Upscaling and Inverse Modeling of Groundwater Flow and Mass ...

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140 BIBLIOGRAPHY Wen, X., Deutsch, C., Cullick, A., 2002. Construction of geostatistical aquifer models integrating dynamic flow and tracer data using inverse technique. Journal of Hydrology 255 (1-4), 151–168. Wen, X. H., Chen, W., 2005. Real-time reservoir model updating using ensemble Kalman filter. In: SPE reservoir simulation symposium. Yeh, W., 1986. Review of parameter identification procedures in groundwater hydrology: The inverse problem. Water Resources Research 22 (2), 95–108. Zheng, C., Wang, P., TUSCALOOSA., A. U., 1999. MT3DMS: A modular three-dimensional multispecies transport model for simulation of advection, dispersion, and chemical reactions of contaminants in groundwater systems; Documentation and user’s guide. Zhou, H., Gómez-Hernández, J. J., Hendricks Franssen, H., Li, L., 2011a. Handling non-gaussian distributions with Ensemble Kalman Filter. Advances in Water Resources, in press, doi:10.1016/j.advwatres.2011.04.014. Zhou, H., Li, L., Gómez-Hernández, J. J., 2010. Three-dimensional hydraulic conductivity upscaling in groundwater modelling. Computers & Geosciences 36 (10), 1224–1235. Zhou, H., Li, L., Hendricks Franssen, H., Gómez-Hernández, J. J., 2011b. Pattern recongition in a bimodal aquifer with normal-score Ensemble Kalman Filter. Mathematical Geosciences, under review. Zimmerman, D., De Marsily, G., Gotway, C., Marietta, M., Axness, C., Beauheim, R., Bras, R., Carrera, J., Dagan, G., Davies, P., et al., 1998. A comparison of seven geostatistically based inverse approaches to estimate transmissivities for modeling advective transport by groundwater flow. Water Resources Research 34 (6), 1373–1413.
Submitted to Hydrol. Earth Syst. Sci.. 6 Groundwater Flow Inverse Modeling in non-multiGaussian Media: Performance Assessment of the Normal-Score Ensemble Kalman Filter 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. 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 141
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Upscaling and Inverse Modeling of G
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c⃝ Copyright by Liangping Li 2011
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Abstract The need to reduce the com
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improved as more data is assimilate
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Resumen La necesidad de reducir el
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Por último, en el tercer bloque, e
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Resum La necessitat de reduir el co
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flux i el transport (conductivitat
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Acknowledgements I want to thank my
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xx CONTENTS 3 Transport Upscaling U
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xxii CONTENTS
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xxiv LIST OF FIGURES 2.7 Flow compa
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xxvi LIST OF FIGURES 4.4 Reference
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xxviii LIST OF FIGURES
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1.1 Motivation and Objectives 1 Int
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CHAPTER 1. INTRODUCTION 3 Chapter 2
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6 CHAPTER 2. A COMPARATIVE STUDY OF
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10 CHAPTER 2. A COMPARATIVE STUDY O
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38 BIBLIOGRAPHY Berkowitz, B., Sche
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40 BIBLIOGRAPHY Gómez-Hernández,
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42 BIBLIOGRAPHY Salamon, P., Fernà
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44 CHAPTER 3. TRANSPORT UPSCALING U
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70 BIBLIOGRAPHY Dagan, G., 1994. Up
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72 BIBLIOGRAPHY Lawrence, A. E., Sa
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74 BIBLIOGRAPHY Zhang, Y., 2004. Up
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76 CHAPTER 4. MODELING TRANSIENT GR
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