Date of Award
Doctor of Philosophy (PhD)
Civil, Environmental & Architectural Engineering
Considering climate change is an imperative for planning, creating and sustaining resilient civil infrastructure systems. However, there exist significant barriers to the understanding and implementation of climate change considerations, including the inherent uncertainty in climate change model projections. This severe uncertainty makes planning, designing and maintaining infrastructure a highly complex task. This is due to the challenge of determining the most likely changes relative to historic design standards. At the same time, traditional cost-benefit analysis to determine alternatives for climate adaptation engineering projects and designs may no longer be valid. The high level of uncertainty associated with climate projection and climate impact assessment requires a new methodology to prioritize alternatives and support decision-making of proactive climate change adaptation investments.
This dissertation seeks to address these challenges in three ways: first, it is demonstrated that is possible to determine specific, quantifiable vulnerability impacts, adaptation options and cost-benefit solutions for civil infrastructure based upon specific climate scenarios. Secondly, it presents the metric of “regret” as a viable option to be incorporated into traditional cost-benefit analysis in order to deal with the severe uncertainty of climate models. Finally, this dissertation introduces a novel method for calculating a “robust” decision rooted in existing decision theory and uncertainty. It presents a framework used for robust decision making that provides guidance about the most low-regret adaptation options for resilient road infrastructure design. The methodology presented in this dissertation is ready to use for practitioner, engineers and planners who are considering proactive climate adaptation projects and investments. Two case studies are elaborated to illustrate and demonstrate the capabilities of the proposed framework. These case studies use investment on the road network in two distinct geographic locations - North East Mexico and Kenya – to demonstrate the applicability of this framework in different contexts.
The interdisciplinary nature of this dissertation relates it to numerous fields of engineering and science, including transport engineering, infrastructure systems, risk and uncertainty engineering, project management and finance, and environmental planning and economics. This dissertation provides a clear framework to support decision makers to prioritize robust proactive adaptation investments for their individual infrastructure assets under the complexity and uncertainty of climate change.
Espinet Alegre, Xavier, "Prioritization Framework for Robust Climate Change Adaptation Investments: Supporting Transport Infrastructure Decision-Making Under Uncertainty" (2015). Civil Engineering Graduate Theses & Dissertations. 197.