<p>This study investigates resilience enhancement strategies for resource-based cities by focusing on the complex coupling of urban subsystems and the interdependencies among multiple risks. A functional interdependence network is developed to depict the interactions among critical systems such as economy, energy, transportation, and environment. Based on historical data and expert judgment, major urban risks and their correlations are identified. A localized Markov assumption is employed to estimate the joint occurrence probabilities of risk scenarios, and a risk chain map is constructed accordingly. To optimize the allocation of limited resilience resources, a two-stage stochastic programming model integrating protection and recovery strategies is proposed. Using Yulin City as a case study, real-world operational and risk data are collected, and the model is solved with the Gurobi optimizer. The results reveal that accounting for multi-system and multi-risk interdependencies significantly improves urban resilience. Moreover, the combined protection–recovery strategy performs better than single-phase strategies in terms of effectiveness and adaptability. This study offers a systematic decision-making framework for emergency management, infrastructure investment, and coordinated governance in resource-based cities facing concurrent and cascading risks, contributing to their long-term safety and sustainable development.</p>