Predicting sedimentary bedrock subsurface weathering fronts and weathering rates

Jiamin Wan, Tetsu K. Tokunaga, Kenneth H. Williams, Wenming Dong, Wendy Brown, Amanda N. Henderson, Alexander W. Newman, Susan S. Hubbard

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

Although bedrock weathering strongly influences water quality and global carbon and nitrogen budgets, the weathering depths and rates within subsurface are not well understood nor predictable. Determination of both porewater chemistry and subsurface water flow are needed in order to develop more complete understanding and obtain weathering rates. In a long-term field study, we applied a multiphase approach along a mountainous watershed hillslope transect underlain by marine shale. Here we report three findings. First, the deepest extent of the water table determines the weathering front, and the range of annually water table oscillations determines the thickness of the weathering zone. Below the lowest water table, permanently water-saturated bedrock remains reducing, preventing deeper pyrite oxidation. Secondly, carbonate minerals and potentially rock organic matter share the same weathering front depth with pyrite, contrary to models where weathering fronts are stratified. Thirdly, the measurements-based weathering rates from subsurface shale are high, amounting to base cation exports of about 70 kmolc ha−1 y−1, yet consistent with weathering of marine shale. Finally, by integrating geochemical and hydrological data we present a new conceptual model that can be applied in other settings to predict weathering and water quality responses to climate change.

Original languageEnglish
Article number17198
JournalScientific Reports
Volume9
Issue number1
DOIs
StatePublished - Dec 1 2019
Externally publishedYes

Funding

We thank the Rocky Mountain Biological Laboratory (RMBL) for helping with field research. This work was conducted as part of the Watershed Function Scientific Focus Area at Lawrence Berkeley National Laboratory and was supported by the U.S. Department of Energy (DOE) Subsurface Biogeochemical Research Program, DOE Office of Science, Office of Biological and Environmental Research, under Contract Number DE-AC02-05CH11231.

FundersFunder number
DOE Office of Science
Office of Biological and Environmental ResearchDE-AC02-05CH11231
U.S. Department of Energy
Lawrence Berkeley National Laboratory

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