Abstract: Flood forecasting in plain river networks has always been a challenging issue in hydrology, especially with the significant impact of human activities. In order to better simulate the hydrological cycle in the basin and address the challenges in engineering applications, this paper proposes a novel distributed architecture hydrological model. The model has distributed characteristics, allowing for flexible selection of the most suitable hydrological feature units based on basin characteristics and requirements, thereby supporting the precise and theoretical study of different hydrological feature units. To achieve real-time forecasting functionality, this paper also developed database coupling technology, large-scale river network real-time correction technology, and hydraulic engineering scheduling technology. Based on this, a distributed architecture model of the Taihu Lake basin was established, which was generalized, and the model parameters were calibrated using 2016 actual data. By conducting real-time forecasts of Taihu Lake water levels with lead times of 1 d, 2 d, and 3 d, the results of this study can basically reflect the actual water flow conditions in the Taihu Lake basin of the plain river network area. In summary, the distributed architecture hydrological model method proposed in this paper has not only been verified in terms of scientificity but also has feasibility in implementation technology. It successfully solves the application problems from concept to reality and provides new ideas and methods for flood forecasting in plain river network areas.