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TGR Activities Address Issues Surrounding the Depletion of Transboundary Groundwater



The Transboundary Groundwater Resilience (TGR) Network-of-Networks (NoN) team has been working to address transboundary groundwater depletion using a systems and network approach. Specifically, TGR synergistically connects water, social, data, and systems science to catalyze transformative change for groundwater systems around the world facing unprecedented depletion.


Over the past year, TGR has hosted an array of community workshops, seminars, and an annual workshop. Additionally, TGR has co-hosted Collective Learning Meetings (CLMs) with the WPI System Dynamics (SD) and SD Club. CLMs, student-run peer mentoring events, allow for feedback on work in-progress and discussions regarding simulation modeling.


Led by Principal Investigator (PI) Sam Fernald, director of the Water Resources Research Institute at New Mexico State University (NMSU), the project team has plans for a panel on data for transboundary groundwater modeling, panel on career development, more co-hosted seminars and CLMs as well as an annual workshop in 2023.


“We are excited to continue to accelerate collaboration that advances transboundary groundwater resilience through this network-of-networks,” said West Hub Executive Director Ashley Atkins, who is also co-PI on the project. “And, we look forward to harnessing data-driven capabilities in support of solutions.


Additional TGR co-PIs are Christine Kirkpatrick, Saeed Langarudi, and Ilya Zaslavsky.


A summary of the TGR events is found on the program’s Event Page.


This work is supported in part by the National Science Foundation's AccelNet program (award no. 2114718).


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The West Big Data Innovation Hub is supported by the National Science Foundation through awards #1916573, 1916481, and 1915774. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Learn more about the NSF Big Data Hubs community here.

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