MT3DMS: Model use, calibration, and validation

Transactions of the ASABE

Volumn 55, Issue 4, 2012, Pages 1549-1559

  Zheng, C ^a,b   Hill, M C ^c   Cao, G ^a   Ma, R ^d  

^a PEKING UNIVERSITY   (China)

^b Department of Geological Sciences ^*  (United States)

^c U S GEOLOGICAL SURVEY   (United States)

^d CHINA UNIVERSITY OF GEOSCIENCES   (China)

Author keywords

Contaminant transport modeling; Groundwater age simulation; Groundwater contamination; Groundwater modeling; Groundwater remediation; MODFLOW; MT3DMS

Indexed keywords

CONTAMINANT TRANSPORT MODELING; GROUND WATER REMEDIATION; GROUNDWATER AGES; GROUNDWATER CONTAMINATION; GROUNDWATER MODELING; MODFLOW; MT3DMS;

CALIBRATION; GROUNDWATER; GROUNDWATER FLOW; MODELS; SOLUTE TRANSPORT;

THREE DIMENSIONAL;

ADVECTION-DIFFUSION EQUATION; DISCRETE ELEMENT METHOD; DISPERSION; FINITE DIFFERENCE METHOD; FLOW MODELING; GROUNDWATER FLOW; GROUNDWATER POLLUTION; MASS TRANSPORT; POLLUTANT TRANSPORT; REMEDIATION; SOLUTE TRANSPORT; THREE-DIMENSIONAL MODELING;

UNITED STATES;

EID: 84867394855     PISSN: 21510032     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (63)

1. Anderman, E. R., M. C. Hill, and E. P. Poeter. 1996. Two-dimensional advective transport in ground-water flow parameter estimation. Ground Water 34(6): 1001-1009.
2. Barlebo, H. C., M. C. Hill, D. Rosbjerg, and K. H. Jensen. 1998. Concentration data and dimensionality in groundwater models: Evaluation using inverse modeling. Nordic Hydrol. 29(3): 149-178.
3. Barlebo, H. C., M. C. Hill, and D. Rosbjerg. 2004. Investigating the macrodispersion experiment (MADE) site in Columbus, Mississippi, using a three-dimensional inverse flow and transport model. Water Resources Res. 40(4): W04211, doi: 10.1029/2002WR001935.
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(3-4): 251-277.
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(3-4): 107-129.
6. Barth, G. R., T. H. Illangasekare, M. C. Hill, and H. Rajaram. 2001a. A new tracer-density criterion for heterogeneous porous media. Water Resources Res. 37(1): 21-31.
7. Barth, G. R., M. C. Hill, T. H. Illangasekare, and H. Rajaram. 2001b. Predictive modeling of flow and transport in a two-dimensional intermediate-scale, heterogeneous porous media. Water Resour. Res. 37(10): 2503-2512.
8. Bianchi, M., C. Zheng, G. R. Tick, and S. M. Gorelick. 2011. Investigation of small-scale preferential flow with a forced-gradient tracer test. Ground Water 49(4): 503-514.
9. Cao, G. 2011. Recharge estimation and sustainability assessment of groundwater resources in the North China Plain. Unpublished PhD diss. Tuscaloosa, Ala.: University of Alabama, Department of Geological Sciences.
10. Clark, M. P., D. Kavetski, and F. Fenicia. 2011. Pursuing the method of multiple working hypotheses for hydrological modeling. Water Resour. Res. 47: W09301, doi: 10.1029/2010WR009827.
11. Clement, T. P. 1997. RT3D: A modular computer code for simulating reactive multi-species transport in 3-dimensional groundwater aquifers. PNNL-11720. Richland, Wash.: Pacific Northwest National Laboratory. Available at: http://bioprocess. pnnl.gov/rt3d.publications.htm. Accessed 8 January 2012.
12. Doherty, J. 2010. PEST User's Guide. Bethesda, Md.: S.S. Papadopulos and Associates, Inc.
13. Feehley, C. E., C. Zheng, and F. J. Molz. 2000. A dual-domain mass transfer approach for modeling solute transport in heterogeneous porous media: Application to the MADE site. Water Resour. Res. 36(9): 2501-2515.
14. Foglia, L., S. W. Mehl, M. C. Hill, P. Perona, and P. Burlando. 2007. Testing alternative ground water models using cross-validation and other methods. Ground Water 45(5): 627-641.
15. Foglia, L., M. C. Hill, S. W. Mehl, and P. Burlando. 2009. Sensitivity analysis, calibration, and testing of a distributed hydrological model using error-based weighting and one objective function. Water Resour. Res. 45: W06427, doi: 10.1029/2008WR007255.
16. Foglia, L., S. W. Mehl., M. C. Hill, and P. Burlando. 2012. Analysis of model discrimination techniques: The case of the Maggia Valley, southern Switzerland. Water Resour. Res. (in review).
17. Goode, D. J. 1996. Direct simulation of groundwater age. Water Resour. Res. 32(2): 289-296.
18. Greskowiak, J., H. Prommer, C. Liu, V. E. A. Post, R. Ma, C. Zheng, and J. M. Zachara. 2010. Comparison of parameter sensitivities between a laboratory and field-scale model of uranium transport in a dual-domain, distributed-rate reactive system. Water Resour. Res. 46: W09509, doi: 10.1029/2009WR008781.
19. Halford, K. J., and R. T. Hanson. 2002. User guide for the drawdown-limited, multimode well (MNW) package for the U.S. Geological Survey's modular three-dimensional finite-difference ground-water flow model, versions MODFLOW-96 and MODFLOW-2000. USGS Open-File Report 02-293. Reston, Va.: U.S. Geological Survey.
20. Harbaugh, A. W. 2005. MODFLOW-2005, the U.S. Geological Survey modular ground-water model: The ground-water flow process. USGS Techniques and Methods 6-A16. Reston, Va.: U.S. Geological Survey.
21. Harbaugh, A. W., and M. G. McDonald. 1996. User's documentation for MODFLOW-96, an update to the U.S. Geological Survey modular finite-difference ground-water flow model. USGS Open-File Report 96-485. Reston, Va.: U.S. Geological Survey.
22. Harbaugh, A. W., E. R. Banta, M. C. Hill, and M. G. McDonald. 2000. MODFLOW-2000, The U.S. Geological Survey modular ground-water model: User guide to modularization concepts and the ground-water flow process. Reston, Va.: U.S. Geological Survey.
23. Hill, M. C. 1998. Methods and guidelines for effective model calibration. USGS Water-Resources Investigations Report 98-4005. Reston, Va.: U.S. Geological Survey.
24. Hill, M. C. 2006. The practical use of simplicity in developing ground water models. Ground Water 44(6): 775-781.
25. Hill, M. C. 2010. Comment on "Two statistics for evaluating parameter identifiability and error reduction" by John Doherty and Randall J. Hunt. J. Hydrol. 380(3-4): 481-488.
26. Hill, M. C., and C. R. Tiedeman. 2007. Effective Groundwater Model Calibration: With Analysis of Sensitivities, Predictions, and Uncertainty. New York, N.Y.: Wiley.
27. Hunt, R. J., J. Doherty, and M. Tonkin. 2007. Are models too simple? Arguments for increased parameterization. Ground Water 45(3): 254-262.
28. Julian, H. E., J. M. Boggs, C. Zheng, and C. E. Feehley. 2001. Numerical simulation of a natural gradient tracer experiment for the natural attenuation study: Flow and physical transport. Ground Water 39(4): 534-545.
29. Konikow, L. F. 2011. The secret to successful solute-transport modeling. Ground Water 49(2):144-159.
30. Konikow, L. F., and J. D. Bredehoeft. 1992. Ground-water models cannot be validated. Adv. Water Resour. 15(1): 75-83.
31. Langevin, C. D., D. T. Thorne Jr., A. M. Dausman, M. C. Sukop, and W. Guo. 2007. SEAWAT version 4: A computer program for simulation of multi-species solute and heat transport. USGS Techniques and Methods, Book 6, Chapter A22. Reston, Va.: U.S. Geological Survey. Available at: http://water.usgs.gov/ogw/ seawat/. Accessed 8 January 2012.
32. Liu, G., C. Zheng, G. R. Tick, 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.
33. Lu, D., M. C. Hill, and M. Ye. 2012. Analysis of regression confidence intervals and Bayesian credible intervals for uncertainty quantification. Water Resour. Res. (in press).
34. Lu, G., T. P. Clement, C. Zheng, and T. H. Wiedemeier. 1999. Natural attenuation of BTEX compounds: Model development and field-scale application. Ground Water 37(5): 707-717.
35. Ma, R., C. Zheng, H. Prommer, J. Greskowiak, C. Liu, J. Zachara, and M. Rockhold. 2010. A field-scale reactive transport model for U(VI) migration influenced by coupled multi-rate mass transfer and surface complexation reactions. Water Resour. Res. 46: W05509, doi: 10.1029/2009WR008168.
36. Ma, R., C. Zheng, M. Tonkin, and J. M. Zachara. 2011. Importance of considering intraborehole flow in solute transport modeling under highly dynamic flow conditions. J. Contam. Hydrol. 123(1-2): 11-19.
37. Matotta, L. S., and A. J. Rabideaub. 2008. Calibration of complex subsurface reaction models using a surrogate-model approach. Advances in Water Resources 31(12): 1697-1707.
38. McDonald, M. G., and A. W. Harbaugh. 1988. A modular three-dimensional finite-difference ground-water flow model. USGS Techniques of Water-Resources Investigations, Book 6, Chapter A1. Reston, Va.: U.S. Geological Survey.
39. Mehl, S. W., and M. C. Hill. 2001. A comparison of solutetransport solution techniques and their effect on sensitivity analysis and inverse modeling results. Ground Water 39(2): 300-307.
40. Mehl, S. W., M. C. Hill, and S. A. Leake. 2006. Comparison of local grid refinement methods for MODFLOW. Ground Water 44(6): 792-796.
41. Newcomer, D. R., B. N. Bjornstad, and V. R. Vermeul. 2010. Vertical wellbore flow monitoring for assessing spatial and temporal flow relationships with a dynamic river boundary. Ground Water Monit. and Remed. 30(4): 123-135.
42. Niswonger, R. G., D. E. Prudic, and R. S. Regan. 2006. Documentation of the unsaturated-zone flow (UZF1) package for modeling unsaturated flow between the land surface and the water table with MODFLOW-2005. USGS Techniques and Methods 6-A19. Reston, Va.: U.S. Geological Survey.
43. NRC. 2007. Models in environmental regulatory decision making. Washington, D.C.: National Research Council, Committee on Models in the Regulatory Decision Process.
44. Parkhurst, D. L., and C. A. J. Appelo. 1999. User's guide to PHREEQC (version 2): A computer program for speciation, batch-reaction, one-dimensional transport, and inverse geochemical calculations. USGS Water-Resources Investigations Report 99-4259. Reston, Va.: U.S. Geological Survey.
45. Poeter, E. P., and M. C. Hill. 2007. MMA: A computer code for multi-model analysis. USGS Techniques and Methods 6-E3. Reston, Va.: U.S. Geological Survey. Available at: http://typhoon.mines.edu/freeware/mma/.
46. Poeter, E. P., M. C. Hill, E. R. Banta, S. Mehl, and S. Christensen. 2005. UCODE-2005 and six other computer codes for universal sensitivity analysis, calibration, and uncertainty evaluation. USGS Techniques and Methods 6-A11. Reston, Va.: U.S. Geological Survey. Available at: http://typhoon. mines.edu/freeware/ucode/.
47. Prommer, H., D. A. Barry, and C. Zheng. 2003. MODFLOW/MT3DMS-based multicomponent reactive transport model. Ground Water 41(2): 247-257.
48. Renard, B., D. Kavetski, E. Leblois, M. Thyer, G. Kuczera, and S. W. Franks. 2011. Toward a reliable decomposition of predictive uncertainty in hydrological modeling: Characterizing rainfall errors using conditional simulation. Water Resour. Res. 47: W11516, doi: 10.1029/2011WR010643.
49. Sanford, W. E. 1997. Correcting for diffusion in carbon-14 dating of ground water. Ground Water 35: 357-361.
50. Sun, N.-Z. 1994. Inverse Problems in Groundwater Modeling. Boston. Mass.: Kluwer Academic.
51. Tonkin, M., C. R. Tiedeman, D. M. Ely, and M. C. Hill. 2007. OPR-PPR: A computer program for assessing data importance to model predictions using linear statistics. USGS Techniques and Methods 6-E2. Reston, Va.: U.S. Geological Survey. Available at: http://water.usgs.gov/software/OPR-PPR.html.
52. Waddill, D. W., and M. A. Widdowson. 1998. A three-dimensional model for subsurface transport and biodegradation. ASCE J. Environ. Eng. 124(4): 336-344.
53. Wang, M., and C. Zheng. 1997. Optimal remediation policy selection under general conditions. Ground Water 35(5): 757-764.
54. 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.
55. Zheng, C. 1990. MT3D: A modular three-dimensional transport model for simulation of advection, dispersion, and chemical reactions of contaminants in groundwater systems. Report to the U.S. Environmental Protection Agency. Available at: www.epa.gov/ada/csmos.html.
56. Zheng, C. 1993. Extension of the method of characteristics for simulation of solute transport in three dimensions. Ground Water 31(3): 456-465.
57. Zheng, C. 2009. Recent developments and future directions for MT3DMS and related transport codes. Ground Water 47(5): 620-625.
58. Zheng, C. 2010. MT3DMS 5.3 supplemental user's guide. Tuscaloosa, Ala.: University of Alabama, Department of Geological Sciences. Available at: http://hydro.geo.ua. edu/mt3d/.
59. Zheng, C. 2011. Reflections: 2002-2009. Ground Water 49(2): 129-132.
60. Zheng, C., and G. D. Bennett. 2002. Applied Contaminant Transport Modeling. 2nd ed. New York, N.Y.: John Wiley and Sons.
61. Zheng, C., and P. P. Wang. 1999. MT3DMS: A modular three-dimensional multi-species transport model for simulation of advection, dispersion, and chemical reactions of contaminants in groundwater systems. Documentation and User's Guide, Contract Report SERDP-99-1. Vicksburg, Miss.: U.S. Army Engineer Research and Development Center. Available at: http://hydro.geo.ua.edu/mt3d/.
62. Zheng, C., and P. P. Wang. 2002. A field demonstration of the simulation-optimization approach for remediation system design. Ground Water 40(3): 258-265.
63. Zheng, C., M. Bianchi, and S. M. Gorelick. 2011. Lessons learned from 25 years of research at the MADE site. Ground Water 49(5): 649-662.