In order to compare and study the application of typical parameter optimization algorithms in Xin"anjiang model in detail, four typical optimization algorithms are selected: Adaptive Genetic Algorithm (AGA), Improved Particle Swarm Algorithm (IPSO), SCE-UA and Bayesian Optimization Algorithm ( BOA), the deterministic coefficient is the value of the objective function, each algorithm operates 50 times independently, and each iteration 300 times. The parameters of the Xin"anjiang model are calibrated in the Chengcun watershed of Huangshan City, Anhui Province. The comparison results show that: AGA convergence value The average level and concentration are better, but the convergence speed and stability are poor; IPSO has the best application effect in all algorithms, but it is sensitive to the initial values of parameters and has a large amount of calculation; SCE-UA has better stability and convergence speed, but The average level of convergence and the degree of concentration are poor; the BOA application effect is poor, but its calculation is small and the calculation speed is fast. Therefore, when applying IPSO to optimize the parameters of the Xin"anjiang model, the BOA optimization results can be used as the initial parameter values of IPSO. When applying AGA or SCE-UA to calibrate Xin"anjiang parameters, both can be used in combination.