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Characterizing curvilinear features using the localized normal-score ensemble Kalman filter

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Characterizing curvilinear features using the localized normal-score ensemble Kalman filter

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Zhou ., H.; Li ., L.; Gómez-Hernández, JJ. (2012). Characterizing curvilinear features using the localized normal-score ensemble Kalman filter. Abstract and Applied Analysis. 2012:1-18. https://doi.org/10.1155/2012/805707

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/28857

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Título: Characterizing curvilinear features using the localized normal-score ensemble Kalman filter
Autor: Zhou ., Haiyan Li ., Liangping Gómez-Hernández, J. Jaime
Entidad UPV: Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient
Fecha difusión:
Resumen:
The localized normal-score ensemble Kalman filter is shown to work for the characterization of non-multi-Gaussian distributed hydraulic conductivities by assimilating state observation data. The influence of type of flow ...[+]
Palabras clave: sequential data assimilation , flow , parameters , transient
Derechos de uso: Reconocimiento (by)
Fuente:
Abstract and Applied Analysis. (issn: 1085-3375 )
DOI: 10.1155/2012/805707
Editorial:
Hindawi Publishing Corporation
Versión del editor: http://dx.doi.org/10.1155/2012/805707
Código del Proyecto:
info:eu-repo/grantAgreement/MICINN//CGL2011-23295/ES/MODELACION ESTOCASTICA INVERSA FUERA DE LO NORMAL/
Agradecimientos:
The authors gratefully acknowledge the financial support by the Spanish Ministry of Science and Innovation through project CGL2011-23295. The authors want to thank the reviewer for the comments which help improving the ...[+]
Tipo: Artículo

References

Houtekamer, P. L., & Mitchell, H. L. (2001). A Sequential Ensemble Kalman Filter for Atmospheric Data Assimilation. Monthly Weather Review, 129(1), 123-137. doi:10.1175/1520-0493(2001)129<0123:asekff>2.0.co;2

Naevdal, G., Johnsen, L. M., Aanonsen, S. I., & Vefring, E. H. (2005). Reservoir Monitoring and Continuous Model Updating Using Ensemble Kalman Filter. SPE Journal, 10(01), 66-74. doi:10.2118/84372-pa

Chen, Y., & Zhang, D. (2006). Data assimilation for transient flow in geologic formations via ensemble Kalman filter. Advances in Water Resources, 29(8), 1107-1122. doi:10.1016/j.advwatres.2005.09.007 [+]
Houtekamer, P. L., & Mitchell, H. L. (2001). A Sequential Ensemble Kalman Filter for Atmospheric Data Assimilation. Monthly Weather Review, 129(1), 123-137. doi:10.1175/1520-0493(2001)129<0123:asekff>2.0.co;2

Naevdal, G., Johnsen, L. M., Aanonsen, S. I., & Vefring, E. H. (2005). Reservoir Monitoring and Continuous Model Updating Using Ensemble Kalman Filter. SPE Journal, 10(01), 66-74. doi:10.2118/84372-pa

Chen, Y., & Zhang, D. (2006). Data assimilation for transient flow in geologic formations via ensemble Kalman filter. Advances in Water Resources, 29(8), 1107-1122. doi:10.1016/j.advwatres.2005.09.007

Li, L., Zhou, H., Hendricks Franssen, H.-J., & Gómez-Hernández, J. J. (2012). Modeling transient groundwater flow by coupling ensemble Kalman filtering and upscaling. Water Resources Research, 48(1). doi:10.1029/2010wr010214

Franssen, H. J. H., & Kinzelbach, W. (2009). Ensemble Kalman filtering versus sequential self-calibration for inverse modelling of dynamic groundwater flow systems. Journal of Hydrology, 365(3-4), 261-274. doi:10.1016/j.jhydrol.2008.11.033

Arulampalam, M. S., Maskell, S., Gordon, N., & Clapp, T. (2002). A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Transactions on Signal Processing, 50(2), 174-188. doi:10.1109/78.978374

Evensen, G., & van Leeuwen, P. J. (2000). An Ensemble Kalman Smoother for Nonlinear Dynamics. Monthly Weather Review, 128(6), 1852-1867. doi:10.1175/1520-0493(2000)128<1852:aeksfn>2.0.co;2

Zhou, H., Gómez-Hernández, J. J., Hendricks Franssen, H.-J., & Li, L. (2011). An approach to handling non-Gaussianity of parameters and state variables in ensemble Kalman filtering. Advances in Water Resources, 34(7), 844-864. doi:10.1016/j.advwatres.2011.04.014

Li, L., Zhou, H., Hendricks Franssen, H. J., & Gómez-Hernández, J. J. (2011). Groundwater flow inverse modeling in non-MultiGaussian media: performance assessment of the normal-score Ensemble Kalman Filter. Hydrology and Earth System Sciences Discussions, 8(4), 6749-6788. doi:10.5194/hessd-8-6749-2011

Zhou, H., Li, L., Hendricks Franssen, H.-J., & Gómez-Hernández, J. J. (2011). Pattern Recognition in a Bimodal Aquifer Using the Normal-Score Ensemble Kalman Filter. Mathematical Geosciences, 44(2), 169-185. doi:10.1007/s11004-011-9372-3

Burgers, G., Jan van Leeuwen, P., & Evensen, G. (1998). Analysis Scheme in the Ensemble Kalman Filter. Monthly Weather Review, 126(6), 1719-1724. doi:10.1175/1520-0493(1998)126<1719:asitek>2.0.co;2

Evensen, G. (2009). Data Assimilation. doi:10.1007/978-3-642-03711-5

Chen, Y., & Oliver, D. S. (2009). Cross-covariances and localization for EnKF in multiphase flow data assimilation. Computational Geosciences, 14(4), 579-601. doi:10.1007/s10596-009-9174-6

Gaspari, G., & Cohn, S. E. (1999). Construction of correlation functions in two and three dimensions. Quarterly Journal of the Royal Meteorological Society, 125(554), 723-757. doi:10.1002/qj.49712555417

Hamill, T. M., Whitaker, J. S., & Snyder, C. (2001). Distance-Dependent Filtering of Background Error Covariance Estimates in an Ensemble Kalman Filter. Monthly Weather Review, 129(11), 2776-2790. doi:10.1175/1520-0493(2001)129<2776:ddfobe>2.0.co;2

Carrera, J., & Neuman, S. P. (1986). Estimation of Aquifer Parameters Under Transient and Steady State Conditions: 2. Uniqueness, Stability, and Solution Algorithms. Water Resources Research, 22(2), 211-227. doi:10.1029/wr022i002p00211

Delhomme, J. P. (1979). Spatial variability and uncertainty in groundwater flow parameters: A geostatistical approach. Water Resources Research, 15(2), 269-280. doi:10.1029/wr015i002p00269

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