Worth of secondary data compared to piezometric data for the probabilistic assessment of radionuclide migration |
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Authors: | José E Capilla J Rodrigo and J J Gómez-Hernández |
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Institution: | (1) Depto. de Física Aplicada Universidad Politécnica de Valencia E-46071 Valencia, Spain, ES;(2) Depto. de Ingeniería Hidráulica y Medio Ambiente Universidad Politécnica de Valencia E-46071 Valencia, Spain, ES |
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Abstract: | A common approach for the performance assessment of radionuclide migration from a nuclear waste repository is by means of
Monte-Carlo techniques. Multiple realizations of the parameters controlling radionuclide transport are generated and each
one of these realizations is used in a numerical model to provide a transport prediction. The statistical analysis of all
transport predictions is then used in performance assessment. In order to reduce the uncertainty on the predictions is necessary
to incorporate as much information as possible in the generation of the parameter fields. In this regard, this paper focuses
in the impact that conditioning the transmissivity fields to geophysical data and/or piezometric head data has on convective
transport predictions in a two-dimensional heterogeneous formation. The Walker Lake data based is used to produce a heterogeneous
log-transmissivity field with distinct non-Gaussian characteristics and a secondary variable that represents some geophysical
attribute. In addition, the piezometric head field resulting from the steady-state solution of the groundwater flow equation
is computed. These three reference fields are sampled to mimic a sampling campaign. Then, a series of Monte-Carlo exercises
using different combinations of sampled data shows the relative worth of secondary data with respect to piezometric head data
for transport predictions. The analysis shows that secondary data allows to reproduce the main spatial patterns of the reference
transmissivity field and improves the mass transport predictions with respect to the case in which only transmissivity data
is used. However, a few piezometric head measurements could be equally effective for the characterization of transport predictions. |
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Keywords: | : Self-Calibrated method Stochastic hydrology Conditional simulation Stochastic inversion |
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