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International Journal of Environment Science and Technology
Center for Environment and Energy Research and Studies (CEERS)
ISSN: 1735-1472 EISSN: 1735-1472
Vol. 12, No. 3, 2015, pp. 919-928
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Bioline Code: st15083
Full paper language: English
Document type: Research Article
Document available free of charge
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International Journal of Environment Science and Technology, Vol. 12, No. 3, 2015, pp. 919-928
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Bayesian approach to quantify parameter uncertainty and impacts on predictive flow and mass transport in heterogeneous aquifer
Liang, J.; Zeng, G. M.; Shen, S.; Guo, S. L.; Li, X. D.; Tan, Y.; Li, Z. W. & Li, J. B.
Abstract
Groundwater flow and mass transport predictions
are subjected to uncertainty due to heterogeneity of
hydraulic conductivity, whose variability in space is considerably
higher than that of other hydraulic properties
relevant to groundwater flow. To characterize the distribution
of hydraulic conductivity, random space function
(RSF) is often used. The Bayesian approach was applied to
quantitatively study the effect of parameter uncertainty in
RSF on a hypothetical two-dimensional uniform groundwater
flow and mass transport. Specifically, the parameter
uncertainty transmitted to macrodispersion in mass transport
model was also inferred. The results showed that the
posterior probability distributions of parameters were
updated after Bayesian inference. The numerical experiments
indicated that the overall predictive uncertainty was
increased with simulating time along the flow direction. As
to the relative contribution of the two types of uncertainty,
it indicated that parametric uncertainty was a little more
important than stochastic uncertainty for the predictive
uncertainty of hydraulic head. When the uncertainty of
hydraulic head as well as macrodispersion was transported
to mass transport model, a much bigger contribution of
stochastic uncertainty was observed. Therefore, parametric
uncertainty should not be neglected during the process of
subsurface simulation.
Keywords
Groundwater; Heterogeneous; Bayesian approach; Uncertainty; Hydraulic conductivity
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