Sensitivity analysis of spatial models using geostatistical simulation

Abstract : Geostatistical simulations are used to perform a global sensitivity analysis on a model Y = f(X1 ... Xk) where one of the model inputs Xi is a continuous 2D-field. Geostatistics allow specifying uncertainty on Xi with a spatial covariance model and generating random realizations of Xi. These random realizations are used to propagate uncertainty through model f and estimate global sensitivity indices. Focusing on variance-based global sensitivity analysis (GSA), we assess in this paper how sensitivity indices vary with covariance parameters (range, sill, nugget). Results give a better understanding on how and when to use geostatistical simulations for sensitivity analysis of spatially distributed models.
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Robert Marschallinger, Fritz Zobl. Mathematical Geosciences at the Crossroads of Theory and Practice - IAMG 2011 Conference, Sep 2011, Salzburg, Austria. pp.178-189, 2012, 〈10.5242/iamg.2011.0172〉
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Nathalie Saint-Geours, Christian Lavergne, Jean-Stéphane Bailly, Frédéric Grelot. Sensitivity analysis of spatial models using geostatistical simulation. Robert Marschallinger, Fritz Zobl. Mathematical Geosciences at the Crossroads of Theory and Practice - IAMG 2011 Conference, Sep 2011, Salzburg, Austria. pp.178-189, 2012, 〈10.5242/iamg.2011.0172〉. 〈hal-00666755〉

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