Aquatic ecosystem is the most important sources of greenhouse gases. However, the uncertainty in estimating the gas flux of water gas interface has not yet been paid attention to by using the linear regression (LR) model in the static floating box method (SFC).This study in Xiangxi Bay of Three Gorges reservoir, using closed static floating box  greenhouse gas analyzer continuous and realtime observation of the gas water interface of methane and carbon dioxide, and through software for fitting the monitoring data fitting. The comparison and analysis of the linear regression (LR), two regression (QR) and exponential regression (ER) fitting results of three kinds of models, the results show that it can better fit the static floating box gas concentration change with time nonlinear regression model, to get closer to the real gas water interface gas flux. This paper argues that the use of linear regression (LR) model to simulate the air interface of the gas flux of the obtained results are largely underestimated, the method of methane and carbon dioxide gas flux estimates averaged about 77% and 80% of the measured value. Moreover, in most cases, the effect of the exponential fit model is better than that of the two fit model, while the two regression model has no physical meaning in terms of the fitting coefficients, and is not applicable to the estimation of gas flux theoretically.

Key words：Static floating chamber; Gas flux estimation; Fitting model；Nonlinear fitting