Stochastic Resilience Thresholds and Early Warning Signals in Water-Energy-Food Systems: A Safety Science Framework for Preventing Catastrophic Transitions

• Stochastic resilience framework detects 82 catastrophic transitions with 20-78 time steps advance warning • Cross-sectoral cascade amplification quantified: 70% water shock propagates to 14% energy and 10% food failures • Variance-autocorrelation algorithms outperform deterministic thresholds in detecting noise-induced infrastructure collapse • Framework validated across energy grids, flood systems, earthquake cascades, and pandemic healthcare surge scenarios • Adaptive governance module enables real-time emergency coordination during multi-sectoral infrastructure failures Water-energy-food infrastructure systems face catastrophic transition risks as climate change intensifies cross-sectoral interdependencies. Prevailing safety methodologies exhibit critical limitations: deterministic frameworks overlooking stochastic resilience thresholds, inadequate early warning capabilities lacking operational protocols, and sectoral isolation underestimating cascade propagation. This study introduces the Stochastic Resilience and Early Warning Framework (SREWF), synthesizing resilience theory, panarchy, and stochastic viability theory into operational modules for catastrophic transition prevention. The framework integrates stochastic resilience thresholds, variance and autocorrelation-based detection algorithms, equity-adjusted safety boundaries, and cascade prevention mechanisms capturing noise-induced collapse and cross-sectoral feedback amplification. Validation across 100 parameter scenarios achieves perfect classification under controlled simulation conditions (82/82 collapses detected, 18/18 stable trajectories), though operational field deployment expects 80-90% accuracy accounting for measurement errors and unmodeled disturbances, consistent with empirical early warning systems. Average lead times reach 39.3 time steps (representing approximately 8-10 months advance warning, with minimum 20 time steps under worst-case conditions). Cross-sectoral cascade analysis reveals 70% water shocks trigger 14.1% energy and 10.3% food secondary impacts, validating coupling coefficients against documented failures. Parameter sensitivity testing demonstrates operational robustness, with 80% of tested combinations maintaining safe-zone operation. Beyond water-energy-food systems, the framework demonstrates transferability to flood early warning, earthquake cascades, energy grid stability, and healthcare surge management. These findings advance catastrophic transition prevention methodology aligned with Sendai Framework principles, providing emergency managers validated tools for protecting vulnerable populations during cascading infrastructure failures.