Articles | Volume 17, issue 9
https://doi.org/10.5194/gmd-17-3949-2024
https://doi.org/10.5194/gmd-17-3949-2024
Development and technical paper
 | 
15 May 2024
Development and technical paper |  | 15 May 2024

A revised model of global silicate weathering considering the influence of vegetation cover on erosion rate

Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu

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Cited articles

Adams, B. A., Whipple, K. X., Forte, A. M., Heimsath, A. M., and Hodges, K. V.: Climate controls on erosion in tectonically active landscapes, Sci. Adv., 6, eaaz3166, https://doi.org/10.1126/sciadv.aaz3166, 2020. 
Allen, J., Forrest, M., Hickler, T., Singarayer, J., Valdes, P., and Huntley, B.: Global vegetation patterns of the past 140,000 years, J. Biogeogr., 47, 2073–2090, https://doi.org/10.1111/jbi.13930, 2020. 
Amiotte Suchet, P., Probst, J.-L., and Ludwig, W.: Worldwide distribution of continental rock lithology: Implications for the atmospheric/soil CO2 uptake by continental weathering and alkalinity river transport to the oceans, Global Biogeochem. Cy., 17, 1038, https://doi.org/10.1029/2002GB001891, 2003. 
Andermann, T., Strömberg, C. A. E., Antonelli, A., and Silvestro, D.: The origin and evolution of open habitats in North America inferred by Bayesian deep learning models, Nat. Commun., 13, 4833, https://doi.org/10.1038/s41467-022-32300-5, 2022. 
Anderson, R.: Modeling the tor-dotted crests, bedrock edges, and parabolic profiles of high alpine surfaces of the Wind River Range, Wyoming, Geomorphology, 46, 35–58, https://doi.org/10.1016/S0169-555X(02)00053-3, 2002. 
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
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