The cost of uniqueness in groundwater model calibration

By Catherine R. Moore, John Doherty. 2006

177 citations recorded by the source corpus.

Subfields: Environmental Engineering, Geophysics

View Paper: https://www.semanticscholar.org/paper/c1bee395e63c80b3df294dde1ea808635b1a48be

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In Environmental Engineering

In Geophysics

Citations in the corpus

Inverse methods in hydrogeology: Evolution and recent trends (2014, background): “Note that, Moore and359 Doherty (2005) and Moore and Doherty (2006) show that the regularized inversion method produces fields360 relatively smoother or simpler than the true conductivity field.”
Sensitivity analysis and parameter estimation for distributed hydrological modeling: potential of variational methods (2009, unknown): “As advocated byMoore and Doherty(2006a,b), empirical dimension reduction do not allow all the information to be extracted from observation data in order to reduce the predictive model error. Parameters at different locations over the surface of the catchment are not equally constrained by the observ”
Efficient nonlinear predictive error variance for highly parameterized models (2006, methodology): “However, simplification is undertaken formally and can be as little as necessary to solve the inverse problem uniquely [Moore and Doherty, 2006].”
Predictive uncertainty analysis of a saltwater intrusion model using null‐space Monte Carlo (2011, background): “Note that further examples of the high level of uncertainty that can accompany predictions made by a “well‐calibrated model” are provided by Moore and Doherty [2005, 2006] .”
Optimization and uncertainty assessment of strongly nonlinear groundwater models with high parameter dimensionality (2010, unknown): “... in the process is model calibration, this yielding (if implemented correctly) something approaching a minimum error variance estimate ^ of the possible set of parameters g. Of necessity, this will be a simplified and smoothed parameter set, exhibiting only as much heterogeneity as can be support”
One decade of multi-objective calibration approaches in hydrological modelling: a review (2010, methodology): “While such approaches are widely used to obtain a unique solution to the inverse problem, an oversimplified parameterization dramatically reduces the model accuracy at local scales (Moore & Doherty, 2006 ; see also discussion by Hunt et al.”
A generalized grid connectivity–based parameterization for subsurface flow model calibration (2011, methodology): “Multiple solutions consistent with geologic data and interpretation may reproduce the observed flow data but fail to predict future performance correctly [Gavalas et al., 1976; Yeh, 1986; Moore and Doherty, 2005; Oliver et al., 2008].”