The unit hydrograph is a simplified way to understand how a watershed responds to rainfall and offers a practical approach for flood forecasting. By approximating real-world watershed processes as a time-invariant linear hydrologic system, Guo turns the unit hydrograph to General Unit Hydrograph (GUH). The traditional runoff hydrological models for flood forecasting require a large number of parameters and datasets. In order to reduce the complexity of flood forecasting and model parameters, a simple GUH model considering rainfall loss and pre-flow is constructed in this study, combining with the Multiple Objective Particle Swarm Optimization (MOPSO) algorithm for parameters optimization. Taking Yuecheng Basin and Jiuzhou Basin as the study basins, different combinations of flood forecasting are constructed according to the improved GUH model、SCS-CN model and Nash unit hydrograph for comparison. The applicability of the model in flood forecasting in small and medium-sized basins is evaluated, and the forecasting accuracy of the improved GUH model at different lead times is discussed. The results showed that: （1）The improved GUH model"s forecasting accuracy was superior to two other runoff hydrological models.（2）The improved GUH model reached a Category II forecast level at both the Yuecheng Basin and Jiuzhou Basin，with mean coefficients of determination for Yuecheng and Jiuzhou Basin were 0.79 and 0.84, and pass rates of 90.91% and 83.33%, respectively;（3）The forecasting accuracy of the improved GUH model gradually decreased with an increase in lead times, but it still maintained a certain level of predictive performance when the lead times was less than four-hour. The improved GUH model, considering rainfall losses and pre-flow, had fewer parameters and a simple structure. It showed potential for flood forecasting and provided new insights for flood forecasting in small and medium-sized watersheds.