A Closed-Loop Digital Twin Framework for Sustainable and Resilient Post-Disaster Urban Recovery: Integrating Environmental Assessment, Risk Prediction, and Adaptive Resource Management

Abstract

Natural disasters, climate change, and rapid urbanization have increased the complexity of post-disaster urban recovery, creating challenges in environmental management, risk mitigation, and resource allocation. Conventional recovery approaches often rely on fragmented information and relatively fixed decisions, limiting their ability to respond to changing environmental and recovery conditions. This study proposes a Digital Twin Framework for Sustainable and Resilient Post-Disaster Urban Recovery (DT-SRUR) that integrates multisource urban data, environmental quality assessment, chemical-risk-aware prediction, sustainable resource management, and adaptive decision support. A Chemical Risk-Aware Digital Twin Environmental Risk Prediction Module (CR-DT-ERP) is incorporated to capture evolving chemical-related environmental risks and connect risk information with recovery strategy evaluation and resource allocation. The framework establishes a closed-loop process linking environmental and infrastructure assessment, digital twin state updating, recovery strategy evaluation, resource allocation, recovery actions, and feedback. A controlled synthetic post-earthquake scenario is developed to demonstrate the framework over a 30-day recovery period. Three recovery strategies are compared under common initial conditions and resource constraints: rapid restoration-oriented recovery, sustainability-oriented recovery, and digital twin-based adaptive recovery. The results indicate that the adaptive strategy achieves a more balanced performance across recovery effectiveness, environmental performance, resilience, chemical risk, and resource consumption, rather than maximizing a single objective. The study extends digital twin applications from conventional monitoring toward adaptive and risk-aware post-disaster recovery coordination. The proposed framework provides a structured basis for integrating environmental risks, resource constraints, and resilience objectives into sustainable urban recovery planning.