Joint identification of contaminant source and aquifer geometry in a sandbox experiment with the restart ensemble Kalman filter

JOURNAL OF HYDROLOGY

卷:564

Article

Chen, Zi¹  Gomez-Hernandez, J. Jaime¹  Xu, Teng¹  Zanini, Andrea² 

[1] Univ Politecn Valencia, Inst Water & Environm Engn, Valencia, Spain

[2] Univ Parma, Dipartimento Ingn & Architettura, Parma, Italy

关键词: Inverse modeling;    Observation error;    Groundwater laboratory experiment;    Stochastic hydrogeology;   

DOI  :  10.1016/j.jhydrol.2018.07.073

来源: Elsevier

【 摘 要 】

Contaminant source identification is a key problem in handling groundwater pollution events. The ensemble Kalman filter (EnKF) is used for the spatiotemporal identification of a point contaminant source in a sandbox experiment, together with the identification of the position and length of a vertical plate inserted in the sandbox that modifies the geometry of the system. For the identification of the different parameters, observations in time of solute concentration are used, but not of piezometric head data since they were not available. A restart version of the EnKF is utilized because it is necessary to restart the forecast from time zero after each parameter update. The results show that the restart EnKF is capable of identifying both contaminant source information and aquifer-geometry-related parameters together with an uncertainty estimate of such identification.

【 授权许可】

Free