Networks Subject to Extreme Flood Events
Start date: 04/01/15
End date: 11/30/16
- Iowa State University
- Midwest Transportation Center
About the research
Among various infrastructure systems, transportation networks are known as one of the most critical infrastructure systems as they directly contribute to essential societal functions, quality of living, and the economy. It is, thus, extremely important to assess the components of transportation networks holistically and plan for the consequences of possible failure or disruption in their normal service. Furthermore, appropriate arrangements must be made for prompt response and emergency recovery after extreme events to maintain the resilience of the community.
To achieve this goal, this project focuses on highway transportation networks subject to extreme flood events and introduces a comprehensive analytical framework to investigate the resilience measures that contribute to the efficient management of such networks. For this purpose, a multi-scale data-driven approach will be developed to address the critical issue of vulnerability of civil infrastructure systems at both component and system levels.
Based on the flood risk data collected from different parts of the network, the functionality measures are evaluated at regular time intervals to estimate the expected socio-economic losses due to operational closures and extreme events.
One of the unique aspects of this approach is to go above and beyond the physical boundaries of the network and examine the direct and indirect impacts of network disruptions on the entire society. Towards this goal, appropriate resilience measures are introduced in terms of robustness, redundancy, rapidity, and resourcefulness.
The outcome of this study can be immediately used by decision-making authorities, state departments of transportation (DOTs), and nongovernmental organizations (NGOs) to identify the most efficient management strategies for mitigation actions prior to and restoration efforts following the occurrence of flooding events.