An Integrated Approach for Assessing the Impact of Large‐Scale Future Floods on a Highway Transport System

Abstract

The negative impact of climate change continues to escalate flood risk. Floods directly and indirectly damage highway systems and disturb the socioeconomic order. In this study, we propose an integrated approach to quantitatively assess how floods impact the functioning of a highway system. The approach has three parts: (1) a multi-agent simulation model to represent traffic, heterogeneous user demand, and route choice in a highway network; (2) a flood simulator using future runoff scenarios generated from five global climate models, three representative concentration pathways (RCPs), and the CaMa-Flood model; and (3) an impact analyzer, which superimposes the simulated floods on the highway traffic simulation system, and quantifies the flood impact on a highway system based on car following model. This approach is illustrated with a case study of the Chinese highway network. The results show that (i) for different global climate models, the associated flood damage to a highway system is not linearly correlated with the forcing levels of RCPs, or with future years; (ii) floods in different years have variable impacts on regional connectivity; and (iii) extreme flood impacts can cause huge damages in highway networks; that is, in 2030, the estimated 84.5% of routes between provinces cannot be completed when the highway system is disturbed by a future major flood. These results have critical implications for transport sector policies and can be used to guide highway design and infrastructure protection. The approach can be extended to analyze other networks with spatial vulnerability, and it is an effective quantitative tool for reducing systemic disaster risk.

Flood Impact Assessments on Transportation Networks: A Review of Methods and Associated Temporal and Spatial Scales

“…Based on the assessment, it can be inferred that non-typical disruptions can impact mobility and accessibility of roads as well as traffic speed. Wang et al (2020), applied the probabilistic approach for the highway network by assuming that the network is two way with no additional lanes or traffic and did not include local transport. Based on the assessment, impact remedies, and recommendations for the network were presented.…”

“…Pregnolato et al (2017a) analyzed the flood impacts by using flood depth vs. vehicular traffic as a criteria to perform flood risk assessment; but this excluded the minor network nodes, which can affect the outcome. Diakakis et al (2020), Wang et al (2020), and Tsang and Scott (2020) also used a traffic model to assess flash flood impacts, direct and tangible impacts, and the temporal scale of the analysis ranged from hours to days. In these articles, traffic data was considered as the base, but they did not identify the vulnerable areas/points in the network due to the flood.…”

“…Floods have direct effects on transportation networks through physical damage to infrastructure, and indirect effects that are the result of a cascade of adverse effects that can severely impact critical infrastructure (e.g., energy related infrastructure). They can lead to the failure of a city's infrastructure and economy (Pant et al, 2018;Serre and Heinzlef, 2018;Wang et al, 2020). Critical infrastructure like transportation systems, power grids, etc., are generally interdependent in cities.…”

An Interdisciplinary Approach to Quantify the Human Disaster Risk Perception and Its Influence on the Population at Risk: A Case Study of Longchi Town, China

“…With a multidisciplinary intersection background, it is widely used in mathematics, physics, biology, sociology, and other fields [ 39 ]. It has also been introduced to disaster risk assessment recently [ 10 , 40 , 41 ], especially for behavioral decisions on disaster response that fully consider the diversity of the population.…”

Adaptive Reinforcement Learning Model for Simulation of Urban Mobility during Crises

“…Studies, including Lei et al [4], have examined the vulnerability and resilience of transportation systems during natural disasters and other crises. The majority of existing studies focus primarily on examining the vulnerability of physical road networks [5,6] and quantifying the effects of crises on traffic patterns [7,8]. A critical missing component is the capability to simulate crisis perturbation scenarios for predictive evaluation of the impacts on movement trajectories and traffic patterns at urban scale to inform emergency-response and resilience-planning decisions.…”