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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 20, issue 1
Hydrol. Earth Syst. Sci., 20, 375–392, 2016
https://doi.org/10.5194/hess-20-375-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Modeling hydrological processes and changes

Hydrol. Earth Syst. Sci., 20, 375–392, 2016
https://doi.org/10.5194/hess-20-375-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 21 Jan 2016

Research article | 21 Jan 2016

Improving flood forecasting capability of physically based distributed hydrological models by parameter optimization

Y. Chen et al.

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Cited articles

Abbott, M. B., Bathurst, J. C., Cunge, J. A., O'Connell, P. E., and Rasmussen, J.: An Introduction to the European Hydrologic System-System Hydrologue Europeen, `SHE', a: History and Philosophy of a Physically-based, Distributed Modelling System, J. Hydrol., 87, 45–59, 1986a.
Abbott, M. B.,Bathurst, J. C.,Cunge, J. A.,O'Connell, P. E., and Rasmussen, J.: An Introduction to the European Hydrologic System-System Hydrologue Europeen, `SHE', b: Structure of a Physically based, distributed modeling System, J. Hydrol., 87, 61–77, 1986b.
Acharjee, P. and Goswami, S. K.: Chaotic particle swarm optimization based robust load flow, Int. J. Electr. Power Energ. Syst., 32, 141–146, 2010.
Ajami, N. K., Gupta, H., Wagener, T., and Sorooshian, S.: Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system, J. Hydrol., 298, 112–135, 2004.
Ambroise, B., Beven, K., and Freer, J.: Toward a generalization of the TOPMODEL concepts: Topographic indices of hydrologic similarity, Water Resour. Res., 32, 2135–2145, 1996.
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Short summary
Parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. A method for parameter optimization with particle swam optimization (PSO) algorithm has been proposed for physically based distributed hydrological model in catchment flood forecasting and validated in southern China. It has found that the appropriate particle number and maximum evolution number of PSO algorithm are 20 and 30 respectively.
Parameter optimization is necessary to improve the flood forecasting capability of physically...
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