Forecasting interregional freight demand for large regions has been a challenging task due to intricate interactions between freight demand and multimodal transportation networks. With this, this paper endeavors to develop a high-fidelity integrated modeling approach to forecast freight demand within a large region. The proposed framework combines spatial economic modeling with a multimodal transportation supernetwork modeling approach to systematically model the quantitative relationship between freight demand, socioeconomic activities, and multimodal transportation networks. First, a “high-fidelity” spatial economic module is developed based on input-output tables, land use, and population/employment data. Parameters of the spatial economic model are calibrated using observed trip length distribution and traffic count data. Then a “high-resolution” multimodal transport supernetwork, consisting of a detailed highway, railway and waterway networks, is developed to assign freight demand to the multimodal transportation supernetwork. Finally, a case study is conducted using the proposed method for the Yangtze River Economic Belt, which demonstrates the utility of the proposed approach in systematically modeling and forecasting the freight demand, as well as in analyzing the impact of related economic, land-use, and transport policies in a high-fidelity fashion. The proposed approach supports improved decision-making in planning and operating regional multimodal transportation systems and related systems, such as economy, land-use and possibly environment.