Past research shows that physically based distributed hydrological model has the advantage of better representing the basin characteristics and the hydrologic processes to potentially simulate/predict river basin flood. But how to physically derive model parameters directly from terrain data and to acquire channel cross-sectional size are still difficult jobs in physically based distributed hydrological modeling that prevented its operational application in river basin flood forecasting. To deal with these challenges, this paper first presents a physically based, distributed hydrological model for river basin flood forecasting/simulation, called the Liuxihe model. Then a method for estimating channel cross-sectional size was proposed that utilizes a readily accessible public data set acquired by remote sensing techniques, which could be employed by other physically based, distributed hydrological models also. Finally, a method for deriving model parameters was proposed that adjusts model parameters with initial model parameters derived directly from terrain data that is completely different from parameter calibration in lumped model, which also can be used in other physically based, distributed hydrological models. A medium-sized river basin in southern China was tested with the above model and methods, and 13 collected flood events were simulated with reasonable model performances. It can be concluded that parameter adjustment is still necessary and vital to improve physically based, distributed hydrological performance as there is no systematic and global referencing in deriving model parameters from terrain data. For the Liuxihe model, the highly sensitive model parameter is water content at saturation condition; the sensitive parameters are water content at field condition, river channel Manning's coefficient, soil thickness, soil porosity characteristics, soil hydraulic conductivity, and hillslope Manning's coefficient; and the less sensitive parameters are potential evaporation, evaporation coefficient, underground water recession coefficient, and water content at wilting condition. The results also showed that the method proposed for estimating river channel cross-sectional size is reasonable and could be applied widely, and the proposed Liuxihe model works well in simulating river basin flood events, thus presenting further evidence of the potential use of the physically based distributed hydrologic model for the operational use of simulating/predicting river basin floods.