In response to the problem of finding a practical, robust, and efficient optimization algorithms in hydrological simulation forecasting and determining the global optimal solution of parameters based on them, the Wucha section, a typical control section in the Qijiang River Basin, was selected as the research object. Four optimization algorithms, GA、SCE-UA、CMA-ES、PSO, were selected to calibrate the convergence parameters of the distributed Xin'anjiang model. The parameter calibration performance of the algorithm was evaluated from four aspects:effectiveness, stability, time consumption, and efficiency. The results show that CMA-ES algorithm has the best optimization effect and the least time consumption under the same number of iterations. SCE-UA algorithm has the highest stability and efficiency, but its time consumption significantly increases with the increase of iteration times. PSO algorithm has relatively better effectiveness and efficiency, but the stability is the worst. GA algorithm takes relatively less time and has the worst optimization effect and efficiency. The comprehensive property is ranked from best to worst as CMA-ES, SCE-UA, PSO, and GA algorithms.