The study of methane (CH₄) emission flux from paddy fields is an important part and hot topic in the current study of carbon cycle in terrestrial ecosystems. The multi-time scale characteristics of CH₄ emission flux and its influencing factors [gross primary productivity (GPP), latent heat flux (LE), air temperature (TA), soil temperature (TS)] in paddy fields were analyzed based on wavelet analysis and eddy covariance flux observation data. The CH₄ emission flux and its influencing factors of paddy field ecosystems had obvious seasonal variation characteristics. The CH₄ emission flux from paddy fields in the rice growing season showed obvious single-peak diurnal variation characteristics, while the CH₄ emission flux from paddy fields in the non-rice growing season was low, and the diurnal variation characteristics were not obvious. GPP, LE, TA and TS showed obvious single-peak diurnal variation patterns. Based on continuous wavelet transform and wavelet variance curve analysis, CH₄ flux, GPP, LE, TA and TS had an obvious 1-day cycle during the rice growing season (July—November), while GPP, LE, TA and TS also had a half-day cycle, and TA and TS also had a long-term cycle of 4 days. From the cross wavelet transform and wavelet coherence spectrum analysis, the resonance period between CH₄ flux and GPP, LE, TA and TS was about 1 day. There was a significant resonance relationship in this frequency domain, and oscillation cohesion and coherence were the strongest. However, in the high-frequency band area, there was also a secondary resonance period of about 0.5 days between CH₄ flux and GPP, LE, TA and TS. In addition, in other frequency bands, the resonance energy of CH₄ flux and GPP, LE, TA and TS was low, but in the resonance period of 4 days and 7-10 days, CH₄ flux had good coherence with TA and TS from mid-August to mid-October. This study analyzed the multi-time scale characteristics of CH₄ flux and its influencing factors from paddy fields and would provide a scientific reference for studying the quantitative relationship between CH₄ flux and its driving factors at different time scales.

multiple time scales  /  paddy ecosystem  /  methane flux  /  wavelet analysis