Use of global sensitivity analysis and polynomial chaos expansion for interpretation of nonreactive transport experiments in laboratory-scale porous media

被引:69
|
作者
Fajraoui, Noura [1 ]
Ramasomanana, Fanilo [1 ]
Younes, Anis [1 ]
Mara, Thierry Alex [2 ]
Ackerer, Philippe [1 ]
Guadagnini, Alberto [3 ]
机构
[1] Univ Strasbourg, EOST, CNRS, Lab Hydrol & Geochim Strasbourg, 1 Rue Blessig, F-67084 Strasbourg, France
[2] Univ La Reunion, PIMENT, Dept Phys, Moufia 97715, Reunion, France
[3] Politecn Milan, Dipartimento Ingn Idraul Ambientale Infrastruttur, I-20133 Milan, Italy
关键词
LOCALIZED ADJOINT METHOD; UNSTRUCTURED MESHES; UNCERTAINTY; MODELS; EFFICIENT; DIFFUSION; EQUATION; INDEXES; SYSTEMS; FLOW;
D O I
10.1029/2010WR009639
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In this work, we show how the use of global sensitivity analysis (GSA) in conjunction with the polynomial chaos expansion (PCE) methodology can provide relevant information for the interpretation of transport experiments in laboratory-scale heterogeneous porous media. We perform GSA by calculating the Sobol indices, which provide a variance-based importance measure of the effects of uncertain parameters on the output of a chosen interpretive transport model. The choice of PCE has the following two benefits: (1) it provides the global sensitivity indices in a straightforward manner, and (2) PCE can serve as a surrogate model for the calibration of parameters. The coefficients of the PCE are computed by probabilistic collocation. The methodology is applied to two nonreactive transport experiments available in the literature, while considering both transient and pseudo steady state transport regimes. This method allows a rigorous investigation of the relative effects and importance of different uncertain quantities, which include boundary conditions as well as porous medium hydraulic and dispersive parameters. The parameters that are most relevant to depicting the system's behavior can then be evaluated. In addition, one can assess the space-time distribution of measurement points, which is the most influential factor for the identifiability of parameters. Our work indicates that these methods can be valuable tools in the proper design of model-based transport experiments.
引用
收藏
页数:14
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