Reed Maxwell, Princeton University
Laura Condon, University of Arizona
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Abstract:
Groundwater is by far the largest liquid freshwater supply on the planet; yet it is often treated as an isolated system and neglected or greatly simplified in earth systems analysis. It is well established that groundwater is an important buffer to the hydrologic cycle. It stabilizes water supplies across spatial scales and over long time frames. However, these dynamics can be difficult to capture because groundwater surface water interactions are non-linear and vary greatly based on climate, human activity and hydrogeologic setting. This challenge is further exacerbated in changing systems where shifting land cover, extreme droughts and floods can significantly change groundwater storage, discharge and recharge dynamics. Observations of groundwater levels and the hydrogeologic properties that govern flow are sparse both in space and time. This limits the applicability of purely data driven approaches and increases the need for physically based numerical models to help us understand this critical component of the hydrologic cycle.
Simulations with integrated hydrology models (that solve the 3D Richards’ equation and 2D shallow water equations in a globally- implicit manner) provide robust results all the way to continental scales, yet are computationally expensive, running on supercomputers. Our team has developed the CONUS2.1 platform, which is a high-resolution, physically-based model that couples surface and subsurface hydrology, enabling the simulation of complex processes such as groundwater-surface water interactions, evapotranspiration, and land-atmosphere feedbacks. We are evolving this platform into the first digital twin of the full terrestrial hydrologic cycle across the United States. Our approach trains Machine Learning (ML) emulators of integrated hydrology models to drastically reduce the computational burden. We combine these emulator approaches with both purely data-driven approaches and Simulation-Based Inference, to generate seasonal to annual hydrologic scenarios of both groundwater and surface water systems using observations and sophisticated physics-based hydrologic models. This talk will highlight the technical challenges of this rapidly developing branch of hydrologic modelling and discuss the platform we have developed, HydroGEN, which is a hyperresolution hydrology digital twin of the Continental US (CONUS).
Bios:
Reed Maxwell is the William and Edna Macaleer Professor of Engineering and Applied Science in Civil and Environmental Engineering (CEE) and the High Meadows Environmental Institute (HMEI) at Princeton University. He also directs the Integrated GroundWater Modeling Center (IGWMC). His research interests are focused on understanding connections within the hydrologic cycle and how they relate to water quantity and quality under anthropogenic stresses. He was the 2020 Henry Darcy Distinguished Lecturer, an elected Fellow of the American Geophysical Union, was the 2018 Boussinesq Lecture and the 2017 School of Mines Research Award recipient. He has authored more than 185 peer-reviewed journal articles and teaches classes on hydrology and fluid mechanics. At Princeton he currently leads a research group of graduate students, postdoctoral researchers and staff housed within CEE and HMEI. Over his career he has mentored 17 PhD students and 20 MS thesis students. Prior to coming to Princeton, he was faculty at the Colorado School of Mines and a postdoc and then staff in the Hydrologic Sciences group at Lawrence Livermore National Laboratory. He holds a PhD degree in Environmental Water Resources from the Civil and Environmental Engineering Department at the University of California, Berkeley.
Dr. Condon is a Professor of Hydrology and Atmospheric Sciences in the Department of Hydrology and Atmospheric Sciences at the University of Arizona. Her research focuses on water sustainability and the dynamics of hydrologic systems in the context of past development and future climate change. Her work combines physically based numerical modeling with statistical techniques. She received her graduate degrees from the Colorado School of Mines and was an Assistant professor at Syracuse University before joining the University of Arizona. Dr. Condon has won multiple awards for her work including the American Geophysical Union Hydrology Section Early Career Award, University of Arizona Early Career Award, University of Arizona Galileo Circle Curie Award and NSF CAREER Award. She is an author on the fifth National Climate Assessment Water Chapter and serves on multiple national and international committees on data stewardship, cyberinfrastructure, and large-scale modeling.