Sarah Burbank ’25


Computer Science

Project Title

Understanding Watershed Processes in Complex Terrain – Mountain Hydrology Field Camp

Certificate(s): African American Studies, Quantitative and Computational Biology

Mountainous watersheds are important for recharging the flow of Western American rivers. Understanding these watersheds is critical to modeling how climate change will affect water resources, however, they are difficult to model due to their complex terrain. I aimed to improve understanding of the spatial and temporal factors that govern soil moisture in mountainous watersheds and to investigate the viability of using machine learning to predict soil moisture in highly complex terrain from in situ measurements. I helped collect various data over a small drainage in Colorado’s East River watershed, including soil moisture data, meteorological data and drone-collected topographical characterization data. Then, I used these datasets to run a random forest regression machine-learning model to predict soil moisture. These methods can be used to extrapolate the findings of labor-intensive field campaigns to larger areas. I learned skills in data collection, organization and preprocessing. Seeing how research can translate data from real environmental trends into a computational output was exciting. The experience also gave me the opportunity to interact with successful people at all levels of academia, which enabled me to envision a future career path doing the same.

Internship Year


Project Category

Water and the Environment


Integrated GroundWater Modeling Center, Department of Civil and Environmental Engineering, Princeton University - Rocky Mountain Biological Laboratory, Gothic, Colorado


Reed Maxwell, William and Edna Macaleer Professor of Engineering and Applied Science, Professor of Civil and Environmental Engineering and the High Meadows Environmental Institute; Harry Stone, Ph.D. candidate, Civil and Environmental Engineering