Simulation of the entire process and multi-dimensional sustainability assessment of regional water footprint supply chain using the SCOR-SD-BN coupled framework

Context Global water resources face critical challenges such as pollution, over-exploitation, and inequitable distribution. This necessitates the development of scientific frameworks to effectively evaluate the sustainability of water resource management. Objective This study establishes a theoretical framework for the agricultural water footprint supply chain, directly elucidates the transformation mechanisms and sustainable evaluation methods from farmland water use to final products, and constructs a system dynamics model for the agricultural water footprint in Heilongjiang Province. This model simulates dynamic processes, enables real-time evaluation of multidimensional sustainability, and analyzes dominant paths. Methods Drawing on the Supply Chain Operations Reference (SCOR) model, this study treated water footprint (WF) and water value as equivalent to the supply chain's total cost and total revenue, respectively. It established a WF supply chain transformation mechanism from water consumption to the product side and used a system dynamics (SD) model to simulate the entire WF supply chain process in Heilongjiang Province, quantitatively analyzing supply chain structure diversity and disturbance amplification. Based on this, a multidimensional evaluation index system covering economic, environmental, and social dimensions was constructed and, in combination with Bayesian Network (BN), fuzzy logic, and semantic mapping, facilitated multidimensional dynamic evaluation and dominant path identification of regional WF supply chain sustainability. Results and conclusions The research findings demonstrate that (1) From 2000 to 2050, both the total cost and total revenue of Heilongjiang Province's WF supply chain consistently exhibit an initial increase followed by a decrease, with the disturbance amplification effect present across all sectoral WF supply chains. (2) In agriculture, apple and beef cattle supply chains possess the strongest sustainability, while soybean and sheep supply chains display the weakest. In the industry, the food manufacturing sector has the strongest sustainability, while the electric heating and metallurgical sectors are the weakest. (3) The comprehensive sustainability index of the WF Supply Chain pursues a distinctly fluctuating upward trajectory from 2000 to 2025. Under the established scenario, the index is projected to continue rising overall from 2026 to 2050, reaching approximately 0.83 around 2045, entering the high sustainability level, and becoming largely stable by 2050. Environmental improvement stands out as the primary strategy when sustainability is low, while economic factors become the principal constraint when sustainability is high. Significance This research establishes a novel analytical framework and quantitative tool for assessing the sustainability of water resource management. The findings decisively guide the promotion of sustainable utilization and management of regional water resources.