## Abstract The parameters of a constitutive model are usually identified by minimization of the distance between model response and experimental data. However, measurement failures and differences in the specimens lead to deviations in the determined parameters. In this article we present our resu
Parameter identification for conceptual modelling using combined behavioural knowledge
✍ Scribed by Sarah M. Dunn; Chris Soulsby; Allan Lilly
- Publisher
- John Wiley and Sons
- Year
- 2003
- Tongue
- English
- Weight
- 226 KB
- Volume
- 17
- Category
- Article
- ISSN
- 0885-6087
- DOI
- 10.1002/hyp.1127
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✦ Synopsis
Abstract
Improved methods for identification of conceptual parameter values are necessary if hydrological models are to be applied to catchments other than those to which they have been specifically calibrated. A technique has been devised to calculate conceptual parameter sets of a semi‐distributed hydrological model using a soil hydrological classification in addition to topographic data. The method is tested in this paper by converting multiple parameter sets, calibrated to two separate catchments, into parameter sets for a third catchment.
The prediction capabilities of the parameter sets are studied for the new catchment in terms of both simulation of total streamflow and the separation of that flow into three components, corresponding to groundwater recharge, sub‐surface flow, and surface runoff. The results from an end‐member mixing analysis (EMMA) using geochemical tracers are employed to assess the flow separation. Results from the simulations demonstrate that there is quite wide variability in the success of the parameter sets at predicting streamflow for the new catchment. There is also considerable variation in the predicted stream flow separation, with only 28 out of 500 simulations giving a comparable result to the EMMA. By accepting or rejecting simulations using these results, the EMMA can be used to reduce the structural uncertainty of the model. However, it does not help to reduce constraints on acceptable parameter values for the simulations, and further research is still necessary to improve parameter identifiability. Copyright © 2003 John Wiley & Sons, Ltd.
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