Parameter calibration is essential for establishing and using a hydrological model. In multi-objectives hydrological calibra - tion, different weights of objective functions directly affect the calibration results, and how to determine the weights of different ob - jective functions is a key step of hydrological calibration. The HSPF (Hydrological Simulation Program-Fortran) model that is a typ - ical semi-distributed hydrological model was taken to study the effect of objective weights for different calibration functions on hy - drological simulation. The upstream watershed of the Niulanjiang River was selected as a case study to simulate runoff by the PEST-HSPF model, and the study was supposed to be a guide for parameter optimization of HSPF by automatic calibration approach. Through altering the objective function weights, the goodness of fit of the model was recorded to determine the impact of different weights on the performance of PEST-HSPF simulation. The results indicate that: (1) when the weight of single objective function (daily flow, month flow, hypercritical flow days) of PEST-HSPF rises, Nash coefficient of the model and the relative devia - tion present nonlinear variation response with a vast and unstable variation in value; (2) Higher prediction ability and less error can be obtained when the three weights of the objective functions are set within 1-10 orders of magnitude. The Nash coefficient can reach over 0.8 and the relative error is lower than 10%; (3)The weight of hypercritical flow days has a greater influence on the a - bility to prediction while the weight of daily flow has a greater influence on the fluctuation of relative deviation. When the weight of hypercritical flow days varies between 1 and 1000, the corresponding Nash coefficient is between 0.02 and 0.86; the relative error will change greatly when the weight of daily flow exceeds 30.