Reliability of urban underground-aboveground logistics networks under rainfall-flood and cascading failure scenarios

Abstract

Urban Underground-Aboveground Logistics Networks (UUALNs) are susceptible to disruptions from unforeseen events such as rainfall and flooding, leading to severe road congestion. This paper investigates the reliability of UUALNs under various attack-recovery conditions, focusing on their ability to recover from cascading failures triggered by extreme rainfall-flood scenarios. We propose a coupled model that integrates a rainfall-flood model with a cascading failure framework. A case study of Nanjing is conducted to simulate the model’s performance and validate its spatiotemporal adaptability in different attack-recovery scenarios. The findings demonstrate that different recovery strategies show varying degrees of effectiveness in mitigating network damage, with strategies based on the interaction attributes of coupled networks proving more resilient in rainfall-flood scenarios. When network congestion exceeds the percolation threshold, the diffusion of congestion intensifies, posing further challenges to network reliability. This study provides a robust framework for enhancing the resilience of urban logistics networks under adverse conditions.