T227 Do Carbon Sources or Sinks Drive the Phanerozoic Carbon Cycle?: Understanding Geobiologic Forcings and Feedbacks

Wednesday, 12 October 2022
8:00 AM - 12:00 PM
506

MAPPING SILICATE WEATHERING FLUX WITH COUPLED MACHINE LEARNING TECHNIQUES

Paper number: T227-5
Program: Technical Sessions
Time: 8:55 AM – 9:10 AM

Authors

  • Shuang Zhang Presenting Author
    Texas A&M University, College Station, TX
  • Tao Wen
    Syracuse University, State College, PA

Abstract

The chemical weathering of silicate rocks in continental settings shapes landscapes, controls soil evolution, and supplies nutrients to the global biosphere. During weathering process, the reaction of silicate rocks with CO2 also acts as a net carbon sink and provides negative feedback in the global carbon cycle. As such, silicate weathering is thought to have played a key role in keeping surface environments clement throughout the majority of Earth’s history. Despite continual advances in simulating silicate weathering fluxes, traditional modeling approaches still have limited power to reproduce empirical estimates. As such, a quantitative framework that yields robust prediction of silicate weathering rates both in local and global scales remains a challenge. In this study, we apply two data-driven machine learning (ML) techniques to map the silicate weathering flux over the Contiguous United States (CONUS). Specifically, we collect and harmonize available gauge station observations and long-term environmental and geological datasets in corresponding watersheds over the CONUS land surface. We then apply non-negative matrix factorization (NMF) ML model to apportion the river bicarbonate to weathering of silicates or carbonates, which will yield the silicate weathering flux for each watershed. This NMF step is critical because it boosters the number of watersheds that could be used in the following ML model. The silicate weathering fluxes and corresponding watershed properties are then fed into the second ML model based on tree ensembles to build the final ML framework, which is subsequently used to map the silicate weathering flux over the CONUS land surface. Besides, the relative importance of key parameters (such as the climatic/hydrological conditions, crustal compositions, and tectonics) in regulating silicate weathering rates are delineated from the data-driven perspective.

Geological Society of America Abstracts with Programs. Vol. 54, No. 6

doi: 10.1130/abs/2022AM-383634

© Copyright 2022 The Geological Society of America (GSA), all rights reserved. Permission is hereby granted to the author(s) of this abstract to reproduce and distribute it freely, for noncommercial purposes. Permission is hereby granted to any individual scientist to download a single copy of this electronic file and reproduce up to 20 paper copies for noncommercial purposes advancing science and education, including classroom use, providing all reproductions include the complete content shown here, including the author information. All other forms of reproduction and/or transmittal are prohibited without written permission from GSA Copyright Permissions.