Fuzzy Committees of Conceptual Distributed Model

Book Chapter (2023)
Author(s)

Mostafa Farrag (University of Potsdam, Deltares, GFZ Helmholtz-Zentrum für Geoforschung)

Gerald A.Corzo Perez (IHE Delft Institute for Water Education)

Dimitri P. Solomatine (IHE Delft Institute for Water Education, Russian Academy of Sciences, TU Delft - Water Resources)

Research Group
Water Resources
DOI related publication
https://doi.org/10.1002/9781119639268.ch4
More Info
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Publication Year
2023
Language
English
Research Group
Water Resources
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. @en
Pages (from-to)
99-127
Publisher
Wiley
ISBN (print)
9781119639312
ISBN (electronic)
9781119639268
Reuse Rights

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Abstract

Conceptual hydrological models imply a simplification of the complexity of the hydrological system; however, they lack the flexibility in reproducing a wide range of the catchment responses. Usually, a trade-off is done to sacrifice the accuracy of a specific aspect of the system behavior in favor of the accuracy of other aspects. This study evaluates the benefit of using a modular approach, “The fuzzy committee model” of building specialized models to reproduce specific responses of the catchment. We also assess the applicability of using predicted runoff from specialized models to form a fuzzy committee model. In this paper, weighting schemes with power parameter values are investigated. A thorough study is conducted on the relation between the fuzzy committee variables (the membership functions and the weighting schemes), and their effect on the model performance. Furthermore, the Fuzzy committee concept is applied on a conceptual distributed model with two cases, the first with lumped catchment parameters and the latter with distributed parameters. A comparison between different combinations of the fuzzy committee variables showed the superiority of all Fuzzy Committee models over single models. Fuzzy committee of distributed models performed well, especially in capturing the highest peak in the calibration data set; however, it needs further study of the effect of model parameterization on the model performance and uncertainty.

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