268

how different flow oscillation periods and amplitudes or sustained high flow rates may affect the

269

methane loading.

270

Temperature dependency on methane loading. The methane bubble emissions fit well with

271

the emission curve presented by DelSontro et al. (Figure 5).16 We report a Q10 of ~10 (the

272

relative change in a process over a 10 °C temperature change), which is generally higher than

273

those reported by others (e.g. ~4 by Yvon-Durocher et al.5), but the effect of temperature on

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methanogenesis is still not well constrained.46 DelSontro et al. 47 defines an “ecosystem-level”

275

Q10 which accounts for additional in situ factors driving ebullition and is better representative of

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actual emissions from freshwater ecosystems. The authors report Q10 for ebullition from shallow

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ponds of 13, which is in the range of those measured in subarctic lakes (Q10 = 14).46, 47

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Total CH4 emissions. The total emissions and internal loadings are summarized in Figure 1

279

for the average case for the longitudinal transects from measured data. Because the average flow

280

rate was low (4.8 ± 1.6 m3 s-1), the flow-dependent contribution R was likely near negligible for

281

that first estimate. However, the fraction of the internal methane loading due to dissolution of

282

rising methane bubbles has important implications for the overall emissions from shallow water

283

bodies. From the mass balance in Figure 1, only about 5% will dissolve in the water column,



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leaving the remaining ~95% of the bubble methane to be emitted to the atmosphere. This rate of

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dissolution corresponds to a 5 mm diameter bubble released from 1 m depth, and is in the size

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range reported in the literature.8,14,34 Therefore, by solving for the amount of methane internal

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loading due to released sediment bubble dissolution combined with bubble modeling16 allows

288

estimating the atmospheric bubble emissions.

Bubble emissions (mg m-2 d-1)

900 800 700 600 500 400

1

300 200

Surveys DelSontro 1 - mass balance 2 - 2013 3 - 2011

2 3

100 15

20

25 o

Water temperature ( C) Figure 5. Sediment bubble emissions from Table S1 as a function of temperature, and fit of ebullition vs. temperature from DelSontro et al. 16. The open symbols are (1) average emissions estimated from the longitudinal surveys, and (2) measured chamber fluxes from 2013 and (3) 2011. 289 290

With this assumption, the total CH4 ebullitive emission for the investigated stretch can be

291

estimated using the temperature relationship from Fig 4b. We estimate that the average bubble

292

emissions (Table S1, Bub.Emiss.) are ~33 kg d-1 (24 mmol m-2 d-1; 384 mg m-2 d-1; Tavg = 19 °C), 16 ACS Paragon Plus Environment

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293

which is well within the range of our surface ebullitive flux measurements and fit well on the

294

emissions vs. temperature curve reported in DelSontro et al. (see Figure 5).16

295

The average methane exported at the dam is 6.6 kg d-1 (Table S1; Dam.CH4Diss.). Combining

296

the estimated ebullition emissions with the dam methane release implies a total mean emission of

297

40 kg d-1 from the investigated stretch, close to the initial 35 kg d-1 estimated from the measured

298

data (Figure 1). In percentage, about 17% is emitted through the dam, and 83% as bubbles to the

299

atmosphere.

300

The temperature equation (Figure 4b) can also be applied to the time series to estimate the

301

average internal methane loading due to bubble dissolution, and subsequent bubble emissions

302

(Figure 3). This results in an average internal bubble dissolution loading of 2.1 kg d-1 and a

303

subsequent ebullitive emission of 28 kg d-1 (Tavg =17.9 °C). For the same time series, it is known

304

that the mean dam methane discharge is 10 kg d-1, giving a total emissions of 38 kg d-1. In this

305

case the dam discharge is about 26% of the total and the bubble emissions are 74%. Nevertheless

306

the total emissions are close to the previous estimates.

307

Using the average of the three total emission estimates (flux chamber, system analysis, and

308

time series) gives an emission of 38 ± 3 kg d-1, or 340 mg m-2 d-1 expressed as an aerial rate over

309

the downstream 3.2 km (~112,000 m2). Average emissions for this small, northern-European

310

river stretch are comparable to tropical reservoirs.48 Though this estimate does not consider the

311

lower emissions in winter, even halving this emission rate is in the same range as tropical and

312

subtropical wetlands and swamps40 and those reported for Amazonian rivers in areas with

313

aquatic macrophytes (92 – 243 mg m-2 d-1 for low and high water, respectively).39 Expressing

314

half of our above average as a yearly value (3.8 mol m-2 yr-1), the emissions from the Schwentine

315

are on the upper-end of those reported by Bastviken et al..12 What is clear in this analysis is the



316

importance of including ebullition in the river methane estimates. In our case, the total methane

317

emissions is ~4 times higher than the diffusive flux and outflow combined.

318

Finally, expressed as CO2 equivalents, the total methane emissions including all sources along

319

the investigated stretch are ~1000 kg CO2 d-1. This demonstrates that this small river, located in a

320

northern temperate zone, has areal methane emissions rates rivaling those from tropical rivers

321

and reservoirs.16, 52 Given the high abundance of small river systems worldwide, such rivers may

322

be much more significant components of the atmospheric carbon and methane budgets than

323

previously suspected.

324

An uncertain future. The Schwentine methane emissions are sensitive to climate parameters,

325

namely temperature and flow rate. The temperature influence on the methane concentration and

326

ebullition is not surprising and has been previously demonstrated.e.g. 49 DelSontro et al.16 reports

327

an exponential increase in bubble emission with increasing temperature in a run-of-river

328

reservoir, though their data were limited to temperatures less than 17oC. The exponential fit of

329

emissions vs. temperature provided by DelSontro et al., however, are in the range of the

330

ebullitive emissions reported in this study (Figure 5).

331

The increases in methane loading with both increasing temperature and flow rate suggests

332

that the emissions can be sensitive to both global warming and precipitation changes, though this

333

also depends on future nutrient and carbon loading that drive methane production. This is similar

334

to Campeau and Del Giorgio,49 who report that for their boreal stream network, GHG emissions

335

may increase by 13 – 68% over estimated climate scenarios spanning the next 50 years.

336

Temperatures in Northern Germany are forecasted to climb by 0.5 – 1.5 oC between 2021 –

337

2050.50 This has the potential to increase methane ebullitive emissions by about 3 – 8 mmol m-2

338

d-1 (15 – 40%). Precipitation is not expected to vary considerably (by about 10%) in the next


Page 18 of 29

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339

decades, but forecasts suggest more extreme events, particularly during the crucial summer

340

period.51

341

Our findings underline the importance of ‘river-connected’ wetlands/floodplains and their

342

role in carbon turnover. Adjacent wetlands, side-bays, etc. create important sedimentation zones

343

in rivers, with the adjacent wetlands in the Schwentine River essentially trapping organic matter

344

and nutrients during higher flows, where it is then processed under probably more reduced,

345

anoxic conditions under low flow rates. The result is a system where the carbon turnover and

346

flux pathways are sensitive to both temperature and flow regimes. These results, while by no

347

means providing complete coverage of annual variations, illustrate the importance of combined

348

measurements and system analytical approaches to help determine and deconstruct the different

349

methane sources, and their drivers. Using these approaches, we could paint a picture of a water

350

body that is sensitive to future changes in climate in terms of methane emissions.

351 352

Acknowledgements

353

The authors would like to thank Mr. H. Kühl and Schwentientalfahrt for providing the boats and

354

infrastructure. The authors also thank the Geomar laboratory for their assistance with the

355

samples, particularly Ms. B. Domeyer. Special thanks to O. Ghamraoui for processing the sensor

356

data, A. Mäck and S. Geissler for assisting with the 2011 flux data. Mr. H.-J. Weber and the

357

Schleswig-Holstein Agency for Coastal Defense, National Park and Marine Conservation kindly

358

provided the flow and water level data.

359 360 361



362

ASSOCIATED CONTENT

363

Supporting information

364

The supporting information includes supplementary methods, 1 table, and 6 ancillary figures,

365

including the map of the study site (Figure S1) and additional figures (Figures S2 – S6)

366

demonstrating the background conditions and results. This information is available free of charge

367

via the Internet at http://pubs.acs.org/.

368 369

Author Contributions

370

DFM conceived the study. NB measured transect data in 2010, 2011. PF installed and treated

371

methane and CTD time series data. SF, PB, KP, DFM organized and conducted field campaigns.

372

MS assisted with 2010, 2011 field campaigns, supervised chemical measurements, and provided

373

partial funding for 2010 and 2011 field work. PB, SF, AL, DFM analyzed flux and time series

374

data. DFM and SF wrote the manuscript and developed figures. All authors contributed to

375

discussion and input to the manuscript. All photographs were taken by SF, MS, and DFM.

376 377

Competing financial interests

378

There are no competing financial interests except for P. Fietzek, who is affiliated with

379

Kongsberg Maritime Contros, the manufacturer of the methane sensor deployed in 2011. We

380

independently validated the sensor measurements with gas chromatography analysis

381

at GEOMAR, and therefore we are confident of the objectivity of the results.

382 383 384


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385

Funding Sources

386

DFM was partially supported by the Leibniz-Institute of Freshwater Ecology and Inland

387

Fisheries (IGB) Fellowship Program in Freshwater Science. SF was founded by the Swiss

388

National Science Foundation Mobility Stipends (PBEZP2-129527 and PAOOP2-142041).

389

Further funding for the study was provided by the German Research Foundation (LO 1150/5-1).

390 391

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