Joint estimation of states and parameters of two-layer coastal aquifers based on ENKF

Abstract

Management of groundwater resources has become a source of heated discussion in coastal hydrogeology. Thus, we introduced an Ensemble Kalman Filter (ENKF) into a two-layer confined groundwater model based on the interactive operation between the MATLAB and GMS to investigate the capability of ENKF under complex conditions and obtain a relatively new forecasting method. ENKF was employed to assimilate and forecast groundwater levels, and invert the hydraulic conductivity (K) of the heterogeneous study area, where the initial values of K were obtained by using trial-and-error based on the two-period groundwater levels. After comparing the efficiencies in forecasting groundwater levels among ENKF, the modified model, and the initial model, four major conclusions could be drawn. ENKF converged fast when forecasting groundwater levels and the accuracy was high. Various convergent results would be represented by ENKF when K in different layers was observed in the same error. ENKF performed better than the initial simulation when monitored data subjected to a certain range of interferences. Forecasting accuracy in the middle of the study area could be enhanced by the large improvement degree of K through ENKF. Therefore, this analytical method could be a theoretical reference for groundwater resources management in coastal areas. HIGHLIGHTS First employed ENKF into a two-layer confined coastal model.; Modified groundwater model by ENKF.; Provided the theoretical reference for groundwater resources management in coastal areas.;

Keywords

• coastal areas in tianjin
• data assimilation
• ensemble kalman filter (enkf)
• groundwater level forecasting
• hydraulic conductivity identification