<p>The application of PCSWMM software to construct airport flood model can provide effective prediction and management for airport flood disaster. Different from cities, airports have strict and special requirements in land use types, functional partition and drainage network layout. The airport flood model involves many parameters, and the sensitivity of the parameters has a great influence on the accuracy of results. It is very important to effectively identify and rank parameter sensitivity to improve the accuracy of the model. A new parameter sensitivity analysis method is proposed in this study, which couples partial correlation and Sensitivity-based Radio Tuning Calibration (SRTC) method. And nine parameters are selected to analyze the parameter sensitivity. It is concluded that Average Depth has two highly correlated parameters (Manning-N &gt; Conductivity), one moderately correlated parameter, and two lowly correlated parameters by using partial correlation-SRTC coupling method. Total Inflow has three highly correlated parameters (N-perv &gt; Initial Deficit &gt; Conductivity), and the remaining six parameters are uncorrelated parameters. The new method proposed in this study can lay a good modeling foundation and theoretical support for the analysis and research of airport flood disaster.</p>