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

Chen, Y.; Li, J.; Xu, H.

doi:10.5194/hess-20-375-2016

Articles | Volume 20, issue 1

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

https://doi.org/10.5194/hess-20-375-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 20, issue 1

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, J. Li, and H. Xu

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Month	HTML	PDF	XML	Total
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Oct 2025	46	33	2	81
Nov 2025	10	9	1	20

Latest update: 08 Nov 2025

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.