Reed Maxwell

About

Reed Maxwell is the William and Edna Macaleer Professor of Engineering and Applied Science at Princeton University, serving as a professor of Civil and Environmental Engineering and the High Meadows Environmental Institute. His research centers on understanding terrestrial freshwater resources on Earth, specifically focusing on how much freshwater is available and the rates at which it is replenished or depleted. His work addresses complex hydrological problems, including groundwater, evapotranspiration, and snow, with an emphasis on understanding the connections within the hydrologic cycle and their relation to water quantity and quality under anthropogenic stresses. Maxwell's research group employs a broad range of approaches, including integrated hydrologic modeling, field observations, and remote sensing products, to investigate these critical issues. He has contributed significantly to the field through his research on hydrology, water resources, and environmental systems. Maxwell has been recognized for his expertise with honors such as the Distinguished Henry Darcy Lecturer by the American Geophysical Union in 2020 and being named a Fellow of the same organization in 2019. He also served as the Boussinesq Lecturer and held the Belle van Zuylen Chair as a visiting professor at the University of Utrecht. In addition to his research, Maxwell teaches courses such as Physical Hydrology and actively contributes to the academic community through his leadership roles,…

Research topics

• Computer Science
• Environmental science
• Geology
• Ecology
• Engineering
• Geography
• Meteorology
• Mechanics
• Environmental resource management
• Physics

Selected publications

• Global Groundwater Modeling and Monitoring: Opportunities and Challenges

  Water Resources Research · 2021 · 273 citations

  Abstract Groundwater is by far the largest unfrozen freshwater resource on the planet. It plays a critical role as the bottom of the hydrologic cycle, redistributing water in the subsurface and supporting plants and surface water bodies. However, groundwater has historically been excluded or greatly simplified in global models. In recent years, there has been an international push to develop global scale groundwater modeling and analysis. This progress has provided some critical first steps. Sti…

  DOI

• Center Pivot Irrigation Systems and Where to Find Them: A Deep Learning Approach to Provide Inputs to Hydrologic and Economic Models

  Frontiers in Water · 2021 · 9 citations

  Availability and quality of administrative data on irrigation technology varies greatly across jurisdictions. Technology choice, however, will influence the parameters of coupled human-hydrological systems. Equally, changing parameters in the coupled system may drive technology adoption. Here we develop and demonstrate a deep learning approach to locate a particularly important irrigation technology—center pivot irrigation systems—throughout the Ogallala Aquifer. The model does not rely on super…

  PublisherOA PDFDOI

• A Deep‐Learning Based Parameter Inversion Framework for Large‐Scale Groundwater Models

  Geophysical Research Letters · 2025-04-23 · 4 citations

  articleOpen accessSenior author

  Abstract Hydrogeologic models generally require gridded subsurface properties, however these inputs are often difficult to obtain and highly uncertain. Parametrizing computationally expensive models where extensive calibration is computationally infeasible is a long standing challenge in hydrogeology. Here we present a machine learning framework to address this challenge. We train an inversion model to learn the relationship between water table depth and hydraulic conductivity using a small numb…

  PublisherOA PDFDOI

• CONCN: a high-resolution, integrated surface water–groundwater ParFlow modeling platform of continental China

  Hydrology and earth system sciences · 2025-05-12 · 3 citations

  articleOpen accessSenior author

  Abstract. Large-scale hydrologic modeling at the national scale is an increasingly important effort worldwide to tackle ecohydrologic issues induced by global water scarcity. In this study, a surface water–groundwater integrated hydrologic modeling platform was built using ParFlow, covering the entirety of continental China with a resolution of 30 arcsec. This model, CONCN 1.0, offers a full treatment of 3D variably saturated groundwater by solving Richards' equation, along with the shallow-wate…

  PublisherOA PDFDOI

• Coupling the ParFlow Integrated Hydrology Model within the NASA Land Information System: a case study over the Upper Colorado River Basin

  Hydrology and earth system sciences · 2025-10-21 · 3 citations

  articleOpen accessSenior authorCorresponding

  Abstract. Understanding, observing, and simulating Earth's water cycle is imperative for effective water resource management in the face of a changing climate. While NASA's Land Information System (LIS)/Noah-MP is widely used for land surface modeling, its ability to represent groundwater processes is limited. In contrast, the ParFlow hydrologic model explicitly simulates subsurface water movement. This study explores the effectiveness and usefulness of the newly coupled modeling framework, ParF…

  PublisherOA PDFDOI

Recent grants

• An Integrated Hydrologic Model Intercomparison Workshop to Develop Community Benchmark Problems

  NSF · $26k · 2011–2014

• WSC-CATEGORY 2 COLLABORATIVE: WATER QUALITY AND SUPPLY IMPACTS FROM CLIMATE-INDUCED INSECT TREE MORTALITY AND RESOURCE MANAGEMENT IN THE ROCKY MOUNTAIN WEST

  NSF · $2.3M · 2012–2018

• Collaborative Research: Framework: Software: NSCI : Computational and data innovation implementing a national community hydrologic modeling framework for scientific discovery

  NSF · $594k · 2020–2023

Frequent coauthors

• Laura E. Condon

  135 shared

• Stefan Kollet

  Forschungszentrum Jülich

  63 shared

• Kenneth H. Williams

  Lawrence Berkeley National Laboratory

  39 shared

• Jun Zhang

  Nanyang Technological University

  30 shared

• Hoang Tran

  Pacific Northwest National Laboratory

  28 shared

• L. A. Bearup

  United States Bureau of Reclamation

  28 shared

• Claire Welty

  28 shared

• James M. Gilbert

  University of California, Santa Cruz

  26 shared

Awards & honors

• 2020 Distinguished Henry Darcy Lecturer American Geophysical…
• Fellow (2019) American Geophysical Union
• 2018 Boussinesq Lecturer
• Belle van Zuylen Chair (visiting), University of Utrecht

Similar researchers at Princeton University

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