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

Water Resources Research

Volumn 49, Issue 9, 2013, Pages 5206-5220

  Ciriello, Valentina ^a   Guadagnini, Alberto ^b,c   Di Federico, Vittorio ^a   Edery, Yaniv ^d   Berkowitz, Brian ^d  

^a UNIVERSITY OF BOLOGNA   (Italy)

^b POLITECNICO DI MILANO   (Italy)

^c UNIVERSITY OF ARIZONA   (United States)

^d WEIZMANN INSTITUTE OF SCIENCE   (Israel)

Author keywords

conservative transport experiment; continuous time random walk; global sensitivity analysis; parameter calibration; polynomial chaos expansion

Indexed keywords

ADVECTION; CALIBRATION; CONTINUOUS TIME SYSTEMS; MASS TRANSFER; MAXIMUM LIKELIHOOD; PARAMETER ESTIMATION; POROSITY; POROUS MATERIALS; RANDOM PROCESSES; SCALES (WEIGHING INSTRUMENTS); SENSITIVITY ANALYSIS;

CONTINUOUS TIME RANDOM WALKS; GLOBAL SENSITIVITY ANALYSIS; PARAMETER CALIBRATION; POLYNOMIAL CHAOS EXPANSION; TRANSPORT EXPERIMENTS;

LEARNING TO RANK;

ADVECTION-DIFFUSION EQUATION; CALIBRATION; COMPARATIVE STUDY; DUAL POROSITY; EXPERIMENTAL DESIGN; MASS TRANSFER; MAXIMUM LIKELIHOOD ANALYSIS; PARAMETERIZATION; POROUS MEDIUM; PROBABILITY; SENSITIVITY ANALYSIS; SOLUTE TRANSPORT; TRACER;

EID: 84883271848     PISSN: 00431397     EISSN: 19447973     Source Type: Journal    
DOI: 10.1002/wrcr.20395     Document Type: Article

References (47)

1. Abramowitz, M., and, I. A. Stegun, (1970), Handbook of Mathematical Functions, Dover, New York.
2. Akaike, H., (1974), A new look at statistical model identification, IEEE Trans. Autom. Control, 19, 716-723.
3. Archer, G. E. B., A. Saltelli, and, I. M. Sobol, (1997), Sensitivity measures, ANOVA like techniques and the use of bootstrap, J. Stat. Comput. Simul., 58, 99-120.
4. Barth, G. R., and, M. C. Hill, (2005a), Numerical methods for improving sensitivity analysis and parameter estimation of virus transport simulated using sorptive-reactive processes, J. Contam. Hydrol., 76, 251-277. (Pubitemid 40416875)
5. Barth, G. R., and, M. C. Hill, (2005b), Parameter and observation importance in modeling virus transport in saturated systems - Investigations in a homogenous system, J. Contam. Hydrol., 80, 107-129. (Pubitemid 41531682)
6. Berkowitz, B., and, H. Scher, (2009), Exploring the nature of non-Fickian transport in laboratory experiments, Adv. Water Resour., 32, 750-755.
7. Berkowitz, B., A. Cortis, M. Dentz, and, H. Scher, (2006), Modeling non-Fickian transport in geological formations as a continuous time random walk, Rev. Geophys., 44, RG2003, doi: 10.1029/2005RG000178.
8. Bianchi Janetti, E., I. Dror, M. Riva, A. Guadagnini, and, B. Berkowitz, (2012), Estimation of single-metal and competitive sorption isotherms through maximum likelihood and model quality criteria, Soil Sci. Soc. Am. J., 76, 1229-1245.
9. Cameron, R. H., and, W. T. Martin, (1947), The orthogonal development of nonlinear functionals in series of Fourier-Hermite functionals, Ann. Math., 48 (2), 385-392.
10. Carrera, J., and, S. P. Neuman, (1986), Estimation of aquifer parameters under transient and steady state conditions: 1. Maximum likelihood method incorporating prior information, Water. Resour. Res., 22 (2), 199-210. (Pubitemid 16477839)
11. Ciriello, V., and, V. Di Federico, (2013), Analysis of a benchmark solution for non-Newtonian radial displacement in porous media, Int. J. Nonlinear Mech., 52, 46-57, doi: 10.1016/j.ijnonlinmec.2013.01.011.
12. Ciriello, V., V. Di Federico, M. Riva, F. Cadini, J. De Sanctis, E. Zio, and, A. Guadagnini, (2013), Polynomial chaos expansion for global sensitivity analysis applied to a model of radionuclide migration in a randomly heterogeneous aquifer, Stochastic Environ. Res. Risk. Assess., 27, 945-954, doi: 10.1007/s00477-012-0616-7.
13. Cortis, A., and, B. Berkowitz, (2005), Computing "anomalous" contaminant transport in porous media: the CTRW Matlab toolbox, Ground Water, 43, 947-950. (Pubitemid 41681850)
14. Dentz, M., A. Cortis, H. Scher, and, B. Berkowitz, (2004), Time behavior of solute transport in heterogeneous media: transition from anomalous to normal transport, Adv. Water Resour., 27, 155-173. (Pubitemid 38242169)
15. Doherty, J., (2002), PEST: Model Independent Parameter Estimation, User Manual, 4th ed., Watermark Numer. Comput., Corinda, Queensland.
16. Fajraoui, N., F. Ramasomanana, A. Younes, T. A. Mara, P. Ackerer, and, A. Guadagnini, (2011), Use of global sensitivity analysis and polynomial chaos expansion for interpretation of nonreactive transport experiments in laboratory-scale porous media, Water Resour. Res., 47, W02521, doi: 10.1029/2010WR009639.
17. Fajraoui, N., T. A. Mara, A. Younes, and, R. Bouhlila, (2012), Reactive transport parameter estimation and global sensitivity analysis using sparse polynomial chaos expansion, Water Air Soil Pollut., 223 (7), 4183-4197.
18. Foglia, L., S. W. Mehl, M. C. Hill, and, P. Burlando, (2013), Evaluating model structure adequacy: The case of the Maggia Valley groundwater system, southern Switzerland, Water Resour. Res., 49, 260-282, doi: 10.1029/ 2011WR011779.
19. Ghanem, R. G., and, P. D. Spanos, (1991), Stochastic Finite Elements - A Spectral Approach, Springer, Berlin.
20. Gramling, C. M., C. F. Harvey, and, L. C. Meigs, (2002), Reactive transport in porous media: a comparison of model prediction with laboratory visualization, Environ. Sci. Technol., 36, 2508-2514. (Pubitemid 34595192)
21. Hernandez, A. F., S. P. Neuman, A. Guadagnini, and, J. Carrera, (2006), Inverse stochastic moment analysis of steady state flow in randomly heterogeneous media, Water Resour. Res., 42, W05425, doi: 10.1029/2005WR004449.
22. Huang, H., A. E. Hassan, and, B. X. Hu, (2003), Monte Carlo study of conservative transport in heterogeneous dual-porosity media, J. Hydrol., 275, 229-241. (Pubitemid 36521808)
23. Hurvich, C. M., and, C. L. Tsai, (1989), Regression and time series model selection in small sample, Biometrika, 76 (2), 297-307.
24. Kashyap, R. L., (1982), Optimal choice of AR and MA parts in autoregressive moving average models, IEEE Trans. Pattern Anal. Mach. Intel., 4 (2), 99-104.
25. Liu, G., C. Zheng, G. R. Tick, J. J. Butler Jr,., and, S. M. Gorelick, (2010), Relative importance of dispersion and rate limited mass transfer in highly heterogeneous porous media: Analysis of a new tracer test at the Macrodispersion Experiment (MADE) site, Water Resour. Res., 46, W03524, doi: 10.1029/2009WR008430.
26. Nataf, A., (1962), Détermination des distributions dont les marges sont données, C. R. Hebd. Seances Acad. Sci., 225, 42-43.
27. Neuman, S. P., (2003), Maximum likelihood Bayesian averaging of alternative conceptual-mathematical models, Stochastic Environ. Res. Risk Assess., 17 (5), 291-305, doi: 10.1007/s00477-003-0151-7. (Pubitemid 38013163)
28. Neuman, S. P., L. Xue, M. Ye, and, D. Lu, (2012), Bayesian analysis of data-worth considering model and parameter uncertainty, Adv. Water Resour., 36, 75-85, doi: 10.1016/j.advwatres.2011.02.007.
29. Oladyshkin, S., F. P. J. de Barros, and, W. Nowak, (2012), Global sensitivity analysis: a flexible and efficient framework with an example from stochastic hydrogeology, Adv. Water Resour., 37, 10-22.
30. Riva, M., M. Panzeri, A. Guadagnini, and, S. P. Neuman, (2011), Role of model selection criteria in geostatistical inverse estimation of statistical data- and model-parameters, Water Resour. Res., 47, W07502, doi: 10.1029/2011WR010480.
31. Saltelli, A., S. Tarantola, and, F. Campolongo, (2000), Sensitivity analysis as an ingredient of modeling, Stat. Sci., 15 (4), 377-395.
32. Shi, L., D. Zhang, L. Lin, and, J. Yang, (2010), A multiscale probabilistic collocation method for subsurface flow in heterogeneous media, Water Resour. Res., 46, W11562, doi: 10.1029/2010WR009066.
33. Sobol, I. M., (1993), Sensitivity estimates for nonlinear mathematical models, Math. Model. Comput., 1, 407-414.
34. Sobol, I. M., (2001), Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates, Math. Comput. Simul., 55, 271-280. (Pubitemid 32672729)
35. Soize, C., and, R. Ghanem, (2004), Physical systems with random uncertainties: Chaos representations with arbitrary probability measures, J. Sci. Comput., 26 (2), 395-410. (Pubitemid 40449850)
36. Stehfest, H., (1970), Numerical inversion of Laplace transforms, Commun. ACM, 13 (1), 47-49.
37. Sudret, B., (2008), Global sensitivity analysis using polynomial chaos expansions, Reliab. Eng. Syst. Safety, 93, 964-979. (Pubitemid 351313888)
38. Tiedeman, C. R., and, M. C. Hill, (2007), Model calibration and issues related to validation, sensitivity analysis, post-audit, uncertainty evaluation and assessment of prediction data needs, in Groundwater, pp. 237-282, Springer, Netherlands.
39. Tiedeman, C. R., M. C. Hill, F. A. D'Agnese, and, C. C. Faunt, (2003), Methods for using groundwater model predictions to guide hydrogeologic data collection, with application to the Death Valley regional ground-water flow system, Water Resour. Res., 39 (1), 1010, doi: 10.1029/2001WR001255.
40. Tiedeman, C. R., D. M. Ely, M. C. Hill, and, G. M. O'Brien, (2004), A method for evaluating the importance of system state observations to model predictions, with application to the Death Valley regional groundwater flow system, Water Resour. Res., 40, W12411, doi: 10.1029/2004WR003313.
41. Volkova, E., B. Iooss, and, F. Van Dorpe, (2008), Global sensitivity analysis for a numerical model of radionuclide migration from the RRC "Kurchatov Institute" radwaste disposal site, Stochastic Environ. Res. Risk Assess., 22, 17-31. (Pubitemid 350142755)
42. Webster, M., M. A. Tatang, and, G. J. McRae, (1996), Application of the probabilistic collocation method for an uncertainty analysis of a simple ocean model, MIT Joint Program on the Sci. and Policy of Global Change Rep. Ser., Tech. Rep. 4, Mass. Inst. of Technol.
43. Wiener, N., (1938), The homogeneous chaos, Am. J. Math., 60, 897-936.
44. Xiu, D., and, G. E. Karniadakis, (2002), The Wiener-Askey polynomial chaos for stochastic differential equations, J. Sci. Comput., 24 (2), 619-644.
45. Ye, M., S. P. Neuman, and, P. D. Meyer, (2004), Maximum likelihood Bayesian averaging of spatial variability models in unsaturated fractured tuff. Water Resour. Res., 40, W05113, doi: 10.1029/2003WR002557.
46. Ye, M., P. D. Meyer, and, S. P. Neuman, (2008), On model selection criteria in multimodel analysis, Water Resour. Res., 44, W03428, doi: 10.1029/2008WR006803.
47. Zhang, D., L. Shi, H. Chang, and, J. Yang, (2010), A comparative study of numerical approaches to risk assessment of contaminant transport, Stochastic Environ. Res. Risk Assess., 24, 971-984.