Characterization of groundwater contaminant source using Bayesian method

Stochastic Environmental Research and Risk Assessment

Volumn 27, Issue 4, 2013, Pages 867-876

  Wang, Hui ^a   Jin, Xin ^b  

^a UNIVERSITY OF TEXAS AT AUSTIN   (United States)

^b Boise State University   (United States)

Author keywords

Bayesian application; Contaminant sources; Groundwater management; Probabilistic inference

Indexed keywords

BAYESIAN NETWORKS; CONTAMINATION; GROUNDWATER; HYDRAULIC CONDUCTIVITY; INFERENCE ENGINES; INVERSE PROBLEMS; MARKOV CHAINS; MONTE CARLO METHODS; PROBABILITY DISTRIBUTIONS; THREE DIMENSIONAL COMPUTER GRAPHICS; UNCERTAINTY ANALYSIS; WATER MANAGEMENT;

BAYESIAN; CONCENTRATION MEASUREMENT; CONTAMINANT SOURCE IDENTIFICATIONS; CONTAMINANT SOURCES; GROUNDWATER MANAGEMENT; MARKOV CHAIN MONTE CARLO; PROBABILISTIC INFERENCE; THREE DIMENSIONAL GROUNDWATER MODEL;

GROUNDWATER POLLUTION;

BAYESIAN ANALYSIS; ERROR ANALYSIS; GROUNDWATER; GROUNDWATER POLLUTION; HYDRAULIC CONDUCTIVITY; MONTE CARLO ANALYSIS; POLLUTANT SOURCE; PROBABILITY; REMEDIATION; THREE-DIMENSIONAL MODELING; UNCERTAINTY ANALYSIS; WATER MANAGEMENT;

EID: 84876084268     PISSN: 14363240     EISSN: 14363259     Source Type: Journal    
DOI: 10.1007/s00477-012-0622-9     Document Type: Article

References (26)

1. Atmadja J, Bagtzoglou AC (2001) Pollution source identification in heterogeneous porous media. Water Resour Res. doi: 10. 1029/2001WR000223.
2. Bauer S, Bayer-Raich M, Holder T, Kolesar C, Muller C, Ptak T (2004) Quantification of groundwater contamination in an urban area using integral pumping tests. J Contam Hydrol 75: 183-213. doi: 10. 1016/j. jconhyd. 2004. 06. 002.
3. Bear J (1979) Hydraulics of groundwater. McGraw-Hill, New York.
4. Carlin BP, Louis TA (2009) Bayesian methods for data analysis. CRC Press, Boca Raton.
5. Cowles MK, Carlin PB (1996) Markov Chain Monte Carlo convergence diagnostics: a comparative review. J Am Stat Assoc 91: 883-904.
6. Duffy C, Brandes D (2001) Dimension reduction and source identification for multispecies groundwater contamination. J Contam Hydrol 48: 151-165. doi: 10. 1016/S0169-7722(00)00169-8.
7. Gelfand AE, Smith AFM (1990) Sampling-based approaches to calculating marginal densities. J Am Stat Assoc 85: 398-409.
8. Gelman A, Carlin JB, Stern HS, Rubin DS (1995) Bayesian data analysis. Chapman & Hall, London.
9. Gilks WR, Richardson S, Spiegelhalter DJ (1996) Introducing Markov Chain Monte Carlo. In: Gilks WR, Richardson S, Spiegelhalter DJ (eds) Markov Chain Monte Carlo in practice. Chapman & Hall, London.
10. Guo S, Yang R, Zhang H, Weng W, Fan W (2009) Source identification for unsteady atmospheric dispersion of hazardous materials using MCMC method. Int J Heat Mass Transf 52: 3955-3962.
11. Hassan AE, Bekhit MH, Chapman JB (2009) Using Markov Chain Monte Carlo to quantify parameter uncertainty and its effect on predictions of a groundwater flow model. Environ Model Softw 24: 749-763.
12. Hastings WK (1970) Monte Carlo sampling methods using Markov chains and their applications. Biometrika 57: 97-109.
13. Hazart A, Giovannelli JF, Dubost S, Chatellier L (2007) Contaminant source estimation in a two-layers porous environment using a Bayesian approach. In: IEEE international geoscience and remote sensing symposium.
14. Huang CL, Hu B, Li X, Ye M (2011) Using data assimilation method to calibrate a heterogeneous conductivity field and improve solute transport prediction with an unknown contamination source. Stoch Env Res Risk Assess 23(8): 1155-1167.
15. Jin X, Mahinthakumar G, Zechman E, Ranjithan RS (2009) A genetic algorithm-based procedure for 3D source identification at the Borden emplacement site. J Hydroinfo 11(1): 51-64.
16. Joseph AS, Adams JB, McCabe B (2010) Methodology for Bayesian belief network development to facilitate compliance with water quality regulations. J Infrastruct Syst 16(1): 58-65.
17. Li Z, Mao X (2011) Global multiquadric collocation method for groundwater contaminant source identification. Environ Model Softw. doi: 10. 1016/j. envsoft. 2011. 07. 010.
18. Liu X, Cardiff MA, Kitanidis PK (2010) Parameter estimation in nonlinear environmental problems. Stoch Environ Res Risk Assess 24: 1003-1022.
19. Mahinthakumar G (1999) PGREM3D: massively parallel codes for groundwater flow and transport online manual. Available at http://www4. ncsu. edu/~gmkumar/pgrem3d. pdf. Accessed 10 Dec 2011.
20. Mirghani BY, Mahinthakumar KG, Tryby ME, Ranjithan RS, Zechman EM (2009) A parallel evolutionary strategy based simulation-optimization approach for solving groundwater source identification problems. Adv Water Resour 32(9): 1373-1385.
21. Olmez I, Beal JW, Villaume JF (1994) A new approach to understanding multiple-source groundwater contamination: factor analysis and chemical mass balance. Water Res. doi: 10. 1016/0043-1354(94)90195-3.
22. Rivette MO, Feenstra S, Cherry JA (2001) A controlled field experiment on groundwater contaminant by a multicomponent DNAPL: creation of the emplaced-source and overview of dissolved plume development. J Contam Hydrol 49: 111-149.
23. Sun NZ (1994) Inverse problems in groundwater modelling. Kluwer Academics, Norwell.
24. Tompson AFB, Aboudu R, Gelhar LW (1989) Implementation of the three-dimensional turning bands random field generator. Water Resour Res 25(10): 2227-2243.
25. Wang H, Harrison KW (in press) Bayesian update method for contaminant source characterization in water distribution systems. J Water Resour Plan Manag. doi: 10. 1061/(ASCE)WR. 1943-5452. 0000221.
26. Zheng C, Wang PP (1999) MT3DMS: a modular three-dimensional multispecies transport model for simulation of advection, dispersion, and chemical reactions of contaminants in groundwater systems; documentation and user's guide.