The main aim of the study was to introduce new filtering techniques to better the prediction of subsurface water contaminant transport. Hybrid nudging-ensemble Kalman filter (HNEnKF) and ensemble adjustment Kalman filter were proposed in this study. EnKF with traditional nudging were gradually applied promptly in the case of the HNEnKF. Other techniques whose performance were evaluated along with HNEnKF are a numerical method, ensemble Kalman filter, and ensemble adjustment Kalman filter. In this study, the HNEnKF and the EAKF are expected to improve in robustness and convergence due to the nudging properties and the assimilation of observations with a nonlinear relation to model state variables respectively. To appraise the HNEnKF and EAKF techniques, the numerical (finite difference) method and EnKF assimilation method were used. These simulations were executed with a three-dimension subsurface contaminant transport model with a first-order decay rate parameter.
A summary of this research are outlined below:
• To investigate the performance of HNEnKF and EAKF data assimilation technique in subsurface water contaminant transport modeling compared to the numerical solution and ensemble Kalman filter technique.
• To apply HNEnKF and EAKF data assimilation scheme in subsurface water contaminant transport.
|Commitee:||Jha, Manoj K., Teasley, Stephanie Luster|
|School:||North Carolina Agricultural and Technical State University|
|School Location:||United States -- North Carolina|
|Source:||MAI 55/05M(E), Masters Abstracts International|
|Subjects:||Civil engineering, Environmental engineering|
|Keywords:||Ensemble adjustment kalman filter data assimilation, Ensemble kalman filter, Hybrid data assimilation, Numerical method, Subsurface water contaminant|
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