In March of 2022, I published the first chapter of my dissertation: Effects of Climate and Anthropogenic Drivers on Surface Water Area in the Southeastern United States . In this paper, we explore the differences in the ability of three different groups of drivers to estimate surface water change in the Southeast - climate, anthropogenic, and the combination of the two. The Southeast is an interesting study area both because of its high population growth rate - the highest of any region in the country! - and because of its large amount of land cover change. It also experiences a wide range of effects from climate change, with a hurricane season in the late summer and early fall, increased rainfall in the winter, and increasingly regular dry spells and even droughts in the summer. The data-driven models we developed use a combination of statistical and machine learning techniques to indicate which group of drivers explains the most amount of variance in surface water across the region, as well as which individual variables are the most important in estimating surface water area.

I am currently writing the second chapter of my dissertation: Projecting Surface Water Area Under Future Climate and Development Scenarios. In this paper, we are builing on the results of Gaines et al. (2022) where we found that a combination of climate and land cover variables in a Mixed Effect Random Forest (MERF) model produced the most accurate estiamations of surface water area. Now, we are expanding this model using climate projection data from two levels of greenhouse gas emissions and land cover projections from several different development scenarios. The goal of this paper is to project surface water area in the Southeast into 2100 under a comnination of emissions and development scenarios that are similar to the storylines of the Shared Socioeconomic Pathways developed for the most recent Intergovernmental Panel on Climate Change report.