Author ORCID Identifier

https://orcid.org/0000-0003-1256-0155

Semester

Spring

Date of Graduation

2025

Document Type

Dissertation

Degree Type

PhD

College

Statler College of Engineering and Mineral Resources

Department

Civil and Environmental Engineering

Committee Chair

James Bryce

Committee Co-Chair

Amir Golalipour

Committee Member

Amir Golalipour

Committee Member

John Quaranta

Committee Member

Bradley Wilson

Committee Member

Dimitra Pyrialakou

Committee Member

Lian-Shin Lin

Abstract

Assessment of anthropogenic climate change impacts in pavement design and analysis remains limited within engineering practice, despite growing recognition of the need for climate-resilient roadway infrastructure. Research efforts have increasingly focused on integrating future climate projections into mechanistic-empirical pavement design, which represents the leading edge of the state of practice. However, a lack of consensus persists regarding the optimal methods for incorporating climate projections, particularly in the selection of downscaling techniques and global climate models (GCMs) to ensure accuracy and applicability for pavement performance analysis. This research investigates the impact of statistical downscaling methodologies and GCM selection routines on subsurface temperature projections derived from the Coupled Model Intercomparison Project Phase 5 climate dataset. Average ensemble-based approaches are compared to individual GCM selection to assess potential biases introduced by model averaging in temperature predictive capacity. Results indicate biases in temperature prediction introduced in average ensemble approaches and significant differences resulting from choices of downscaling methods, demonstrating the sensitivity of subsurface temperature profiles to methodological choices. Commensurate recommendations are provided based on those results. Based on the scope of working toward climate-resilient roadway infrastructure, this research extends beyond pavement infrastructure-focused analyses to introduce broader roadway resilience frameworks for improved top-down decision-making using an environmental justice lens. A multi-criteria decision analysis and community-driven asset management frameworks are proposed to systematically evaluate asset vulnerability, criticality, and community resilience, integrating community resilience metrics to inform transportation adaptation strategies. This work contributes to a more comprehensive methodology for climate-adaptive roadway engineering, providing critical insights for practitioners and policymakers seeking to enhance the resilience of roadway infrastructure under future climate conditions.

Download

Share

COinS