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Unrealistic parameter estimates in inverse modelling: A problem or a benefit for model calibration?

IAHS-AISH Publication

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Abstract

Estimation of unrealistic parameter values by inverse modelling is useful for constructed model discrimination. This utility is demonstrated using the three-dimensional, groundwater flow inverse model MODFLOWP to estimate parameters in a simple synthetic model where the true conditions and character of the errors are completely known. When a poorly constructed model is used, unreasonable parameter values are obtained even when using error free observations and true initial parameter values. This apparent problem is actually a benefit because it differentiates accurately and inaccurately constructed models. The problems seem obvious for a synthetic problem in which the truth is known, but are obscure when working with field data. Situations in which unrealistic parameter estimates indicate constructed model problems are illustrated in applications of inverse modelling to three field sites and to complex synthetic test cases in which it is shown that prediction accuracy also suffers when constructed models are inaccurate.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Unrealistic parameter estimates in inverse modelling: A problem or a benefit for model calibration?
Series title:
IAHS-AISH Publication
Volume
237
Year Published:
1996
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
IAHS-AISH Publication
First page:
277
Last page:
285
Number of Pages:
9