Framework for improving the resilience and recovery of transportation networks under geohazard risks

Abstract

A B S T R A C TRural transportation networks are highly susceptible to geohazards such as earthquakes and landslides. Indirect losses can be severe because the breakdown of a transportation network aggravates rescue, supply, and other recovery activities. The operations and logistics of rural networks that are under seismic risks must be managed using the limited resources specifically in developing countries. We propose a methodology to evaluate road recovery strategies for restoring connectivity after blockages due to earthquakes and earthquake-triggered landslides. This paper gives insight into the recovery process, which can be used by decision-makers for enhancing resilience and supplying immediate relief to rural areas. The proposed framework has four steps: 1) identification of strategies for increasing recovery performance, 2) determination of graph-based metrics to represent network connectivity, 3) applying topology-based and Monte Carlo simulations to each strategy, and 4) analysis of recovery times to compare these resilience-enhancement strategies. The methodology was tested using a case study from Sindhupalchok District, Nepal, a region that was severely affected by the Gorkha earthquake in 2015. The closed road segments and recovery times were determined through field surveys with locals and governmental authorities, and by investigating the intensity of earthquake-triggered landslides. Our results showed that the proposed approach provides information about the recovery behavior of road networks and simplifies the evaluation process. It is robust enough to extend and assess decision-makers' preferences for improving resilience.

Resilience-Based Recovery Assessments of Networked Infrastructure Systems under Localized Attacks

“…In other words, resilience is a characteristic that represents system performance under unusual conditions, recovery speed, and required actions for recovery to its original functional state [22]. It is a component importance measure related to system reliability and recovery after an attack or failure [12,19]. According to C. Whitson et al, resilience is a composite of (1) the ability of an infrastructure system to provide service despite external failures and (2) the time to restore service when in the presence of such failures [10].…”

“…System reliability and recoverability complement each other and are highly related to the resilience of a system. To maintain the desired level of system performance in the presence of disruptive events, an assessment of infrastructure resilience must be conducted [12,13].…”

Quantitative Study on the Waterlogging Resilience of Road Transportation System Based on the Validity View of System Functions

“…Rural transportation networks are vulnerable to geological disasters, such as earthquake and landslide; therefore, Aydin et al proposed a method to assess the resilience of road transportation system. This method evaluated the resilience of a road transportation system by the connections after blockage caused by earthquakes and earthquake-induced landslide [18]. In addition to earthquake disasters, Chan et al studied Hurricanes Irene and Sandy and the snowstorm in New York.…”

Enhancing Road Network Resilience by Considering the Performance Loss and Asset Value

“…Previous studies have focused on resilience assessment for lifelines such as road networks using flow diagrams and complex network theory [14][15][16]. Aydin et al [14] studied the recovery behavior of road networks and simplified the evaluation process using rural transportation networks.…”

“…Previous studies have focused on resilience assessment for lifelines such as road networks using flow diagrams and complex network theory [14][15][16]. Aydin et al [14] studied the recovery behavior of road networks and simplified the evaluation process using rural transportation networks. Ganin et al [15] focused on multi-level directed acyclic graphs and interdependent networks, and demonstrated how network parameters can be traded off to obtain desired levels of resilience and other performance parameters.…”