Real‐time groundwater flow modeling with the Ensemble Kalman Filter: Joint estimation of states and parameters and the filter inbreeding problem

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Best unbiased ensemble linearization and the quasi‐linear Kalman ensemble generator (2009, methodology): “Typical numbers for ensemble-based methods range about 500 [e.g., Chen and Zhang, 2006; Hendricks Franssen and Kinzelbach, 2008b].”
Inverse methods in hydrogeology: Evolution and recent trends (2014, methodology): “Computers & Geosciences.949 Hendricks Franssen, H., Brunner, P., Makobo, P., Kinzelbach, W., 2008.”
A comparison of seven methods for the inverse modelling of groundwater flow. Application to the characterisation of well catchments (2009, background): “[97] and was started to be applied to groundwater problems in 2006 [32,44,68,90].”
Physically based modeling in catchment hydrology at 50: Survey and outlook (2015, methodology): “The ensemble framework used in these assimilation methods to compute the statistical quantities of interest allows EnKF and particle filters to be applied not only for updating model states but also for uncertainty estimation, model performance diagnostics, parameter estimation, and sensor failure a”