The sustainable management of water resources within the Water-Energy-Food-Carbon (WEFC) nexus is critical for mitigating systematic risks in rapidly urbanization progress. However, traditional linear assessments often fail to capture the complex, non-monotonic feedbacks limiting water security. This study develops an integrated "assessment-diagnosis-analysis" framework to evaluate the hydrological centrality and coupling dynamics of the WEFC system across the Yangtze River Economic Belt (YREB) from 2001 to 2022. By synthesizing an enhanced Coupling Coordination Degree (CCD) model with an explainable machine learning architecture (XGBoost-SHAP-GAM) and Feature Interaction Networks, this research quantifies the nonlinear thresholds governing system stability. The results reveal distinct spatial heterogeneity in hydrological coordination: the Yangtze River Delta exhibits a mature "networked equilibrium," whereas upstream regions experience persistent "siphon effects" and developmental fragmentation. Crucially, the machine learning based variance decomposition identifies a structural "saturation effect" in water supply, whereby its marginal attribution to the composite coordination index plateaus and diminishes significantly after exceeding specific thresholds. This phenomenon indicates that infrastructure expansion yields diminishing marginal returns for water security. Furthermore, carbon intensity acts as a rigid "veto" constraint, while feature interaction analysis demonstrates that water availability significantly modulates the efficacy of energy and food subsystems (coupling stiffness). Consequently, these findings challenge the "supply-driven" paradigm and advocate a transition to efficiency-oriented management. This study provides a robust methodological tool for diagnosing nonlinear hydrological interactions in complex adaptive systems, offering scientific support for Integrated Water Resources Management (IWRM) and collaborative governance in large-scale urban catchments.
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Binyu Liu
Yuan Wang
Zuowen Tan
Water Research X
Zhejiang University
Shanghai Ocean University
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Liu et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69df2a4be4eeef8a2a6af83d — DOI: https://doi.org/10.1016/j.wroa.2026.100541
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