摘要:开展太湖流域农田稻季CH₄排放研究，深入了解稻田CH₄排放规律，为稻田CH₄减排、制定合理稻田管理措施提供科学依据。以太湖流域稻麦轮作农田为研究区域，运用涡度相关法观测其稻季CH₄通量变化，分析其通量变化特征及影响因子。结果表明：太湖流域典型稻麦轮作区稻季为CH₄的源，CH₄排放总量为28.95 g/m²，稻季CH₄通量日变化表现为无规则型与单峰型两种模式；稻季CH₄排放整体集中在水稻生长前期（81.61%）及中期（16.16%）、后期排放相对较弱（2.23%），返青期排放量较低（日均0.102 μmol m^-2 s^-1），分蘖期较强（日均0.451 μmol m^-2 s^-1），成熟期最低（日均0.006 μmol m^-2 s^-1）；模型所模拟的累计CH₄排放通量比累计测量CH₄通量低6.69%，较好地模拟了太湖流域稻田CH₄的排放，土壤温度、土壤水分、土壤电导率、摩擦风速可确认为太湖流域农田稻季CH₄排放的主要驱动因子。



Abstract:Methane emissions play a key role in global warming and climate change. The mechanism of methane emission in the paddy fields of the Taihu Lake Basin-a typical rice-wheat rotation region of China and also an area with one of the highest rates of land use change in the country-is still unclear, largely due to limited observation and the spatial heterogeneity of the environment. Eddy covariance, one of most popular approaches to observing methane flux, has many advantages, including long-term continuous observation, high frequency, and large monitoring range, without destruction of the original soil environment. We utilized the eddy covariance method to observe the methane flux in rice-wheat rotation paddy fields in the Taihu Lake Basin. The missing flux values were interpolated with the GA-BPNN model. The characteristics and influencing factors of methane flux were then analyzed, and a semi-empirical multiplicative model was built. The results showed that the rice-wheat rotation paddy fields were the main source of methane in the Taihu Lake Basin. During the observation period, the total amount of emitted methane was 28.95 g/m², and methane flux values varied in the range of 0-0.861 μmol m^-2 s^-1. The diurnal variation in methane flux during the rice season appears under two modes:irregular and unimodal. In the irregular mode, methane flux was unstable throughout the day, and in the unimodal mode, the emissions during the day were significantly higher than that at night. The emission of methane in the rice season is concentrated in the early and middle stages of rice growth, relatively weak in the later stage, relatively low in the green stage (0.102 μmol m^-2 s^-1 per day), strong in the tillering stage (0.451 μmol m^-2 s^-1 per day), and lowest in the maturity stage (0.006 μmol m^-2 s^-1 per day). The results of the analysis of various impact factors are as follows:The methane flux in the rice season increased exponential with air temperature and soil temperature at 10/20/40 cm depth (R²=0.589, 0.584, 0.521, 0.459, P<0.0001). Methane flux increased with increasing temperature. Methane flux showed a weak exponential relationship with soil moisture at 10/20 cm depth (R²=0.362, 0.372, P<0.0001). With the rise in soil moisture, methane flux increased. Methane flux has a quadratic relationship with soil moisture at a depth of 40 cm (R²=0.378, P<0.0001). When the soil moisture is less than 0.41 m³ m^-3, methane flux decreases with the increase in soil moisture, and when the soil moisture is greater than 0.41 m³ m^-3, methane flux increased with the rise in soil moisture. Methane flux showed a power relationship with soil conductivity at 10/20/40 cm depth (R²=0.309, 0.54, 0.439, P<0.0001). As the soil conductivity increases, the methane flux increases. Methane flux and friction wind speed are only significantly correlated on a half-hour scale. The methane flux estimated by the model 2 is 6.69% lower than measured flux. The model 2 well simulates the methane emission from paddy fields in the Taihu Lake Basin. The main driving factors of methane emission from paddy fields in the Taihu Lake Basin include soil temperature, soil moisture, soil conductivity, and friction wind speed.





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