<p>This study employs a PRISMA-guided systematic review and bibliometric analysis to examine the Water-Energy-Food (WEF) nexus in China, revealing a paradox where increasing technical complexity fails to enhance operational governance. The synthesis identifies that traditional mechanism-based models are fundamentally limited by deterministic structures that overlook dynamic environmental uncertainty, whereas machine learning approaches lack the causal interpretability required for informed administrative decision-making. Such methodological fragmentation restricts research outputs to abstract indices rather than converting them into executable policy levers. Furthermore, a pervasive scale mismatch exists because the predominance of national-level models masks granular resource conflicts occurring at river basin and provincial scales. Scholarship is further hindered by a flawed problem framing that treats critical constraints, such as land integrity and carbon targets, as exogenous thematic extensions rather than endogenous system determinants. To address these systemic deficiencies, this study proposes a conceptual hybrid modeling framework that synergistically integrates mechanism-based logic with data-driven stochastic capabilities. By explicitly embedding national policy mandates as primary analytical drivers, this framework provides a roadmap to enhance the policy relevance and operational impact of future nexus research.</p>