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Author |
Van Hoey, S.; Nopens, I.; van der Kwast, J.; Seuntjens, P. |
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Title |
Dynamic identifiability analysis-based model structure evaluation considering rating curve uncertainty |
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A1 Journal article |
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Year |
2015 |
Publication |
Journal of hydrologic engineering |
Abbreviated Journal |
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Volume ![sorted by Volume (numeric) field, ascending order (up)](img/sort_asc.gif) |
20 |
Issue |
5 |
Pages |
04014072 |
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Keywords |
A1 Journal article; Sustainable Energy, Air and Water Technology (DuEL) |
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Abstract |
When applying hydrological models, different sources of uncertainty are present, and evaluations of model performances should take these into account to assess model outcomes correctly. Furthermore, uncertainty in the discharge observations complicates the model identification, both in terms of model structure and parameterization. In this paper, the authors compare two different lumped model structures (PDM and NAM) considering uncertainty coming from the rating curve. Limits of acceptability for the model simulations were determined based on derived uncertainty bounds of the discharge observations. The authors applied the DYNamic Identifiability Approach (DYNIA) to identify structural failure of both models and to evaluate the configuration of their structures. In general, similar model performances are observed. However, the model structures tend to behave differently in the course of time, as revealed by the DYNIA approach. Based on the analyses performed, the probability based soil storage representation of the PDM model outperforms the NAM structure. The incorporation of the observation error did not prevent the DYNIA analysis to identify potential model structural deficiencies that are limiting the representation of the seasonal variation, primarily indicated by shifting regions of parameter identifiability. As such, the proposed approach is able to indicate where deficiencies are found and model improvement is needed. |
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000353995400002 |
Publication Date |
2014-03-06 |
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ISSN |
1084-0699 |
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UA library record; WoS full record; WoS citing articles |
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Call Number |
UA @ admin @ c:irua:126056 |
Serial |
7829 |
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Author |
Van Hoey, S.; Seuntjens, P.; van der Kwast, J.; Nopens, I. |
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Title |
A qualitative model structure sensitivity analysis method to support model selection |
Type |
A1 Journal article |
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Year |
2014 |
Publication |
Journal of hydrology |
Abbreviated Journal |
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Volume ![sorted by Volume (numeric) field, ascending order (up)](img/sort_asc.gif) |
519 |
Issue |
D |
Pages |
3426-3435 |
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Keywords |
A1 Journal article; Sustainable Energy, Air and Water Technology (DuEL) |
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Abstract |
The selection and identification of a suitable hydrological model structure is a more challenging task than fitting parameters of a fixed model structure to reproduce a measured hydrograph. The suitable model structure is highly dependent on various criteria, i.e. the modeling objective, the characteristics and the scale of the system under investigation and the available data. Flexible environments for model building are available, but need to be assisted by proper diagnostic tools for model structure selection. This paper introduces a qualitative method for model component sensitivity analysis. Traditionally, model sensitivity is evaluated for model parameters. In this paper, the concept is translated into an evaluation of model structure sensitivity. Similarly to the one-factor-at-a-time (OAT) methods for parameter sensitivity, this method varies the model structure components one at a time and evaluates the change in sensitivity towards the output variables. As such, the effect of model component variations can be evaluated towards different objective functions or output variables. The methodology is presented for a simple lumped hydrological model environment, introducing different possible model building variations. By comparing the effect of changes in model structure for different model objectives, model selection can be better evaluated. Based on the presented component sensitivity analysis of a case study, some suggestions with regard to model selection are formulated for the system under study: (1) a non-linear storage component is recommended, since it ensures more sensitive (identifiable) parameters for this component and less parameter interaction; (2) interflow is mainly important for the low flow criteria; (3) excess infiltration process is most influencing when focussing on the lower flows; (4) a more simple routing component is advisable; and (5) baseflow parameters have in general low sensitivity values, except for the low flow criteria. (C) 2014 Elsevier B.V. All rights reserved. |
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000347589600057 |
Publication Date |
2014-10-08 |
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ISSN |
0022-1694 |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Open Access |
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UA @ admin @ c:irua:123809 |
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7395 |
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