Articles | Volume 25, issue 6
https://doi.org/10.5194/hess-25-3397-2021
https://doi.org/10.5194/hess-25-3397-2021
Research article
 | 
17 Jun 2021
Research article |  | 17 Jun 2021

Machine learning deciphers CO2 sequestration and subsurface flowpaths from stream chemistry

Andrew R. Shaughnessy, Xin Gu, Tao Wen, and Susan L. Brantley

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Latest update: 16 Jan 2025
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Short summary
It is often difficult to determine the sources of solutes in streams and how much each source contributes. We developed a new method of unmixing stream chemistry via machine learning. We found that sulfate in three watersheds is related to groundwater flowpaths. Our results emphasize that acid rain reduces a watershed's capacity to remove CO2 from the atmosphere, a key geological control on climate. Our method will help scientists unmix stream chemistry in watersheds where sources are unknown.