Improving gap-filling performance for CH4 fluxes of eddy covariance data by combining marginal distribution sampling and machine learning algorithm over paddy fields

Accurate gap-filling CH4 fluxes from eddy covariance measurements over paddy fields is important in assessing agriculture carbon balance and greenhouse gas emission and therefore contribute to agriculture cleaner production. However, as a type of highly managed wetland, the mechanisms of CH4 emission from paddy field are different from those from natural wetlands. This study improved the methods to process CH4 fluxes data from paddy fields. Adding gross primary production (GPP) into the Moving Point test (MP) method enables it to calculate the threshold of friction velocity (U-c & lowast;) in the paddy fields. The order of calculated U-c & lowast; for all sites is: TWT (0.27 m s(-1)) > MSE (0.20 m s(-1)) > CRK (0.12 m s(-1)) > HRC (0.11 m s(-1)) > RIP (0.10 m s(-1)) > HRA (0.09 m s(-1)) > NC (0.08 m s(-1)) > CAS (0.05 m s(-1)). GPP is 2.5 h ahead of CH4 fluxes, incorporating the asynchrony phenomenon improves the gap-filling performance at all 8 sites, with the R-2 increases by 6.3 %-16.1 %, RMSE decreases by 8.0 %-26.8 %, MAE decrease by 10.5 %-25.2 %. Replacing soil moisture condition with the 'on-off switch' effect of water table only improves the gap-filling performance at CRK, HRA, HRC, MSE and NC sites, with the R-2 increase by 7.2 %, 8.1 %, 10.4 %, 3.8 %, 7.1 %, and the improvement of gap-filling accuracy was positively correlated with times of alternate wetting and drying cycles during the growing season. The gap-filling effect of six machine learning algorithms were in order: Adaboost > XGBoost > RF > BPNN > SVM and KNN, with the MDS method worse than the RF. By solving the uneven distribution of CH4 fluxes, integrating the MDS method into machine learning algorithm could improve the performance of gap-filling, with R-2 increased by 0.02-0.06, MAE decreased by 0.13 %-7.88 %. Overall, the study is benefit for data processing of CH4 fluxes over paddy fields.