Balancing water, food, and energy security while sustaining economic growth remains a critical challenge for developing countries such as China. Despite its importance, the spatiotemporal interaction between inter-provincial water competition and regional economic trajectories remains underexplored. This study calculates the food and energy water footprints in China based on the life cycle assessment (LCA) method, coupling the level of competition between food and energy with regional economic development across 31 Chinese provinces (2006–2022). Machine learning models are used to predict future trends. Results reveal that many provinces, especially in the middle Yellow River and northeastern regions, are still in the antagonism stage, facing intense water resource competition. The predictions indicate that with targeted policy and technological interventions, regions like FJ, GX, and HB could enhance their coordination in the future, while areas such as SX and SN may continue to struggle. These findings provide robust provincial-scale evidence of the complex interdependencies between water, food, energy and regional economic growth. The implications of this work extend to transboundary water governance, offering a replicable tool for policymakers to optimize the distribution of fiscal subsidies and technological investments in China and other water-stressed developing countries in transition, thereby supporting progress toward the United Nations Sustainable Development Goals (SDGs).
Zhao et al. (Thu,) studied this question.