A complex network approach to quantifying flood resilience in high-density coastal urban areas: A case study of Macau

Abstract

Urban flood resilience is a critical challenge for high-density coastal cities, where traditional infrastructure-based approaches often fail to capture the dynamic interactions between physical systems, functional recovery, and cascading disruptions. This study introduces a novel resilience assessment framework based on complex network theory, applied to the Macau Peninsula as a case study. By modeling urban infrastructure as an interconnected network of nodes (buildings) and edges (roads), the framework quantifies resilience through three core capacities: resistance, absorption, and recovery. The analysis integrates scenario-based flood simulations with network metrics to assess system vulnerabilities and identify key determinants of resilience. Results reveal significant weaknesses in Macau's high-density urban areas, particularly under compound flood events combining storm surges and extreme rainfall. Findings underscore the critical role of road network redundancy and shelter accessibility, as areas with lower redundancy experience prolonged recovery times. Model validation confirms the framework's effectiveness in quantifying resilience dynamics, though its current focus on physical infrastructure presents limitations in capturing socioeconomic and institutional factors. Nonetheless, this study establishes a scalable foundation for integrating such dimensions in future research. By bridging network topology with functional recovery dynamics, this work advances the theoretical understanding of urban flood resilience while offering actionable insights for policymakers to prioritize infrastructure investments and resilience planning in coastal cities.