| dc.description.abstract | The past decade has seen an increase in the intensity and frequency of extreme weather events around the globe. The changes in weather and climate patterns can be linked to the increasing amount of greenhouse gases, GHGs, in the earth’s atmosphere. The increase in frequency and intensity of extreme weather has caused disruptions across all elements of modern societies. Particularly, infrastructure and the built environment are frequently subjected to disruptions and damage. Only during 2022, eighteen weather and climate disaster events exceeded $1 billion in losses and damages in the U.S. Transportation infrastructure is one of the critical sectors for the nation’s security, economy, and overall development. However, extreme weather events continue to pose a significant challenge to the nation’s transportation network, including disruptions to the national airspace system, highway system, bridges, coastal roads, and ports. In response, planners, stakeholders, and decision-makers seek tools and guidance to assist in planning more resilient infrastructure.
In this context, resilience has become the norm in planning against disruptive events. Resilience has been identified by academics, practitioners, and the federal government as essential to secure and maintain normal operations of the nation’s transportation network. However, we still lack a standardized and transferable process to guide planners and decision-makers in implementing resilience into the transportation planning process. Another issue in implementing resilience analysis is failing to incorporate future weather conditions, as most analysis is based on historical weather conditions.
In response, this dissertation aims to develop a practical, performance-based framework to quantify the resilience of transportation systems to extreme weather and climate events. The Performance-based Resilience Evaluation Program (PREP) Framework is a standardized 12-step process that can be deployed to quantify resilience against extreme weather conditions among different transport systems. It is also transferable to multiple performance measures, regardless of their unit of measurement. Results show that the framework can be successfully implemented for two transport systems (airports and highways) and multiple performance measures (passenger arrival delays, passenger departure delays, and reduced capacity). Finally, this dissertation highlights a research agenda that can guide the implementation of the framework in the traditional planning process. | en_US |
