Comparative analysis of formulations for conservative transport in porous media through sensitivity-based parameter calibration

被引:33
作者
Ciriello, Valentina [1 ]
Guadagnini, Alberto [2 ,3 ]
Di Federico, Vittorio [1 ]
Edery, Yaniv [4 ]
Berkowitz, Brian [4 ]
机构
[1] Univ Bologna, Dipartimento Ingn Civile Chim Ambientale & Mat, I-40136 Bologna, Italy
[2] Politecn Milan, Dipartimento Ingn Civile & Ambientale, I-20133 Milan, Italy
[3] Univ Arizona, Dept Hydrol & Water Resources, Tucson, AZ 85721 USA
[4] Weizmann Inst Sci, Dept Environm Sci & Energy Res, IL-76100 Rehovot, Israel
基金
以色列科学基金会;
关键词
parameter calibration; global sensitivity analysis; polynomial chaos expansion; conservative transport experiment; continuous time random walk; POLYNOMIAL CHAOS EXPANSION; GROUNDWATER-FLOW SYSTEM; NON-FICKIAN TRANSPORT; MAXIMUM-LIKELIHOOD; MODEL PREDICTIONS; RADIONUCLIDE MIGRATION; CONTAMINANT TRANSPORT; REACTIVE TRANSPORT; VIRUS TRANSPORT; MONTE-CARLO;
D O I
10.1002/wrcr.20395
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
We apply a general strategy based on Global Sensitivity Analysis (GSA) and model discrimination criteria to (a) calibrate the parameters embedded in competing models employed to interpret laboratory-scale tracer experiments, (b) rank these models, and (c) estimate the relative degree of likelihood of each model through a posterior probability weight. We consider a conservative transport experiment in a uniform porous medium. We apply GSA to three transport models, based on: the classical advection-dispersion equation (ADE), a dual-porosity (DP) formulation with mass transfer between mobile and immobile regions, and the Continuous Time Random Walk (CTRW) approach. GSA is performed through Polynomial Chaos Expansion of the governing equations, treating key model parameters as independent random variables. We show how this approach allows identification of (a) the relative importance of model-dependent parameters, and (b) the space-time locations, where the models are most sensitive to these parameters. GSA is then employed to assist parameter estimates within a Maximum Likelihood framework. Finally, formal model identification criteria are employed to (a) rank the alternative models, and (b) associate each model with a posterior probability weight for the specific case study. The GSA-based calibration of each model returns an acceptable approximation (remarkably accurate in the case of the CTRW model) of all available concentration data, with calibration being performed using minimum sets of observations corresponding to the most sensitive (space-time) locations.
引用
收藏
页码:5206 / 5220
页数:15
相关论文
共 47 条
[1]  
Abramowitz M., 1970, HDB MATH FUNCTIONS
[2]   NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION [J].
AKAIKE, H .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1974, AC19 (06) :716-723
[3]  
[Anonymous], 1996, MIT JOINT PROGRAM SC
[4]   Sensitivity measures, ANOVA-like techniques and the use of bootstrap [J].
Archer, GEB ;
Saltelli, A ;
Sobol, IM .
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 1997, 58 (02) :99-120
[5]   Numerical methods for improving sensitivity analysis and parameter estimation of virus transport simulated using sorptive-reactive processes [J].
Barth, G ;
Hill, MC .
JOURNAL OF CONTAMINANT HYDROLOGY, 2005, 76 (3-4) :251-277
[6]   Parameter and observation importance in modelling virus transport in saturated porous media - investigations in a homogenous system [J].
Barth, GR ;
Hill, MC .
JOURNAL OF CONTAMINANT HYDROLOGY, 2005, 80 (3-4) :107-129
[7]   Modeling non-Fickian transport in geological formations as a continuous time random walk [J].
Berkowitz, Brian ;
Cortis, Andrea ;
Dentz, Marco ;
Scher, Harvey .
REVIEWS OF GEOPHYSICS, 2006, 44 (02)
[8]   Exploring the nature of non-Fickian transport in laboratory experiments [J].
Berkowitz, Brian ;
Scher, Harvey .
ADVANCES IN WATER RESOURCES, 2009, 32 (05) :750-755
[9]   THE ORTHOGONAL DEVELOPMENT OF NON-LINEAR FUNCTIONALS IN SERIES OF FOURIER-HERMITE FUNCTIONALS [J].
CAMERON, RH ;
MARTIN, WT .
ANNALS OF MATHEMATICS, 1947, 48 (02) :385-392
[10]   ESTIMATION OF AQUIFER PARAMETERS UNDER TRANSIENT AND STEADY-STATE CONDITIONS .1. MAXIMUM-LIKELIHOOD METHOD INCORPORATING PRIOR INFORMATION [J].
CARRERA, J ;
NEUMAN, SP .
WATER RESOURCES RESEARCH, 1986, 22 (02) :199-210