Skip to main content
SpringerLink
Log in

Parameter Identification for Modeling River Network Using a Genetic Algorithm

  • Published:
Journal of Hydrodynamics Aims and scope Submit manuscript

Abstract

The simulation of a one-dimensional river network needs to solve the Saint-Venant equations, in which the variable parameters normally have a significant influence on the model accuracy. A Trial-and-Error approach is a most commonly adopted method of parameter calibration, however, this method is time-consuming and requires experience to select the appropriate values of parameter. Consequently, simulated results obtained via this method usually differ between practitioners. This article combines a hydrodynamic model with an intelligent model originated from the Genetic Algorithm (GA) technique, in order to provide an intelligent simulation method that can optimize the parameters automatically. Compared with current approaches, the method presented in this article is simpler, its dependence on field data is lower, and the model accuracy is higher. When the optimized parameters are taken into the hydrodynamic numerical model, a good agreement is attained between the simulated results and the field data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. NGUYEN Q. K., KAWANO H. Simultaneous solution for flood routing in channel networks[J]. Journal of Hydraulic Engineering, 1995, 121(10): 744–750.

    Article  Google Scholar 

  2. SEN D. J., GARG N. K. Efficient solution technique for dendritic channel networks using FEM[J]. Journal of Hydraulic Engineering, 1998, 124(8): 831–839.

    Article  Google Scholar 

  3. LI Yue-sheng, YANG Shi-xiao and XIAO Zhi-liang. Sparse matrix method for solving implicit scheme system of equations of waterway network unsteady flow[J]. Journal of Zhongshan University (Natural Sciences), 1977, (3): 27–37 (in Chinese).

    Google Scholar 

  4. DRONKERS J. J. Tidal computations of rivers, coastal areas and seas[J]. Journal of Hydraulic Division, ASCE, 1969, 95(1): 29–77.

    Google Scholar 

  5. ZHANG Er-jun, ZHANG Dong-sheng and LI Ting. 3-step method for river net unsteady flows[J]. Journal of East China Institute of Water Conservancy, 1982, (1): 1–13 (in Chinese).

    Google Scholar 

  6. WU Shou-hong. 4-step method for river net unsteady flow[J]. Journal of Hydraulic Engineering, 1985, (8): 42–50 (in Chinese).

    Google Scholar 

  7. LI Yi-tian. A junctions group method for unsteady flow in multiply connected networks[J]. Journal of Hydraulic Engineering, 1997, (3): 49–57 (in Chinese).

    Google Scholar 

  8. LI Y. S., PANG Yong. Hydrodynamic model for river network in Pearl River Delta[J]. Journal of Hydrodynamics, Ser. A, 2001, 16(2): 143–155 (in Chinese).

    Google Scholar 

  9. ZHANG Wei, HUO Guang and ZHU Yu-liang. Prediction model for suspended-sediment transport in unsteady flow in Pearl network[J]. Journal of Hohai University (Natural Sciences), 2005, 33(5): 542–545 (in Chinese).

    Google Scholar 

  10. ZHOU Yi-lin, TANG Hong-wu and LIU Xiao-hua. A split-characteristic finite element model for 1-D unsteady flows[J]. Journal of Hydrodynamics, Ser. B, 2007, 19(1): 54–61.

    Article  Google Scholar 

  11. YANG Fang-li, ZHANG Xiao-feng and TAN Guang-ming. One- and two-dimensional coupled hydro-dynamics model for dam break flow[J]. Journal of Hydrodynamics, Ser. B, 2007, 19(6): 769–775.

    Article  Google Scholar 

  12. FREAD D. L., SMITH G. F. Calibration techniques for 1-D unsteady flow models[J]. Journal of Hydraulic Egineering, ASCE, 1978, 104(7): 1027–1043.

    Google Scholar 

  13. JIN Zhong-qing, HAN Long-xi and ZHANG Jian. The inverse problem of roughness parameter in hydraulic calculation of complicated river net work[J]. Journal of Hydrodynamics, Ser. A, 1998, 13(3): 280–285 (in Chinese).

    Google Scholar 

  14. HAN Long-xi, JIN Zhong-qing. Roughness calibration and formula of area pollution sources basing on three steps method in river network[J]. Journal of Hydraulic Engineering, 1998, (7): 30–34 (in Chinese).

    Google Scholar 

  15. BAO Wei-min, ZHANG Xiao-qin and QU Si-min. Dynamic correction of roughness in the hydrodynamic model[J]. Journal of Hydrodynamics, 2009, 21(2): 255–263.

    Article  Google Scholar 

  16. ATANOV G. A., EVSEEVA E. G. and MESELHE E. A. Estimation of roughness profile in trapezoidal open channel[J]. Journal of Hydraulic Engineering, ASCE, 1999, 125(3): 309–312.

    Article  Google Scholar 

  17. LI Guang-chi, ZHOU Jing-yan and ZHANG Gui-shou. Inverse analysis of river channel roughness parameter by use of Kalman filter[J]. Journal of Hohai University (Natural Sciences), 2003, 31(5): 490–493 (in Chinese).

    Google Scholar 

  18. WU Xiao-ling, WANG Chuan-hai and CHEN Xi et al. Kalman filtering correction in real time forecasting with hydrodynamic model[J]. Journal of Hdrodynamics, 2008, 20(3): 391–397.

    Article  Google Scholar 

  19. DING Y., JIA Y. and WANG S. S. Y. Identification of Manning’s roughness coefficient in shallow water flows[J]. Journal of Hydraulic Engineering, 2004, 130(6): 501–510.

    Article  Google Scholar 

  20. CHENG Wei-ping, LIU Guo-hua. Inverse analysis of channel friction based on generalized inverse theory[J]. Journal of Zhejiang University(Engineering Science), 2005, 39(10): 1063–1068 (in Chinese).

    Google Scholar 

  21. LIU Zhi-xian. Inversion of roughness parameter of river network based on genetic algorithm[D]. Master Thesis, Hangzhou: Zhejiang University, 2008 (in Chinese).

    Google Scholar 

  22. LIN G. F., WANG C. M. A nonlinear rainfall-runoff model embedded with an automated calibration method-Part II: The automated calibration method[J]. Journal of Hydrology, 2007, 341(3–4): 196–206.

    Article  Google Scholar 

  23. LIU S. M., BUTLER D. and BARZIER R. et al. Using genetic algorithms to calibrate a water quality model[J]. Science of the Total Environment, 2007, 374(2): 260–272.

    Article  Google Scholar 

  24. LEI Yan, TANG Hong-wu and ZHOU Yi-lin et al. Application of genetic algorithm for back analysis of roughness parameters in river networks[J]. Journal of Hydrodynamics, Ser. A, 2008, 23(6): 612–617 (in Chinese).

    Google Scholar 

  25. ZHANG X. S., SRINIVASAN R. and BOSCH D. Calibration and uncertainty analysis of the SWAT model using genetic algorithms and Bayesian model averaging[J]. Journal of Hydology, 2009, 374(3–4): 307–317.

    Article  Google Scholar 

  26. MU Jing-bin, ZHANG Xiao-feng. Real time flood forecasting method with 1-D unsteady flow model[J]. Journal of Hydrodynamics, Ser. B, 2007, 19(2): 150–154.

    Article  MathSciNet  Google Scholar 

  27. ZHANG Ming-liang, SHEN Yong-ming. Study and application of steady flow and unsteady flow mathematical model for channel networks[J]. Journal of Hydrodynamics, Ser. B, 2007, 19(5): 572–578.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China

    Hong-wu Tang, Xiao-kang Xin, Wen-hong Dai & Yang Xiao

Authors
  1. Hong-wu Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiao-kang Xin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wen-hong Dai
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yang Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hong-wu Tang.

Additional information

Project supported by the National Natural Science Foundation of China (Grant Nos. 50879019, 50879020), the Key Science Project of Guangdong Traffic Department (Grant No. 2008-19).

Biography: TANG Hong-wu (1966-) Male, Ph. D., Professor

Rights and permissions

Reprints and permissions

About this article

Cite this article

Tang, Hw., Xin, Xk., Dai, Wh. et al. Parameter Identification for Modeling River Network Using a Genetic Algorithm. J Hydrodyn 22, 246–253 (2010). https://doi.org/10.1016/S1001-6058(09)60051-2

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1016/S1001-6058(09)60051-2

Key words

Search

Navigation