Applying micro-genetic algorithm in the one-dimensional unsteady hydraulic model for parameter optimization

Tsun-Hua Yang*, Yu Chi Wang, Shun Chung Tsung, Wen Dar Guo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Selection of an appropriate value for Manning's roughness coefficient could significantly impact the accuracy of a hydraulic model. However, it is highly variable and depends on flow circumstances, such as water stage and flow quantity; a stream's geomorphology, such as the fluvial process and river meandering; and physical conditions, such as the channel surface roughness and irregularities. Nevertheless, choosing proper roughness coefficients is not easy, especially with limited information and time in a practical application. Even it is done for a specific event it may not apply to another event due to its time- and site-dependency. This study proposes a Visual Basic (VB)-based system, which integrates the HEC-RAS modeling tool and the ?GA to efficiently search for Manning's roughness coefficients. The matching coefficients will thereafter improve the accuracy of hydraulic modeling. Two events in the Yilan River Basin were applied to test the feasibility of the system and four evaluation criteria were used to evaluate the system performance. The results showed that ?GA efficiently converged and the hydraulic model showed good agreement in comparison with the measured data. The system can be used as a good tool for finding onsite Manning's roughness coefficients in hydraulic modeling when detailed information is not available.

Original languageEnglish
Pages (from-to)772-783
Number of pages12
JournalJournal of Hydroinformatics
Issue number4
StatePublished - 1 Jan 2014


  • Manning's roughness coefficient
  • Micro-genetic algorithm
  • Parameter Optimization

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