Reed Maxwell, a leader in hydrologic modeling, has joined the Princeton faculty as a professor of civil and environmental engineering and the High Meadows Environmental Institute (HMEI).

Maxwell joined the University Sept. 1 after more than a decade at the Colorado School of Mines, where he has directed the Integrated Groundwater Modeling Center since 2011. Maxwell and his team are expanding the center’s activities to Princeton, where they will continue developing broadly accessible simulation tools for the study, management and protection of groundwater resources.

In addition to state-of-the-art computational modeling, Maxwell’s research uses field observations and remote sensing methods to understand and predict groundwater availability, as well as the roles of evapotranspiration and snow in the water cycle.

“I take a holistic view of the hydrologic cycle,” said Maxwell. “I’m interested in how much fresh water we have, how fast it is being replenished, and how fast it is being depleted” — mainly by human use and, increasingly, by effects of climate change.

Maxwell brings new energy and expertise to the civil and environmental engineering department’s longstanding, world-renowned research program in water resources, said Peter Jaffé, the William L. Knapp ’47 Professor of Civil Engineering and acting chair of the department.

Maxwell’s recent work includes a reconstruction of the past 100 years of groundwater pumping across the continental United States — a high-resolution, large-scale simulation that offers critical insights for future water use. The simulation integrates information about the land surface, streamflow, and evapotranspiration, which measures the contributions of soil and plants to the water cycle. Maxwell and colleagues applied similar methods to project U.S. groundwater changes over the 21st century under different climate warming scenarios. The results showed that even a modest temperature increase of 1.5 degrees Celsius could significantly deplete shallow groundwater stores, meaning parts of the eastern U.S. would experience water conditions similar to those now prevalent in western states.

The amount of water loss under this scenario would be about four times the volume of Lake Powell, “one of the most important reservoirs on the Colorado River system … that would just devastate the entire system,” said Maxwell. This type of work emphasizes “unintended consequences, or factors you wouldn’t otherwise be able to connect in the hydrologic cycle, to understand how much water we have and how much it might change,” he added.

These studies form part of the groundwork for Maxwell’s newest endeavor, a major, multidisciplinary project in groundwater modeling funded by the National Science Foundation’s Convergence Accelerator program. The project’s research team is using artificial intelligence methods to further improve groundwater forecasting capabilities. They are also partnering with the U.S. Bureau of Reclamation to collect data and apply their findings to water management in the western United States. Maxwell is a co-principal investigator for the project along with Laura Condon of the University of Arizona and Princeton’s Peter Melchior, an assistant professor of astrophysical sciences jointly appointed in the Center for Statistics and Machine Learning (CSML).

Princeton’s computing resources and interdisciplinary research centers such as HMEI and CSML were invaluable in getting the project off the ground, said Maxwell. The team is also working with the Office of Information Technology’s User Experience Office to ensure its modeling tools meet the needs of researchers and policymakers.

“One of my main reasons for moving to Princeton is to build big things that are outward-facing and benefit the community” of hydrology researchers and educators, said Maxwell. “That’s really what I want to do in the second phase of my career.”

Faculty

  • Reed Maxwell

Research

  • Energy and Environment

Related Department

  • Three students look closely at a model of an architectural structure.

    Civil and Environmental Engineering