Best unbiased ensemble linearization and the quasi‐linear Kalman ensemble generator

By Wolfgang Nowak. 2009

96 citations recorded by the source corpus.

Subfields: Environmental Engineering, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/f3b3ae38f55f093fb41d0dc6b4ee4721e2bae332

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In Environmental Engineering

In Water Science and Technology

Citations in the corpus

A hypothesis‐driven approach to optimize field campaigns (2012, unknown): “…quasilinear geostatistical approach [Kitanidis, 1995] and its upgrades [e.g., Nowak and Cirpka, 2004], ensemble Kalman filters [Zhang et al., 2005; Nowak, 2009], and biasaware modifications of it [e.g., Drécourt et al., 2006; Kollat et al., 2011], or other conditional Monte Carlo methods based…”
Bayesian assessment of the expected data impact on prediction confidence in optimal sampling design (2012, methodology): “The EnKF has recently been extended toward geostatistical inversion and parameter estimation [e.g., Zhang et al., 2005; Nowak, 2009; A. W. Schöniger, W. Nowak, and H.-J. Franssen, Parameter estimation by ensemble Kalman filters with transformed data: Approach and application to hydraulic…”
Bayesian geostatistical design: Task‐driven optimal site investigation when the geostatistical model is uncertain (2010, methodology): “Once the design is decided upon and the data become available, we condition the log conductivity field by the Kalman Ensemble Generator (KEG) [Nowak, 2009b], which is an adaptation of the EnKF to geostatistical inversion.”
Inverse methods in hydrogeology: Evolution and recent trends (2014, methodology): “The EnKF has been widely applied as a data 487 assimilation tool in diverse disciplines such as oceanography, meteorology and hydrology (e.g., Bertino et al., 488 2003; Chen and Zhang, 2006; Houtekamer and Mitchell, 2001; Moradkhani et al., 2005; Nowak, 2009; Wen 489 and Chen, 2006).”
A generalized grid connectivity–based parameterization for subsurface flow model calibration (2011, background): “…et al., 1992; LaVenue et al., 1995; RamaRao et al., 1995; Gomez‐Hernandez et al., 1997] or those that simultaneously update an ensemble of prior sample realizations to generate an ensemble of conditional realizations [e.g., Evensen, 1994; Chen and Zhang, 2006; Wen and Chen, 2006; Nowak, 2009].”
Global sensitivity analysis: a flexible and efficient framework with an example from stochastic hydrogeology (2012, methodology): “These secants (polynomials) approximate the model over the entire parameter space in a weighted least-square sense (compare with the best unbiased ensemble linearization approach described by Nowak [37]).”