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

大洪水 环境科学 脆弱性(计算) 损害赔偿 气候变化 影响评估 计算机科学 比例(比率) 运输工程 环境资源管理 土木工程 工程类 地理 生态学 计算机安全 地图学 考古 公共行政 政治学 法学 生物
作者
Weiping Wang,Saini Yang,Jianxi Gao,Fuyu Hu,Zhao Wan-yi,H. Eugene Stanley
出处
期刊:Risk Analysis [Wiley]
卷期号:40 (9): 1780-1794 被引量:27
标识
DOI:10.1111/risa.13507
摘要

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.
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