An integrated spatial economic modeling framework for forecasting inland waterway freight demand

The decarbonization of freight transportation has become a strategic priority in achieving global carbon neutrality goals. Inland waterways offer a low-emission alternative to road and rail freight, but their effective integration into transportation systems requires robust forecasting tools that account for regional socioeconomic dynamics and infrastructure investments. However, existing freight demand models are simplistic, rely on static assumptions, neglect spatial-economic feedbacks, and are inadequate for long-term forecasting. This paper introduces a quasi-dynamic, Integrated Spatial Economic Modeling (ISEM) framework based on the Production, Exchange, and Consumption Allocation System (PECAS) to address these limitations. ISEM models freight demand as a derived outcome of spatially distributed production and consumption behaviors of economic activity, land use, and multimodal transport networks within a recursive feedback structure. The framework includes a Spatial Activity Model (SAM) that simulates economic development, land use change, and commodity exchanges, and a Transportation Model (TM) that assigns freight flows to the multimodal transportation supernetwork, including highways, railways, and inland waterways, using the incremental freight assignment. The method was tested on the Ganyue Canal in Jiangxi Province and demonstrated high predictive accuracy. Scenario analyses reveal a significant shift in freight transport from highways and railways to waterways during the Ganyue Canal's operation. Study results indicate that the proposed method can provide multidimensional decision support, including the economic and environmental impacts of investments on water transportation infrastructure, its effects on other modes, and expected transport demand.