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Stochastic conditional inverse modeling of subsurface mass transport: A brief review and the self-calibrating method

  • J. J. Gómez-Hernández
  • H.-J. W. M. Hendricks Franssen
  • A. Sahuquillo
Article

Abstract.

Conditioning transmissivity realizations to state variable data is complex due to the non-linear dependence of transmissivity (or any univariate transform of it) and piezometric heads, concentrations or velocities. A review of the literature shows these complexities. The self-calibrating algorithm combines standard geostatistics and non-linear optimization in a way that allows the generation of multiple realizations of logtransmissivity, which are conditioned not only to logtransmissivity measurements but also to piezometric head and concentration data. The self-calibrating method is demonstrated in a two-dimensional synthetic exercise in which the trade-offs between transmissivity, piezometric head and concentration data are analyzed.

Keywords

Stochastic inverse modeling Worth of data Inverse conditional realizations Geostatistics Non-linear optimization Uncertainty Monte-Carlo analysis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • J. J. Gómez-Hernández
    • 1
  • H.-J. W. M. Hendricks Franssen
    • 1
  • A. Sahuquillo
    • 1
  1. 1.Departamento de Ingeniería Hidráulica y Medio AmbienteUniversidad Politécnica de ValenciaValenciaSpain

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