A Bayesian Modeling Approach for Estimation of a ShapeFree Groundwater Age Distribution using Multiple Tracers
The mixing of groundwaters with different ages in aquifers, groundwater age is more appropriately represented by a distribution rather than a scalar number. To infer a groundwater age distribution from environmental tracers, a mathematical form is often assumed for the shape of the distribution and the parameters of the mathematical distribution are estimated using deterministic or stochastic inverse methods. We found that the prescription of the mathematical form limits the exploration of the age distribution to the shapes that can be described by the selected distribution. In this paper, the use of freeform histograms as groundwater age distributions is evaluated. A Bayesian Markov Chain Monte Carlo approach is used to estimate the fraction of groundwater in each histogram bin. This method was able to capture the shape of a hypothetical gamma distribution from the concentrations of four age tracers. The number of bins that can be considered in this approach is limited based on the number of tracers available. The histogram method was also tested on tracer data sets from Holten (The Netherlands; ^{3}H, ^{3}He, ^{85}Kr, ^{39}Ar) and the La Selva Biological Station (CostaRica; SF_{ 6}, CFCs, ^{3}H, ^{4}He and ^{14}C), and compared to a number of mathematical forms. Accordingmore »
 Authors:

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 The Catholic Univ. of America, Washington, DC (United States)
 Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
 Deltares, Utrecht (Netherlands); Geological Survey of the Netherlands, Utrecht (Netherlands); VU Univ., Amsterdam (Netherlands)
 Publication Date:
 OSTI Identifier:
 1237523
 Report Number(s):
 LLNLJRNL637575
Journal ID: ISSN 08832927
 Grant/Contract Number:
 AC5207NA27344
 Type:
 Accepted Manuscript
 Journal Name:
 Applied Geochemistry
 Additional Journal Information:
 Journal Volume: 50; Journal ID: ISSN 08832927
 Publisher:
 Elsevier
 Research Org:
 Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
 Sponsoring Org:
 USDOE
 Country of Publication:
 United States
 Language:
 English
 Subject:
 54 ENVIRONMENTAL SCIENCES
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