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A comparison of non-linear least square and GLUE for model calibration and uncertainty estimation for pesticide transport in soils

Zhang, Danrong and Beven, Keith and Mermoud, André (2006) A comparison of non-linear least square and GLUE for model calibration and uncertainty estimation for pesticide transport in soils. Advances in Water Resources, 29 (12). pp. 1924-1933.

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Abstract

The problems of calibrating soil hydraulic and transport parameters are well documented, particularly when data are limited. Programs such as CXTFIT, UUCODE and PEST, based on well established principles of statistical inference, will often provide good fits to limited observations giving the impression that a useful model of a particular soil system has been obtained. This may be the case, but such an approach may grossly underestimate the uncertainties associated with future predictions of the system and resulting dependent variables. In this paper, this is illustrated by an application of CXTFIT within the generalised likelihood uncertainty estimation (GLUE) approach to model calibration which is based on a quite different philosophy. CXTFIT gives very good fits to the observed breakthrough curves for several different model formulations, resulting in very small parameter uncertainty estimates. The application of GLUE, however, shows that much wider ranges of parameter values can provide acceptable fits to the data. The wider range of potential outcomes should be more robust in model prediction, especially when used to constrain field scale models.

Item Type: Article
Journal or Publication Title: Advances in Water Resources
Uncontrolled Keywords: CXTFIT ; GLUE ; Atrazine ; Bromide ; Tracer ; Dispersion ; Column scale ; Solute transport
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Departments: Faculty of Science and Technology > Lancaster Environment Centre
ID Code: 9263
Deposited By: Ms Margaret Calder
Deposited On: 02 Jun 2008 16:35
Refereed?: Yes
Published?: Published
Last Modified: 26 Jul 2012 18:34
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/9263

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