IMPROVING DECISION MAKING IN CLIMATE ADAPTATION WITH MULTIPLE OBJECTIVES UNDER UNCERTAINTY: NEW DECISION SUPPORT TOOLS AND COMPARISON OF URBAN TEMPERATURE DATA COLLECTION METHODS

Climate change is one of the biggest challenges facing humankind. Adaptation is important and urgent but receives less attention and resources than mitigation. This motivates this dissertation to address four research questions regarding climate adaptation. The first two questions concern general methodology for adaptation planning under uncertainty, and the other two focus on urban heat adaptation specifically. Those questions are: (1) how to select the most appropriate decision analysis for a particular adaptation problem? (2) how to rank adaptation problems based on their likelihood of being improved by comprehensive analysis? (3) what is an appropriate methodology for performing decision analyses for urban heat adaptation, and what insights can be generated? and (4) how do current intra-urban temperature monitoring approaches compare with each other and how to improve those approaches? In this dissertation, Chapter 1 provides the background of the research and establishes the contributions of this dissertation. Chapter 2 addresses the first two questions by developing two practical tools that can assess whether uncertainty and flexibilities will affect climate adaptation decisions and help managers select the most appropriate analytical tools to use. Chapter 3 focuses on the third question and proposes a decision analysis tool, City-HEAT, that can simultaneously consider uncertainty, multi-objective, and adaptive management in generating adaptation plans. Results of a case study suggest that plans generated by City-HEAT are superior to plans based on simple rules or optimized with respect to just one scenario. Chapter 4 studies the fourth question by comparing two intra-urban temperature monitoring approaches with data collected by each approach in Baltimore, MD. It finds that measuring temperatures over various urban land covers, maximizing sensor distances, and monitoring under different weather conditions, are key criteria to improve the data quality of intra-urban temperature monitoring. Finally, Chapter 5 presents the conclusions and some future research opportunities. Overall, the contributions of my dissertation include the development of two decision support tools for improving climate adaptation in general, the creation of an innovative decision analysis tool to support urban heat adaptation, and the generation of insights that can improve intra-urban temperature monitoring in practice