Date of Award

Fall 2023

Project Type

Thesis

Program or Major

Civil Engineering

Degree Name

Master of Science

First Advisor

Jennifer M Jacobs

Second Advisor

Eshan V Dave

Third Advisor

Jo Sias

Abstract

Coastal communities rely heavily on their road network for the transportation of goods, services, and people. However, rising sea levels due to climate change are causing many of the communities’ transportation infrastructure to become vulnerable to coastal stressors. Understanding how sea-level rise (SLR) will impact pavement performance and identifying adaptation strategies is vital for making coastal communities more resilient. Natural and Nature-Based Features (NNBF) are becoming increasingly recognized as an adaptation solution to protect coastal communities from SLR-induced stressors and provide ecological and social benefits. This research aims to identify the linkages between storm surge and pavement damage and identify NNBF sites for adaptation solutions in Coastal New Hampshire. Interviews were conducted with stakeholders working in coastal state and federal agencies. These interviews found that most state DOTs have limited knowledge and capacity to apply NNBF as adaptation solutions and are unaware of road pavement damage that occurs due to storms. To identify NNBF, a GIS-based analysis was performed to identify the dunes, beaches, and salt marshes present in New Hampshire’s coastline and categorize the type of protection they provide to coastal roads. The NNBF included in this research are salt marshes, beaches, and dunes. Metrics to measure the protection capacity of salt marshes to roads are the Index of Ecological Integrity (IEI), the Unvegetated to Vegetated Ratio (UVVR), and the Percent Inundation during Mean High High Water (MHHW). For beaches, beach profiles provided the profile length, mean elevation, and volume were used to measure the protection capacity. Similar to beaches, dune profiles provided the dune crest elevation and the dune area were used to measure the protection capacity. From these metrics, the natural features were separated into four protection categories: Storm Buffering, Erosion Control, Wave Attenuation, and Resilience to SLR. This research found that all identified salt marshes, beaches, and dunes have characteristics that lead to at least one type of protection to surrounding roads. To identify vulnerable road sections to storms, a fragility damage model was used to determine a road section’s probability that damage occurred under different historical storm events and in the future under three SLR scenarios. The road fragility model used the distance of the road segment to the shoreline and the inundation duration caused by each storm event. The fragility model found that coastal roads will become increasingly vulnerable to storm impacts in the future due to SLR. Under all storm conditions evaluated in this research with 1.28 m of SLR, there could be over a 1000% increase in number of damaged road segments compared to initial conditions. This means that there are over ten times the amount of damaged road segments in future storm events compared to what is being experienced currently.

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