Advancing Resilience of Transportation Infrastructure Systems to Land Subsidence (LS), Sea-Level Rise (SLR) and Storm Surge in Coastal Areas

Vulnerability of critical infrastructure, especially the transportation system and high value assets to direct and indirect damage is increasing in the region, as relative SLR, shoreline retreat and the magnitude and frequency of near-shoreline coastal flooding increases. Many of the transportation infrastructure have been designed within the area without consideration of LS and SLR, it is thus critical to close the gaps between the convectional designs and the phasing of the innovative designs that realistically anticipate these treats. Adaptive engineered systems that integrate with and leverage natural infrastructure are urgently needed to mitigate these impacts and promote sustainable and resilient coasts.

The overall goal of the proposed project is to develop approaches and methods that will enable design and management of more sustainable, resilient multi-modal transportation infrastructure in coastal areas that are subject to the combined effects of LS and SLR. Two important U.S. coastal areas that are experiencing rapid relative SLR because of LS and SLR will be studied (Chesapeake Bay and Huston Galveston Area). A combined research team from Morgan State University, the lead institution located in Baltimore, MD, and Carnegie Mellon University will work collaboratively on the project.

In this project, we seek to address the following high-level research questions:

1) In the defined areas of study, what are the components of the multi-modal transportation network(s) that are most vulnerable to SLR and LS?

2) With prioritization of enhancing resilience, how can coastal transportation networks be adapted optimally to mitigate the potential damages from the vulnerabilities?

3) Which innovative designs and approaches can best support these adaptation strategies, in terms of an integrated approach to multi-modal transportation management?

The proposed project will support development of resilient built infrastructures in coastal areas, through better monitoring, mapping, prediction/forecasting, and modeling of SLR and LS. Chesapeake Bay in Maryland and Galveston Bay in Texas are proposed as test beds for study of needs and opportunities for deployment of modern sensing, monitoring, modeling and control technologies for continuous assessment and management of LS and SLR, and integration of this information in adaptive approaches for design and management of infrastructure. The project addresses the vulnerability of transportation infrastructure to LS and SLR and will yield new approaches for designing resilient and sustainable coastal infrastructure. The project will also offer educational opportunities about LS and SLR to minority students. Additionally, the project will ultimately create more informed strategies for policy makers, planners and engineers as scientific understanding of LS, SLR and storm surge is critical for making informed decisions about public investment and management of vulnerable coastal communities.

LS would be computed with COMPAC (Helm, 1975) based on CMP2006 simulated groundwater level and compaction parameter values from Pope and Burbey (2004) and further analysis. The local mean SLR projection would be downscaled from global mean SLR projection with a quadratic SLR equation (Parris et. al., 2012; UACE, 2013) based on local NWLON station relative SLR analysis and removing impacts of LS.