Groundwater flow inverse modeling in non-MultiGaussian media: performance assessment of the normal-score Ensemble Kalman Filter

Li, L.; Zhou, H.; Gomez-Hernandez, J.J.; Hendricks-Franssen, H.J.

doi:10.5194/hess-16-573-2012

Journal Article

Groundwater flow inverse modeling in non-MultiGaussian media: performance assessment of the normal-score Ensemble Kalman Filter

Li, L. ; Zhou, H. ; Hendricks-Franssen, H. J.FZJ* ; Gomez-Hernandez, J. J.

2012
EGU Katlenburg-Lindau

Hydrology and earth system sciences 16, 573 - 590 (2012) [10.5194/hess-16-573-2012]

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Please use a persistent id in citations: http://hdl.handle.net/2128/7479 doi:10.5194/hess-16-573-2012

Abstract: The normal-score ensemble Kalman filter (NS-EnKF) is tested on a synthetic aquifer characterized by the presence of channels with a bimodal distribution of its hydraulic conductivities. This is a clear example of an aquifer that cannot be characterized by a multiGaussian distribution. Fourteen scenarios are analyzed which differ among them in one or various of the following aspects: the prior random function model, the boundary conditions of the flow problem, the number of piezometers used in the assimilation process, or the use of covariance localization in the implementation of the Kalman filter. The performance of the NS-EnKF is evaluated through the ensemble mean and variance maps, the connectivity patterns of the individual conductivity realizations and the degree of reproduction of the piezometric heads. The results show that (i) the localized NS-EnKF can characterize the non-multiGaussian underlying hydraulic distribution even when an erroneous prior random function model is used, (ii) localization plays an important role to prevent filter inbreeding and results in a better logconductivity characterization, and (iii) the NS-EnKF works equally well under very different flow configurations.

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Note: The authors gratefully acknowledge the financial support by the Spanish Ministry of Science and Innovation through project CGL2011-23295. The two anonymous reviewers are gratefully acknowledged for their comments which helped improving the final version of the manuscript.

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