In order to quantitatively analyze and classify waterborne traffic flow complexity, a method of waterborne traffic flow complexity metric was proposed based on Lempel-Ziv algorithm and TOPSIS (technique for order preference by similarity to an ideal solution). Firstly, Lempel-Ziv algorithm was used to obtain the complexity eigenvalues of measured time sequences of waterborne traffic flow and other compared sequences (periodic sequence, logistic sequence, Henon sequence and random sequence). Secondly, the close degree of each sequence was calculated by using TOPSIS. The class of complexity was divided by those close degrees of compared sequences. At last, the complexity degree of each sequence was represented by close degrees of time sequences of waterborne traffic flow and the complexity class. This complexity metric was carried out on the waterborne traffic flow of south channel of the Yangtze River. Calculation result shows that the correlation coefficient of complexity close degree of waterborne ship traffic flow is 0.6981 with the number of ship traffic accidents, and 0.7692 with the downside traffic flow of standard ships, respectively. The change trend is basically consistent, so the complexity close degree can reflect the complexity of waterborne ship traffic flow. The close degrees of periodic sequence and random sequence are 0.0001 and 0.9999, respectively. Meanwhile, the close degrees of logistic sequence and Henon sequence are 0.4492 and 0.5377, respectively. The close degrees of logistic sequence and Henon sequence are greater than periodic sequence and and less than random sequence. The close degrees of waterborne traffic flow from July to November in 2013 are 0.8280, 0.8527, 0.8565, 0.8237 and 0.8107, respectively, the complexity of waterborne traffic flow is basically consistent. The values of waterborne traffic flow are far greater than those of periodic sequence, locate between the values of Henon sequence and random sequence, and are closer to the value of random sequence, which shows that the waterborne traffic system is neither periodic nor completely stochastic. The complexity class of time sequence of waterborne traffic flow is Level 1, showing high complexity.@en