The water–energy–environment nexus (WEEN) system constitutes a large-scale complex system plagued by multifaceted risks amid global challenges to sustain economic growth, resource security, and environmental resilience. Accelerated urbanization has triggered escalating water and energy demands, exposing over 60% of Chinese regions to severe resource shortage risks. Concurrently, policymakers face critical dilemmas in balancing systemic benefits against potential losses under tightening water and energy policies. To address this dual-risk challenge spanning resource scarcity and economic instability, this study develops a copula-based stochastic downside risk-aversion programming (CSDP) model for regional WEEN management.The CSDP framework synergistically integrates copula functions for dependency modeling and risk-aversion optimization techniques. It uniquely quantifies nonlinear interactions between water and energy risks under multivariate distributions—including scenarios with undefined prior correlations—while generating robust solutions through joint chance constraints. Crucially, the model establishes quantifiable tradeoffs between economic objectives (e.g., GDP targets) and system reliability through conditional value-at-risk metrics. Applied to Tianjin—a coastal metropolis grappling with chronic water deficits and coal-dependent energy systems—the CSDP examines 12 copula structures across five policy scenarios and three risk-tolerance tiers. The results demonstrate water scarcity’s dominant influence (>68% impact) over energy constraints in industrial restructuring, directly affecting sectoral output allocations, wastewater discharge limits, and PM2.5 control strategies. Notably, tertiary industry expansion, while boosting GDP by 19.2% in optimal scenarios, intensifies the graywater footprint by 27% and requires integrated pollution mitigation frameworks. This research provides actionable pathways for sustainable resource co-management amid climate uncertainties.