Assimilating transient groundwater flow data via a localized ensemble Kalman filter to calibrate a heterogeneous conductivity field |
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Authors: | Juxiu Tong Bill X Hu Jinzhong Yang |
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Institution: | (1) Collage of Water Resources and Environmental Sciences, China University of Geosciences, Beijing, 100083, China;(2) Department of Earth, Ocean & Atmospheric Sciences, 108 Carraway Building, Florida State University, Tallahassee, FL 32306, USA;(3) State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China; |
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Abstract: | A localized ensemble Kalman filter (EnKF) method is developed to assimilate transient flow data to calibrate a heterogeneous
conductivity field. To update conductivity value at a point in a study domain, instead of assimilating all the measurements
in the study domain, only limited measurement data in an area around the point are used for the conductivity updating in the
localized EnKF method. The localized EnKF is proposed to solve the problems of the filter divergence usually existing in a
data assimilation method without localization. The developed method is applied, in a synthetical two dimensional case, to
calibrate a heterogeneous conductivity field by assimilating transient hydraulic head data. The simulations by the data assimilation
with and without localized EnKF are compared. The study results indicate that the hydraulic conductivity field can be updated
efficiently by the localized EnKF, while it cannot be by the EnKF. The covariance inflation and localization are found to
solve the problem of the filter divergence efficiently. In comparison with the EnKF method without localization, the localized
EnKF method needs smaller ensemble size to achieve stabilized results. The simulation results by the localized EnKF method
are much more sensitive to conductivity correlation length than to the localization radius. The developed localized EnKF method
provides an approach to improve EnKF method in conductivity calibration. |
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