Articles | Volume 20, issue 1
https://doi.org/10.5194/hess-20-375-2016
https://doi.org/10.5194/hess-20-375-2016
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

Viewed

Total article views: 3,859 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,088 1,657 114 3,859 112 100
  • HTML: 2,088
  • PDF: 1,657
  • XML: 114
  • Total: 3,859
  • BibTeX: 112
  • EndNote: 100
Views and downloads (calculated since 16 Oct 2015)
Cumulative views and downloads (calculated since 16 Oct 2015)

Cited

Saved (preprint)

Latest update: 23 Nov 2024
Download
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.