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Global Rivers Group
@Texas A&M
We use satellites, models, and fieldwork to study Earth's freshwater
We're an academic research group in the Department of Geography at Texas A&M University. Founded in 2018 by Dr. George H. Allen, we are recruiting students and postdocs who are interested in using emerging technology to tackle problems involving freshwater resources.
What we do
We study freshwater resources using remote sensing, fieldwork, and models. We seek to understand how climate change and land use are altering the global water cycle, in particular river and lake hydrology. With rapid advancements in satellite technology, computing power, and model sophistication, it is an exciting time to be studying the global water cycle.
Why we do it
Water is widely considered to be the world’s most vital natural resource, yet freshwater systems are directly endangered by human activities. Our work is motivated by a desire to promote the conservation, management, and understanding of Earth's surface water resources.
News
Updated August 16, 2021
August 16, 2021 - Molly Stroud (BA Dartmouth) joins the Global Rivers Group as an MS student. Molly will work on constraining observational requirements needed to track sediment dynamics within Earth's inland water bodies. Her research is funded by a NASA-Caltech Jet Propulsion Laboratory Strategic University Research Partnership (SURP) grant. Welcome to Texas, Molly!
August 12, 2021 - Science Magazine covers findings presented in Zipper et al., (2021): Climate change is drying out many part-time streams in the United States
July 31, 2021 - Paper led by Sam Zipper at Kansas Geological Survey published in Environmental Research Letters. Study reveals widespread changes in flow intermittency across the United States rivers and streams: https://iopscience.iop.org/article/10.1088/1748-9326/ac14ec/meta
July 1, 2021 - Emily Ellis (MS, BS, Oklahoma State) joins the Global Rivers Group as a PhD student. Emily is the recipient of the MERIT Fellowship, the most prestigious University fellowship bestowed upon graduate students at Texas A&M. Welcome, Emily!
June 30, 2021 - Ryan Riggs receives the TX Space Grant Consortium Graduate Fellowship to support his dissertation research on the topic of remote sensing of river discharge. Congratulations, Ryan!
June 25, 2021 - JPL Strategic University Research Program (SURP) Proposal approved for funding: "Assessing altimetry and optical remote sensing products to study global sediment transport dynamics in Earth’s inland water bodies" (JPL PI: Marc Simard, TAMU PI: George Allen).
Apr 20, 2021 - GRG Ph.D student Ryan Riggs awarded First Prize in Geology/Geography/Geophysics for his presentation, "Estimating discharge from Landsat" for the TAMU Student Research Week. Congrats, Ryan!
Apr 5, 2021 - Paper led by Judith Rosentreter at Yale published in Nature Geosciences which presents a global metadata analysis of methane fluxes from all aquatic ecosystems. Half of the methane in the atmosphere comes from aquatic systems, including rivers & lakes: https://doi.org/10.1038/s41561-021-00715-2
- Related news article: [link]
Mar 12, 2021 - Paper led by Jake Hosen at Purdue published in Hydrological Processes on the relationship between river water travel time and dissolved organic matter composition: https://doi.org/10.1002/hyp.14124
Mar 8, 2021 - George gives a seminar talk at Virginia Tech for Remote Sensing Interdisciplinary Graduate Education Program as the student-nominated speaker.
Feb 8, 2021 - GRG M.S. student Ennis Rios awarded the Mills Scholarship for conducting water-related research on remote sensing of river water temperature. Congratulations, Ennis!
Feb 7, 2021 - Paper led by Alessandra Marzadri (University of Trento, Italy) and Giuseppe Amatulli (Yale) published in Science of The Total Environment on estimating global nitrous oxide emissions from rivers and streams: https://doi.org/10.1016/j.scitotenv.2021.145148
Jan 26, 2021 - Paper led by Peirong Lin at Princeton University published in Scientific Data. This paper presents a state-of-the-art global vector hydrography dataset of rivers with spatially variable drainage density and flow intermittence. An innovative example of using machine learning to extend information from the national scale to the global scale. Great job, Peirong! https://doi.org/10.1038/s41597-021-00819-9
Jan 13, 2021 - Paper led by Yao Li at Texas A&M Department of Civil Engineering published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing on tracking reservoir storage variations using TanDEM-X satellite mission inSAR data: http://doi.org/10.1109/JSTARS.2021.3051103