Analysis of Uncertainties Affecting Numerical Transport Models for a Potential Radioactive Waste Disposal Site

Abstract:

Numerical models have been commonly used to study solute transport behaviours both in laboratory-and field-scale cases. However, numerical interpretation and predictions of solute transport are complicated by various uncertainties and therefore can be misleading and lead to incorrect understanding of solute transport behaviours in hydrogeological systems. Such uncertainties have been discussed with a case study of radionuclides transport at a potential site for disposal of Low-and Intermediate-Level radioactive Wastes (LILW) in southern China. Firstly, pre-modelling assumptions cause uncertainties for model performance and have a significant influence on the model output. Therefore, such assumptions and related factors should be thoroughly considered and minimized in laboratory experiments or investigated in the field. Secondly, difference in the calculated plumes caused by uncertainties in the development of conceptual models suggests that the hydrogeological conceptual model should be developed based on intrinsic understanding of the transport problems and relevant data collection. Thirdly, relative sensitivity (RS) has been calculated to analyse the parameter uncertainties. Results indicate that the uncertainties are tracer-, parameter-and time-dependent. Therefore, model uncertainties arising from parameters should be considered for each specific parameter with the specific period. Finally, prediction scenarios are associated with uncertainties in the model prediction stage. Results suggest that the uncertainties in scenarios of future transport conditions should be recognized prior to model prediction. This study illustrates some of the uncertainties that might affect numerical transport models and therefore will be a useful reference for application of solute transport models to assessment of contamination risks from a LILW disposal site.

• Periodical: Advanced Materials Research (Volumes 955-959)
• Pages: 1607-1614
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.955-959.1607
• Online since: June 2014
• Authors: Hai Yi Ma, Shu Ping Yi*, Guo Cheng Ren, Xue Ling Hu
• Keywords: LILW Disposal, Numerical Model, Relative Sensitivity, Solute Transport, Uncertainty

References

[1] Bear J (1972). Dynamics of fluids in porous media. Elsevier, New York.

[2] Reardon E J (1981). Kd's – Can they be used to describe reversible ion sorption reaction in contaminant migration?. Ground Water, 19(3): 279-286.

DOI: 10.1111/j.1745-6584.1981.tb03472.x

[3] Gillham R W and Cherry J A (1982). Contaminant Migration in Saturated Unconsolidated Geologic Deposits. Geological Society of American Special Paper, 189: 31-61.

DOI: 10.1130/spe189-p31

[4] Liu C W and Narasimhan T N (1989). Redox-controlled multiplespecies reactive chemical transport, 2, Verification and application. Water Resource Research, 25: 883-910.

DOI: 10.1029/wr025i005p00883

[5] Yeh G T and Tripathi V S (1991). A model for simulating transport of reactive multispecies components: model development and demonstration. Water Resource Research, 27(12): 3075-3094.

DOI: 10.1029/91wr02028

[6] Xu T, Pruess K, Brimhall G (1999). An improved equilibrium–kinetics speciation algorithm for redox reactions in variably saturated subsurface flow systems. Computed Geoscience, 25: 655–666.

DOI: 10.1016/s0098-3004(99)00005-9

[7] Zheng C and Wang P (1999).

[8] Van der Lee J, Windt L D (2001). Present state and future directions of modelling of geochemistry in hydrogeological systems. Journal of Contaminant Hydrology, 47: 265-282.

DOI: 10.1016/s0169-7722(00)00155-8

[9] Prommer H, Barry D A and Zheng C (2003). MODFLOW/MT3DMS-Based Reactive Multicomponent Transport Modeling. Ground Water, 41(2): 247-257.

DOI: 10.1111/j.1745-6584.2003.tb02588.x

[10] Palut J M, Montarnal P, Gautschi A et al (2003). Characterisation of HTO Diffusion properties by In-situ Tracer experiment in Opalinus clay at Mont Terri. Journal of Contaminant Hydrology, 61: 203-218.

DOI: 10.1016/s0169-7722(02)00134-1

[11] Wersin P, Van Loon L R et al (2004). Long-term Diffusion Experiment at Mont Terri: First Results from Field and Laboratory Data. Applied Clay Science, 26: 123-135.

DOI: 10.1016/j.clay.2003.09.007

[12] García-Gutiérrez M, Cormenzana J L, Missana T et al (2006). Large-scale laboratory diffusion experiments in clay rocks. Physics and Chemistry of the Earth, 31: 523-530.

DOI: 10.1016/j.pce.2006.04.004

[13] Samper J, Yang C, Naves A et al (2006). A fully 3-D anisotropic numerical model of the DI-B in situ diffusion experiment in the Opalinus clay formation. Physics and Chemistry of the Earth, Parts A/B/C 31: 531-540.

DOI: 10.1016/j.pce.2006.04.017

[14] Appelo A C, Wersin P (2007). Multicomponent diffusion modeling in clay systems with application to the diffusion of Tritium, Iodide, and Sodium in Opalinus Clay. Environment Science Technology, 41: 5002-5007.

DOI: 10.1021/es0629256

[15] Ma R, Zheng C, Prommer H, Greskowiak J, Liu C, Zachara J, Rockhold M (2010).

[16] Yi S, Javier S, Acacia N, Josep M S (2012a). Identifiabiligy of diffusion and retention parameters of anionic tracers from the DR experiment. Journal of Hydrology, 446-447: 70-76.

DOI: 10.1016/j.jhydrol.2012.04.032

[17] El-Ghonemy H, Len W, Linda F (2005). Treatment of uncertainty and developing conceptual models for environmental risk assessments and radioactive waste disposal safety cases. Environment International, 31: 89-97.

DOI: 10.1016/j.envint.2004.07.002

[18] Samper J, Yi S, Naves A (2010). Analysis of the parameter identifiability of the in situ diffusion and retention （DR） experiment. Physics and Chemistry of the Earth, 35: 207-216.

DOI: 10.1016/j.pce.2010.04.012

[19] Yi S, Hanyi M, Zheng C, Zhu X, Wang H, Li X, Hu X, Qin J (2012b). Assessment of condictions for disposal of low- and intermediate-level radioactive wastes: A case study in sourthern China. Science of the Total Environment, 414: 624-631.

DOI: 10.1016/j.scitotenv.2011.10.060

[20] Zheng C and Bennett G D (2002). Applied contaminant transport modeling. John Wiley & Sons, Inc., New York.