ADCP online flow gauging system can be established for the tidal reach in the lower Yangtze River with changeable hydraulicfactors to collect index velocity in real time, and determine mean velocity at a cross-section by using appropriate method,so as to realize flood reporting and reorganizing the flow in time. Multiple linear regression analysis and BP neural network havethe characteristics of clear principle and convenient application. The fitting precision and prediction accuracy of the two models un -der different circumstances were analyzed based on the observed data at the Nanjing Hydrological Experimental Station since 2014to compare the advantages and disadvantages of the two methods above in the calculation of mean section velocity. The resultsshow that both of the two models have good effectiveness, accuracy and stability, and fitting precision is related to the monitoringindex selected for the model. If the single index velocity is adopted only, the results of BP neural network model are obviously su -perior to those of multiple linear regression model. Meanwhile, both of the two models can forecast mean section velocity well, andBP neural network is more adaptable.