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. 2014 Mar 24;4:4449. doi: 10.1038/srep04449

Methane formation and consumption processes in Xiangxi Bay of the Three Gorges Reservoir

Chenghao Wang 1, Shangbin Xiao 1,2,a, Yingchen Li 1, Huayao Zhong 1, Xuechen Li 1, Feng Peng 1
PMCID: PMC5394752  PMID: 24658370

Abstract

Indoor simulation experiment was carried out to evaluate the formation and consumption rates of methane (CH4) in Xiangxi Bay of the Three Gorges Reservoir (TGR), China. The results show that both the CH4 formation and consumption rates were significantly positively correlated with temperature. CH4 efflux decreased with rising temperature due to its potential increasing oxidation rate. CH4 oxidation in surface sediments accounted for 51.8% of the total production and it even reached to 77.4% at 35°C. The methane oxidation rate in water column ranged from 1.26 to 4.65 mg/(m2h), of which the average and greatest rate accounted for 46.7% and 73.9% of CH4 production respectively under the condition of 30 m water column and 35°C. The methane oxidation may increase by 41.04 mg/(m2h) under average water level of TGR (160 m), and most methane resulted from sediments can be oxidized in the water column.

CH4 is an important atmospheric contaminant contributing to the greenhouse effect1. Owing mainly to anthropogenic production, atmospheric methane concentrations have doubled from 850 ppbv to approximately 1750 ppbv over the last 150 years.

Hydropower resulted from reservoirs has been thought as a kind of clean and renewable energy. However, the conversion of land surface areas saturated by oxygen to anoxic sediments overlain by water results in CH4 emissions from reservoirs under certain conditions2. Hydroelectric reservoirs do not have a negligible carbon footprint, in other words, they are not carbon-free3. CH4 emissions from hydroelectric reservoirs might have an influence on the anthropogenic CH44,5,6,7,8,9,10,11. Moreover, some reservoirs emit more carbon than fossil-fuel based electricity12. Other greenhouse gas (GHG) emissions like CO2 and N2O are also found in many lakes and reservoirs13, although seasonal mean N2O fluxes were generally low6.

At the very beginning, CH4 is exclusively formed in anaerobic environments10,14,15. This gas is then partially mineralized into CO2 through aerobic oxidation by methanotrophic bacteria in surface sediments or water column. Only the unoxidized parts escape to the atmosphere as CH4 emissions10,16. CH4 emissions from aquatic environments depend on both CH4 formation and CH4 oxidation rates, and the latter is also known as consumption process17. According to previous reports, CH4 emission from reservoirs not only linked to reservoir age and latitude3, but also related to both temperature and sediment characteristics (eg. C: N ratio). CH4 formation, which results from a temperature-controlled mineralization process of organic matter18, is more temperature sensitive than CH4 oxidation17. The rate of methanogenesis varies with sediment site and depth. It decreases with increasing sediment depth due to the number of methanogens in deeper sediment19. Moreover, substrate concentrations on temperature sensitivity of methanogenesis will also influence CH4 formation, and it reduces with decreasing substrate concentrations17,20. Further studies are also needed to explore the distribution of methanogens and methanotrophs under different environment conditions21.

The TGR, which is located in the subtropical zone and resulted from the biggest water-control projects in the world, is a huge and typical fluvial reservoir. However, the greenhouse gas fluxes from TGR were reported scarcely. Data reported varied greatly and resulted in a tremendous controversy22,23,24. This paper aims to quantitatively evaluate the processes of CH4 formation and consumption in Xiangxi Bay of TGR based on simulation experiment. The relationship between temperature and contributions of oxidation process in surface sediments and water column are reported here.

Results

Based on the experimental design, CH4 fluxes of Tube A, B and C respectively simulate CH4 efflux with oxidation in surface sediments and water column, CH4 efflux only with oxidation in surface sediments, and CH4 efflux process without aerobic oxidation (Fig. 1 & Table 1).

Figure 1. CH4 flux under different temperatures in Tube A, B and C.

Figure 1

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Tube A, B and C are experimental controls. CH4 fluxes in Tube A, B and C simulate CH4 formation with oxidation consumption of surface sediments and water column, CH4 formation only with oxidation consumption of surface sediments, and CH4 formation process without aerobic oxidation, respectively. CH4 flux didn't increase continuously during the rapid warming process except Tube C from 20 to 30°C, while it decreased continuously during the rapid natural cooling processes in all tubes. When the temperature remained constant, CH4 flux in each tube is fluctuating around a certain value.

Table 1. Variations of CH4 fluxes of three tubes.

Tube Maximum mg/(m2h) Minimum mg/(m2h) Average mg/(m2h) Standard deviation C.V
A 6.20 0.94 3.02 1.59 0.53
B 19.66 1.59 10.70 4.86 0.46
C 26.83 2.41 13.61 7.77 0.57
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A good correlation between CH4 flux and temperature for each tube (Fig. 2, Supplementary Table S1 & Supplementary Table S2) is observed here. During the rapid natural cooling process, CH4 flux decreased continuously in all tubes. However, CH4 flux didn't increase continuously with the rapid warming except Tube C, and the flux in Tube A and B decreased with temperature increasing from 20 to 30°C. When temperature remained changeless, CH4 flux in each tube fluctuated around a certain value.

Figure 2. Average CH4 flux vs. each constant temperature.

Figure 2

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The wave property and some experimental error effects can be weakened when we use average value. Meanwhile, CH4 consumption processes can be clear. CH4 flux of Tube C is higher than B except a high fluxes process at the beginning. On the whole, CH4 flux has a decline trend during this gaseous diffusion process when CH4 emits from sediments to atmosphere via surface sediments and water.

In general, the CH4 efflux is the biggest in Tube C, and is the smallest in Tube A. The latter may be due to CH4 oxidation in surface sediments and its water column.

When temperature remained changeless, the CH4 flux changed little (Fig. 2). There is a positive correlation between the CH4 flux and temperature according to Fig. 1 and Fig. 2 if we rule out the decreasing CH4 with the rapid warming from 20 to 30°C.

Discussion

The Bunsen solubility coefficient for CH4 is 0.03–0.05, which is expressed as ml of CH4 (STP, Standard Temperature and Pressure) dissolved in 1 ml of H2O25. So the quantity of dissolved CH4 can be ignored here. There is a positive correlation in some degree between the CH4 flux and temperature (Supplementary Table S1). However, the correlation coefficients of Tube A and B (0.30 ~ 0.40) are lower than that of Tube C (>0.90), which may indicate that the CH4 production in Tube C is significantly positively correlated with temperature. Better correlation between the CH4 flux and temperature is observed when the average values of both are used (Supplementary Table S2).

CH4 fluxes of Tube C are higher than B on the whole except at the beginning of rapid warming period. The difference between CH4 fluxes of Tube C and B resulted from the aerobic CH4 oxidation in surface sediments. Average CH4 fluxes were used during rapid warming process from 5 to 20°C to evaluate this process. The decreasing CH4 flux, which resulted from its oxidation, is shown as Fig. 3. The CH4 oxidation rate is less sensitive to temperature according to previous reports17,26. However, our results do show a significantly positive correlation between the CH4 oxidation rate and temperature, and the correlation coefficient is 0.94 (it can even be improved to 0.96 when average values are used, Fig. 3 & Supplementary Table S3).

Figure 3. Changes of CH4 oxidation amount with temperature in surface sediments and water column (initial and average values).

Figure 3

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Average value was also used during the rapid warming process from 5 to 20°C. The difference between fluxes of Tube C and B is the decrease of CH4 flux due to oxidation consumption in surface sediments, while the difference between B and A results from oxidation consumption in water column. Average values of CH4 fluxes were used during rapid warming process from 5 to 20°C. The change of decrease of CH4 flux can be interpreted as oxidation amount. Oxidation rate, which is the oxidation amount in unit time, is positively correlative to temperature due to the temperature-controlled formation process. Faster increase rate of oxidation process results in a decrease process of the total CH4 emission.

The linear fitting between the CH4 oxidation rate (initial value and average value) with temperature have different slopes (Supplementary Table S3). During each period with changeless temperature, CH4 efflux varies little, so the average value is used here in order to better understand the potential process in CH4 formation and oxidation.

CH4 fluxes of Tube B are higher than that of Tube A on the whole except in the beginning. Therefore, its average value was also used during the rapid warming process from 5 to 20°C. The CH4 flux difference between Tube B and A resulted from extra CH4 oxidation in water column of Tube A. A positive correlation between CH4 oxidation rate in water column and temperature (R = 0.68) was observed here, and the correlation coefficient can be improved to 0.90 when the average values were used (Fig. 3 & Supplementary Table S4).

CH4 oxidation rate in both surface sediments and water column increased with temperature. A high correlation coefficient between CH4 oxidation rate and its fluxes of Tube A and B in the warming process (20–30°C) is observed (Supplementary Table S5). Increased CH4 oxidation rate under high temperature is bigger than increased CH4 formation rate17,18, which results in the similar decreasing CH4 flux in Tube A and B during the warming process.

The average CH4 oxidation in surface sediments accounts for 51.8% of the total CH4 production with a range of 26.1–77.4%. Therefore, CH4 oxidation played a vital role in controlling the CH4 flux2. Considering the different CH4 consumption contribution of water at different water temperatures (Table 2), average CH4 oxidation in water column accounts for about 46.7% of the total oxidation, and the value reaches to 73.9% when temperature is 35°C. Our data accords well with previous reports, in which water column oxidized 51 ~ 80% of the CH4 produced in freshwater lakes27, and also played a fundamental role in regulation of CH4 emissions. In Lake Kasumigaura, CH4 oxidation consumed an annual average of 74% of dissolved CH4 in the water column. This lake is very shallow with a maximum depth of only 7.3 m and a mean depth of 3.8 m14.

Table 2. CH4 consumption contribution rate of water at different water temperatures.

Water temperature(°C) 5 10 15 20 25 30 35
C (mg/(m3·h)) 0.09 0.73 0.76 1.22 2.23 2.07 2.47
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The bigger the reservoir water depth is, the more CH4 is oxidized in water column. The change amplitude of water depth in the TGR is about 30 m when its water level changes from 145 m to 175 m28, which can influence CH4 consumption largely(Table 3). The oxidation can be increased by 41.0 mg/(m2·h) in 30 m water column when the average CH4 oxidation contribution rate, 1.37 mg/(m3·h), was used to calculate the CH4 oxidation in water column.

Table 3. CH4 consumption rate in water column at different water depth.

Water depth(m) 0 5 10 15 20
C (mg/(m2·h)) Values range 0 0.43 ~ 12.36 0.86 ~ 24.71 1.29 ~ 37.07 1.72 ~ 49.42
Average value 0 6.84 13.68 20.52 27.36  
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Here, higher temperature is conducive to decreasing the CH4 flux in Xiangxi Bay of TGR, which is quite different from the results from eight lakes of boreal and northern regions in central Sweden17. According to the latter, CH4 emissions would increase if the climate gets both warmer and more variable. Further work is expected to explore the potential mechanism between CH4 formation and oxidation in fresh aquatic systems. Many factors can determine various CH4 formation and consumption process27. For instance, the trophic state of water, state method, sediments origin, climatic region and so on. Whether or not consumption rate dominates the whole process will lead to the opposite results.

Deeper water and higher temperature, whether in summer or winter, can decrease the CH4 emission in Xiangxi Bay of TGR according to the results of our research. CH4 effluxes range from 1.26 to 4.65 mg/(m2h) under different water depth and temperature conditions. The highest CH4 oxidation rates are located at oxic/anoxic interfaces where opposite fluxes of CH4 and O2 occur29. A large fraction of CH4 diffusing from the anoxic zone is oxidized at the sediment surface (66 ~ 95%29,30,31) and in the water column (45 ~ 100%32). CH4 consumption in Xiangxi Bay of the TGR is mostly determined by the surface sediments oxidation effect of about 51.8%, and water bodies of about 46.7%.

Xiangxi Bay of TGR has an approximate CH4 flux to the Middle Yangtze River24, both of which are in the subtropical climate zone. CH4 fluxes in the TGR are much smaller than those data from water bodies of tropical zone such as Petit Saut and Miranda33,34, but larger than those from the reservoirs in temperate zone and frigid zone such as Quebéc and Lokka6,11. This verifies that CH4 emissions were correlated to latitude3.

Xiangxi Bay of TGR is a human-made freshwater system, and its CH4 flux may decrease as time goes on according to the negative correlation between gas flux and reservoir age3. At the same time, the earth is experiencing a global warming process obviously, particularly after 1980s35. The air temperature of TGR area also has a rising tendency36, which increased by 0.2–1.0°C in 2003–2009 when compared to the average value in 1996–200237. Thus, CH4 flux in Xiangxi Bay of TGR may decline to some degree over the next decade.

Methods

TGR is an artificial fresh river-channel reservoir which formed after the construction of the Three Gorge Project (TGP) with an area of 1084 km2. It has a total reservoir capacity of 39.3 billion m3 with a normal water level elevation of 175 m38. The reservoir is located in a sub-tropical continental monsoon climatic region. The spring has a plenty of rain with temperature changing frequently; midsummer drought occurs frequently in summer with burning hot and concentrated rainfall; the steady raining is continual in autumn and winter; moreover, the winter also has early frost. The annual change range of water level is about 30 m which is influenced by flood control operation of TGR39. TGR has a steep-sided gorge characteristic rather than a relatively shallow basin characteristic when compared with the boreal and tropical reservoirs40.

Xiangxi River, as the largest tributary flowing into the Yangtze River in Hubei of TGR area, is located in the western Hubei province of China41. The river is 94 km and its estuary is about 32 km from the dam site. The geographical coordinates of the River are 30°57′ ~ 31°34′N, 110°25′ ~ 111°06′E42,43.

Surface sediments and water samples used here were both taken from the Xiangxi Bay. The sediments were mixed gently in order to decrease spatial variability of sediments inside and the destruction of the microbial communities. These communities are the main part of CH4 formation process44,45. Sediments used for experiment were well mixed46,47 and equally divided into thirds (each weighed about 2.9 kg), and then were transferred into three 1.0 m long acrylic round tubes (signed A, B and C, and the length of sediments in each tube was 35 cm). The free space of tubes was filled with water, and the sediments were immersed more than 72 hours prior to the experiment.

Tube A, B and C were designed to simulate three different situations from CH4 formation to oxidation. Tube C is designed to simulate CH4 formation without any aerobic oxidation. Tube C was filled with pure nitrogen to maintain anaerobic condition in Tube C 3 days ago before the experiment. Then pure nitrogen flow was injected into the tube continually for 12 hours so as to avoid CH4 accumulating and equilibrate the pressure inside with outside atmospheric pressure before the experiment. Tube A is designed to simulate CH4 formation with oxidation in surface sediments and water column, and B is designed to simulate CH4 formation only with oxidation in surface sediments. Water was injected into Tube A to column of 27 cm before experiment in order to simulate CH4 oxidation in water column.

The whole experiment system consists of a big water tank with three tubes inside, electric heaters, a micro-pump, a few of pipes, some three-way and connecting pipes, some small fans, an air pump, barometers, stabilizer, gum stoppers and a greenhouse gas analyzer (Fig. 4). The Greenhouse Gas Analyzer (CH4, CO2, H2O) LGR (Los Gatos Research, USA, main technical parameters: CH4: 1 ppbv, CO2: 0.2 ppmv, H2O: 100 ppmv; the accuracy: <1%; measuring range: CH4: 0.1–20 ppmv, CO2: 200–4000 ppmv, H2O: 7000–70000 ppmv; precision is better than 1%) was used to measure the concentration of greenhouse gases in the tubes.

Figure 4. Experimental equipment layout.

Figure 4

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(a) The whole experiment system consists of a big water tank with electric heater (1), micro-pump (2), small fans (4), temperature transducers (5) and electronic thermometers TP3001 (6), some three-way and connecting pipes. The environment water (3) in the tank was darkened by ink to shield sediments from light. Three 1.0 m long acrylic round tubes were signed A, B and C as experimental controls, and the length of sediments from Xiangxi Bay (7) in each tube was 35 cm. Tube A also has a water column of 27 cm from Xiangxi Bay (8). All of these tubes were sealed by gum stoppers (9) with two small two measurement holes. Free space of Tube C was filled with pure nitrogen, while Tube A and B were filled with air. (b) Experimental equipment of Tube A. Three-way pipes, connecting pipes and other pipes connect the tube with nitrogen cylinder and LGR. The Greenhouse Gas Analyzer (CH4, CO2, H2O) LGR from Los Gatos Research was used to measure the concentration of greenhouse gases.

The continuous experiment process included a warming period and a cooling one, during which the temperature ranged from 5 to 35°C. In warming process, the temperature of 5, 10, 15, 20, 25, 30 and 35°C were maintained for about 3 hours. Micro-pump was used here to mix the water of tank well. The whole experiment lasted for more than 60 hours. Once the gas contents in each tube were measured, pure nitrogen was injected to lower the concentrations of CH4 and CO2 in the tube right away. The dissolve oxygen (DO) concentration of water in Tube A was measured every two hours. Average DO of the experiment was kept around 9.27 mg/L.

When calculating CH4 fluxes, a series of scattered points were fitted into a linear function model only when the R2 (squared correlation coefficient) is bigger than 0.995 in most cases. As an example, the diffusion rate (k)48 of CH4 in Tube C at 5°C is shown as Fig. 5.

Figure 5. The diagram illustrates the calculation of CH4 flux.

Figure 5

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The blue line is measured values. The black line is a trend line. The R2 (squared correlation coefficient) and linear formula of it is shown.

Supplementary Material

Supplementary Information

Supplementary Table S1-S5

srep04449-s1.pdf (72.1KB, pdf)

Acknowledgments

This work was sponsored by National Science Foundation of China (No. 41273110, 51079163) and State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences.

Footnotes

The authors declare no competing financial interests.

Author Contributions C.H.W. and S.B.X. prepared the primary manuscript and figures. Y.C.L. and X.C.L. prepared the simulation experiment. F.P. and H.Y.Z. collected the samples from Xiangxi Bay. All authors reviewed and discussed the manuscript.

References

  1. Wahlen M. et al. Carbon-14 in methane sources and in atmospheric methane: the contribution from fossil carbon. Science 245, 286–290 (1989). [DOI] [PubMed] [Google Scholar]
  2. Venkiteswaran J. J. & Schiff S. L. Methane oxidation: isotopic enrichment factors in freshwater boreal reservoirs. Appl. geochemistry 20, 683–690 (2005). [Google Scholar]
  3. Barros N. et al. Carbon emission from hydroelectric reservoirs linked to reservoir age and latitude. Nat. Geosci. 4, 593–596 (2011). [Google Scholar]
  4. Galy-Lacaux C. et al. Gaseous emissions and oxygen consumption in hydroelectric dams: A case study in French Guyana. Global Biogeochem. Cycles 11, 471–483 (1997). [Google Scholar]
  5. Galy-Lacaux C., Delmas R., Kouadio G., Richard S. & Gosse P. Long-term greenhouse gas emissions from hydroelectric reservoirs in tropical forest regions. Global Biogeochem. Cycles 13, 503–517 (1999). [Google Scholar]
  6. Huttunen J. T. et al. Fluxes of CH4, CO2, and N2O in hydroelectric reservoirs Lokka and Porttipahta in the northern boreal zone in Finland. Global Biogeochem. Cycles 16, 1003 (2002). [Google Scholar]
  7. Keller M. & Stallard R. F. Methane emission by bubbling from Gatun Lake, Panama. J. Geophys. Res. 99, 8307–8319 (1994). [Google Scholar]
  8. Matvienko B. et al. Gas release from a reservoir in the filling stage. Verh. Int. Ver. Theor. Angew. Limnol./Proc. Int. Assoc. Theor. Appl. Limnol./Trav. Assoc. Int. Limnol. Theor. Appl. 27, 1415–1419 (2001). [Google Scholar]
  9. Rosa L. P. & Schaeffer R. Greenhouse gas emissions from hydroelectric reservoirs. Ambio. Stockholm 23, 164–165 (1994). [Google Scholar]
  10. Soumis N., Duchemin É., Canuel R. & Lucotte M. Greenhouse gas emissions from reservoirs of the western United States. Global Biogeochem. Cycles 18, GB3022 (2004). [Google Scholar]
  11. Tremblay A. & Bastien J. Greenhouse gases fluxes from a new reservoir and natural water bodies in Québec, Canada. Verh. Internat. Verein. Limnol 30, 866–869 (2009). [Google Scholar]
  12. Kemenes A., Forsberg B. R. & Melack J. M. CO2 emissions from a tropical hydroelectric reservoir (Balbina, Brazil). J. Geophys. Res.: Biogeosci. (2005–2012) 116, G03004 (2011). [Google Scholar]
  13. Hirota M., Senga Y., Seike Y., Nohara S. & Kunii H. Fluxes of carbon dioxide, methane and nitrous oxide in two contrastive fringing zones of coastal lagoon, Lake Nakaumi, Japan. Chemosphere 68, 597–603 (2007). [DOI] [PubMed] [Google Scholar]
  14. Utsumi M. et al. Oxidation of dissolved methane in a eutrophic, shallow lake: Lake Kasumigaura, Japan. Limnol. Oceanogr. 43, 471–480 (1998). [Google Scholar]
  15. Utsumi M. et al. Dynamics of dissolved methane and methane oxidation in dimictic Lake Nojiri during winter. Limnol. Oceanog r. 43, 10–17 (1998). [Google Scholar]
  16. Scranton M. I., Crill P., de Angelis M. A., Donaghay P. L. & Sieburth J. M. The importance of episodic events in controlling the flux of methane from an anoxic basin. Global Biogeochem. Cycles 7, 491–507 (1993). [Google Scholar]
  17. Duc N. T., Crill P. & Bastviken D. Implications of temperature and sediment characteristics on methane formation and oxidation in lake sediments. Biogeochemistry 100, 185–196 (2010). [Google Scholar]
  18. Gudasz C. et al. Temperature-controlled organic carbon mineralization in lake sediments. Nature 466, 478–481 (2010). [DOI] [PubMed] [Google Scholar]
  19. Zeikus J. & Winfrey M. Temperature limitation of methanogenesis in aquatic sediments. Appl. Environ. Microbiol. 31, 99–107 (1976). [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Westermann P. Temperature regulation of methanogenesis in wetlands. Chemosphere 26, 321–328 (1993). [Google Scholar]
  21. Semrau J. D., DiSpirito A. A. & Yoon S. Methanotrophs and copper. FEMS Microbiol. Rev. 34, 496–531 (2010). [DOI] [PubMed] [Google Scholar]
  22. Chen H. et al. Methane emissions from newly created marshes in the drawdown area of the Three Gorges Reservoir. J. Geophys. Res. 114, D18301 (2009). [Google Scholar]
  23. Qiu J. Chinese dam may be a methane menace: Wetlands around Three Gorges produce tonnes of the greenhouse gas. Nature 29; 10.1038/news.2009.962 (2009). [DOI] [Google Scholar]
  24. Zhao J., Zhang G., Wu Y. & Yang J. Distribution and emission of methane from the Changjiang. Environ. Sci. 32, 18 (2011). [PubMed] [Google Scholar]
  25. Wiesenburg D. A. & Guinasso Jr N. L. Equilibrium solubilities of methane, carbon monoxide, and hydrogen in water and sea water. J. Chem. Eng. Data 24, 356–360 (1979). [Google Scholar]
  26. Segers R. Methane production and methane consumption: a review of processes underlying wetland methane fluxes. Biogeochemistry 41, 23–51 (1998). [Google Scholar]
  27. Bastviken D., Cole J. J., Pace M. L. & Van de Bogert M. C. Fates of methane from different lake habitats: Connecting whole-lake budgets and CH4 emissions. J. Geophys. Res. 113, G02024 (2008). [Google Scholar]
  28. Yang Z., Liu D., Ji D. & Xiao S. Influence of the impounding process of the Three Gorges Reservoir up to water level 172.5 m on water eutrophication in the Xiangxi Bay. Sci. China Technol. Sci. 53, 1114–1125 (2010). [Google Scholar]
  29. Borrel G. et al. Production and consumption of methane in freshwater lake ecosystems. Res. Microbiol. 162, 832–847 (2011). [DOI] [PubMed] [Google Scholar]
  30. Bosse U., Frenzel P. & Conrad R. Inhibition of methane oxidation by ammonium in the surface layer of a littoral sediment. FEMS Microbiol. Ecol. 13, 123–134 (1993). [Google Scholar]
  31. Frenzel P., Thebrath B. & Conrad R. Oxidation of methane in the oxic surface layer of a deep lake sediment (Lake Constance). FEMS Microbiol. Lett. 73, 149–158 (1990). [Google Scholar]
  32. Bastviken D., Ejlertsson J. & Tranvik L. Measurement of methane oxidation in lakes: a comparison of methods. Environ. Sci. Technol. 36, 3354–3361 (2002). [DOI] [PubMed] [Google Scholar]
  33. Abril G. et al. Carbon dioxide and methane emissions and the carbon budget of a 10-year old tropical reservoir (Petit Saut, French Guiana). Global Biogeochem. Cycles 19, GB4007 (2005). [Google Scholar]
  34. Tremblay A., Varfalvy L., Roehm C. & Garneau M. Greenhouse gas Emissions-Fluxes and Processes: hydroelectric reservoirs and natural environments. (Springer, Berlin; 2005). [Google Scholar]
  35. Murray J. C. & Colle B. A. The spatial and temporal variability of convective storms over the northeast United States during the warm season. Mon. Weather Rev. 139, 992–1012 (2011). [Google Scholar]
  36. Yao Y. et al. Changes of meteorological parameters and lightning current during water impounded in Three Gorges area. Atmos. Res. 134, 150–160 (2013). [Google Scholar]
  37. Xua X., Tan Y. & Yang G. Environmental Impact Assessments of the Three Gorges Project in China: Issues and Interventions. Earth-Sci. Rev. 124, 115–125 (2013). [Google Scholar]
  38. Guoshuai L., Kan Y., Ran Z. & Jiao Z. Application of Genetic Algorithm and Annealing Genetic Algorithm in Short-term Optimal Operation and Economical Operation of Three Gorges Cascade. Proced. Eng. 28, 81–84 (2012). [Google Scholar]
  39. Huang Y. Study on the Formation and Disappearance Mechanism of Algal Bloom in the Xiangxi River Bay at Three Gorges Reservoir (in Chinese), Ph. D. Theses. Yangling: Northwest A&F Univ., 57–60 (2007). [Google Scholar]
  40. BF W. Spatial and temporal patterns of greenhouse gas emissions from Three Gorges Reservoir of China. Biogeosciences 10, 1219–1230 (2013). [Google Scholar]
  41. Huan W., Shuan H. & Hongbing D. A preliminary assessment on the Xiangxi River ecosystem services. Acta Ecol. Sinica 26, 2971–2978 (2006). [Google Scholar]
  42. Tang T., Li D., Pan W., Qu X. & Cai Q. River continuum characteristics of Xiangxi River. Chin. J. Appl. Ecol. 15, 141 (2004). [PubMed] [Google Scholar]
  43. Ye L., Li D., Tang T., Qu X. & Cai Q. [Spatial distribution of water quality in Xiangxi River, China]. Chin. J. Appl. Ecol. 14, 1959 (2003). [PubMed] [Google Scholar]
  44. Dannenberg S., Wudler J. & Conrad R. Agitation of anoxic paddy soil slurries affects the performance of the methanogenic microbial community. FEMS Microbiol. Ecol. 22, 257–263 (1997). [Google Scholar]
  45. Metje M. & Frenzel P. Effect of temperature on anaerobic ethanol oxidation and methanogenesis in acidic peat from a northern wetland. Appl. Environ. Microbiol. 71, 8191–8200 (2005). [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Fahrner S., Radke M., Karger D. & Blodau C. Organic matter mineralisation in the hypolimnion of an eutrophic Maar lake. Aquat. Sci. 70, 225–237 (2008). [Google Scholar]
  47. Kiene R. P. Microbial production and consumption of greenhouse gases: Methane, nitrogen oxides and halomethanes (eds Rogers, J. E. & Whitman,W. B.). 111–146 (American Society for Microbiology, Washington DC; 1991). [Google Scholar]
  48. Lambert M. & Fréchette J.-L. Analytical techniques for measuring fluxes of CO2 and CH4 from hydroelectric reservoirs and natural water bodies. Greenhouse Gas Emissions–Fluxes and Processes, 37–60; 10.1007/978-3-540-26643-3_3 (Springer, Berlin Heidelberg; 2005). [DOI] [Google Scholar]

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Supplementary Materials

Supplementary Information

Supplementary Table S1-S5

srep04449-s1.pdf (72.1KB, pdf)

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