Flood Impacts on Urban Transit and Accessibility

by Yiyi He

Date: Wednesday, 10 Nov 2021 | 17:00-18:00 CET

Abstract: Transportation networks underpin socioeconomic development by enabling the movement of goods and people. However, despite frequent occurrences, little is known about how floods disrupt transportation systems in developing country cities. We collect an innovative dual-condition transit feed specification dataset, and combine it with a travel survey and high-resolution flood maps to examine how regular floods in Kinshasa impact transport services, job accessibility, and the associated economic opportunity costs from travel delays. Our results show that flood disruptions cause increases in public transit headways, transit re-routing, decreases in travel speeds, which translate into travel delays and loss of job accessibility. This induces substantial economic costs to local commuters-$1,200,000 (daily) and hinders the establishment of an integrated citywide labor market. In addition, we reveal sizeable socio-spatial heterogeneities, with clusters of low-income residents incurring a large share of the travel delays and identified critical network segments that should be prioritized for resilience interventions.

Speaker Biography: Yiyi He is a Ph.D. candidate from the College of Environmental Design at University of California, Berkeley. She received her bachelor’s degree in City and Regional Planning from Nanjing University and her master’s degree in Environmental Planning from UC Berkeley. She is currently working as an Artificial Intelligence (AI) Resident at GoogleX. Prior to this, she worked as a consultant for the Global Facility for Disaster Reduction and Recovery (GFDRR) and a researcher for the Center for Catastrophic Risk Management (CCRM) and Federal Aviation Administration Consortium in Aviation Operations Research (NEXTOR III). Her research focuses on climate-induced weather impacts on complex infrastructure networks. Her previous work involves using 3D hydrodynamic flood models to simulate flooding in the Bay Area under different climate scenarios and analyze the impact of both coastal and inland flooding on a multi-modal fuel transportation network. She hopes to bring environmental studies and network science together and utilize tools in data science and modeling to help identify network vulnerabilities to climate-induced extreme weather events and to help inform the development of contingency plans to increase network resilience.

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