Methane and carbon dioxide dynamics affected by water-level fluctuations in a shallow lake: Implications for wetland restoration

<p>Shallow lake was characterized by distinct hydrology, biochemistry and ecology that influence the carbon balance. This study explored methane and carbon emission responses to water level fluctuation in shallow lake, and also addressed its legacy for wetland restoration. This study used the process-based biogeochemical model, denitrification-decomposition (DNDC) model to simulate the alteration of methane and carbon emission with water level fluctuation in the Baiyangdian Lake (BYD Lake). The results showed: (i) compared with the observed carbon flux, the DNDC model can presented a suitable results in capturing the dynamics of methane and carbon dioxide, and the daily rate of carbon dioxide and methane emission showed sensitive to water fluctuation when it ranged from -10 cm to 10 cm; (ii) for the carbon dioxide, the annual flux showed a decline trend when the duration prolonged from 10 days to 40 days, and then an increasing trend while the duration prolonged to 90 days furtherly, with a lowest flux when the duration is 40 days, while for the methane, annual emission increased with inundation lasting time and the flux changing from -2.27 kg C/ha/y to 1.57 kg C/ha/y; and (iii) The flux of carbon dioxide and methane increased when water level fluctuation frequency increased, for a certain water level fluctuation frequency, carbon dioxide flux is lowest in January and February, and methane flux is negative from December to March of the following year. All of these results indicated that water level fluctuation (e.g., magnitude, duration and frequency) affected the carbon dioxide and methane flux, which will help to reduce the emission of carbon dioxide and methane by regulating ecological water transfer.</p><p><strong>Keywords: </strong>shallow lake, carbon emission; DNDC; water level fluctuation</p><p><strong>Acknowledgments</strong></p><p>This study was supported by the National Key R&D Program of China (No. 2018ZX07110001, No. 2017YFC0404505) and the National Natural Science Foundation of China (No. 51579008).</p>