Institute of Transportation Systems Science and Engineering, Beijing Jiaotong University, Beijing, China.
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing, China.
Risk Anal. 2020 Sep;40(9):1780-1794. doi: 10.1111/risa.13507. Epub 2020 Jun 7.
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.
气候变化的负面影响持续加剧洪水风险。洪水直接和间接地破坏公路系统并扰乱社会经济秩序。在本研究中，我们提出了一种综合方法来定量评估洪水如何影响公路系统的功能。该方法有三个部分：(1) 一个多主体仿真模型，用于表示公路网络中的交通、异质用户需求和路径选择；(2) 一个洪水模拟器，使用来自五个全球气候模型、三种代表性浓度途径 (RCP) 和 CaMa-Flood 模型的未来径流情景生成；(3) 一个影响分析器，将模拟洪水叠加到公路交通仿真系统上，并根据跟车模型量化洪水对公路系统的影响。本方法以中国公路网的案例研究为例进行说明。结果表明：(i) 对于不同的全球气候模型，相关的洪水对公路系统的破坏与 RCP 的强迫水平或未来年份不呈线性相关；(ii) 不同年份的洪水对区域连通性的影响是不同的；(iii) 极端洪水的影响可能导致公路网络遭受巨大损失；即，在 2030 年，当公路系统受到未来重大洪水的干扰时，估计有 84.5%的省份之间的路线无法完成。这些结果对交通部门政策具有重要意义，并可用于指导公路设计和基础设施保护。该方法可以扩展到分析具有空间脆弱性的其他网络，是降低系统灾害风险的有效定量工具。
