To analyze pumping test data can supply a new method for estimating aquifer parameters. The particle swarm algorithm improved in terms of particle diversity increased convergence speed and accuracy of the algorithm. The improved particle swarm optimization algorithm was applied to estimate the aquifer parameters. The calculated results were compared with the other methods , and the estimated values of parameters under different initial scopes were analyzed and discussed. The results showed that, the relative errors of improved particle swarm algorithm (which were 7.3% and 4.5%, respectively) were smaller than the relative errors of the other methods, and the objective function value was also relatively smaller, reaching 0.335×10-5; For different initial parameter ranges, the improved algorithm obatined a satisfactory parameter estimation result and maintained a high rate of optimization search. Based on pumping test data, the results of improved particle swarm optimization algorithm for estimating aquifer parameters were more effective and reliable with fast convergence speed, strong optimization ability and good stability.