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Weibull-distributed dyke thickness reflects probabilistic character of host-rock strength

Author

Listed:
  • Michael Krumbholz

    (Uppsala University
    Geoscience Center Göttingen, Georg-August Universität)

  • Christoph F. Hieronymus

    (Uppsala University)

  • Steffi Burchardt

    (Uppsala University
    Geoscience Center Göttingen, Georg-August Universität)

  • Valentin R. Troll

    (Uppsala University)

  • David C. Tanner

    (Leibniz Institute of Applied Geophysics, Section 1—Seismics, Gravimetry, Magnetics)

  • Nadine Friese

    (Geoscience Center Göttingen, Georg-August Universität
    Wintershall Norge AS, Kanalpiren)

Abstract

Magmatic sheet intrusions (dykes) constitute the main form of magma transport in the Earth’s crust. The size distribution of dykes is a crucial parameter that controls volcanic surface deformation and eruption rates and is required to realistically model volcano deformation for eruption forecasting. Here we present statistical analyses of 3,676 dyke thickness measurements from different tectonic settings and show that dyke thickness consistently follows the Weibull distribution. Known from materials science, power law-distributed flaws in brittle materials lead to Weibull-distributed failure stress. We therefore propose a dynamic model in which dyke thickness is determined by variable magma pressure that exploits differently sized host-rock weaknesses. The observed dyke thickness distributions are thus site-specific because rock strength, rather than magma viscosity and composition, exerts the dominant control on dyke emplacement. Fundamentally, the strength of geomaterials is scale-dependent and should be approximated by a probability distribution.

Suggested Citation

  • Michael Krumbholz & Christoph F. Hieronymus & Steffi Burchardt & Valentin R. Troll & David C. Tanner & Nadine Friese, 2014. "Weibull-distributed dyke thickness reflects probabilistic character of host-rock strength," Nature Communications, Nature, vol. 5(1), pages 1-7, May.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms4272
    DOI: 10.1038/ncomms4272
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    Cited by:

    1. Hakan Savaş Sazak & Melis Zeybek, 2022. "The modified maximum likelihood estimators for the parameters of the regression model under bivariate median ranked set sampling," Computational Statistics, Springer, vol. 37(3), pages 1069-1109, July.

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