Assessment of the water-energy-food system and its coordination level in China’s major grain production areas

The water, energy, and food systems exhibit a tightly interconnected nexus, serving as core elements of sustainable development. However, many studies predominantly rely on statistical correlations between aggregate indices to evaluate coupling–coordination, with limited use of explicit cross-system linkage indicators. To address this, this study constructs an evaluation index system from developmental and coupling dimensions. For water-energy coupling, we use the percentage of hydropower generation; for water-food coupling, we adopt water use per unit grain yield, proportion of effectively irrigated farmland area, and effective utilization coefficient of irrigation water; for energy-food coupling, we include electricity consumption per unit grain yield and total agricultural machinery power per unit cultivated area. By introducing these explicit intersystem correlation indicators, we enhance traditional evaluation models. Using the Analytic Hierarchy Process (AHP) to derive indicator weights and a comprehensive index approach to aggregate them, we conduct empirical analyses on the Water-Energy-Food (WEF) nexus in Jiangxi Province and Henan Province, China. The results indicate that in Jiangxi the coupling–coordination degree of the WEF nexus is 0.63 (intermediate), while the total development degree is 0.71 (intermediate) and the total coupling degree is 0.57 (low); in Henan, these values are 0.68 (intermediate), 0.71 (intermediate), and 0.64 (intermediate), respectively. Jiangxi’s energy subsystem development (0.46) and water–energy coupling (0.33) are notably weak and constitute key bottlenecks, whereas Henan’s water subsystem development (0.65) is significantly lower than Jiangxi’s (0.81), making water scarcity a critical constraint. Strengthening renewable energy deployment, optimizing pumped‑storage layouts, and improving hydropower dispatch can enhance WEF coordination and safeguard grain production. By incorporating refined linkage indicators, the enhanced model yields more realistic evaluations and provides actionable decision support for regional resource management.