An approach based on localizaed ensemble Kalman filter to identify groundwater dispersivity field
Cao Shaohua，Zeng Xiankui，Jiang Jianguo，Wu Jichun*
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Key Laboratory of Surficial Geochemistry，Ministry of Education，Department of Hydrosciences， School of Earth Science and Engineering，Nanjing University，Nanjing，210023，China
Solute transport simulation is significantly important to predict contaminant transport，however，the parameters used in the model are very difficult to obtain precisely.Ensemble Kalman Filter(EnKF)assimilates observation data from multiple sources to get parameters approach to the real values.In this paper，we assimilate solute transport data observed from a twodimensional confined aquifer with a covariance localized Ensemble Kalman Filter system to estimate the real dispersivity field.The effects of the number of realizations，statistical characteristic of initial assumed field，the number of observations，configuration of observations，and observation error on the efficiency of this method are investigated.Results indicate that a well estimated dispersivity field can be obtained by assimilating transport data with localized EnKF.The optimal number of realization is from 100 to 700 for the model we study，and excessive or insufficient number of realizations affect the accuracy of the assimilation results.A better estimation results can be obtained if initial assumed field is similar with the real logarithmic dispersivity field and the observation error is small.
Cao Shaohua，Zeng Xiankui，Jiang Jianguo，Wu Jichun*.
An approach based on localizaed ensemble Kalman filter to identify groundwater dispersivity field [J]. Journal of Nanjing University(Natural Sciences), 2016, 52(3): 429-437
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