Volume 4 Issue 1
Mar.  2011
Turn off MathJax
Article Contents
Xiao-meng SONG, Fan-zhe KONG, Zhao-xia ZHU. 2011: Application of Muskingum routing method with variable parameters in ungauged basin. Water Science and Engineering, 4(1): 1-12. doi: 10.3882/j.issn.1674-2370.2011.01.001
Citation: Xiao-meng SONG, Fan-zhe KONG, Zhao-xia ZHU. 2011: Application of Muskingum routing method with variable parameters in ungauged basin. Water Science and Engineering, 4(1): 1-12. doi: 10.3882/j.issn.1674-2370.2011.01.001

Application of Muskingum routing method with variable parameters in ungauged basin

doi: 10.3882/j.issn.1674-2370.2011.01.001
Funds:  This work was supported by the Technological Fund Item of China University of Mining and Technology (Grant No. OF4533) and the Key Research Project of the Water Resources Department of Henan Province.
More Information
  • Corresponding author: Xiao-meng SONG
  • Received Date: 2010-06-30
  • Rev Recd Date: 2010-09-12
  • This paper describes a flood routing method applied in an ungauged basin, utilizing the Muskingum model with variable parameters of wave travel time K and weight coefficient of discharge x based on the physical characteristics of the river reach and flood, including the reach slope, length, width, and flood discharge. Three formulas for estimating parameters of wide rectangular, triangular, and parabolic cross sections are proposed. The influence of the flood on channel flow routing parameters is taken into account. The HEC-HMS hydrological model and the geospatial hydrologic analysis module HEC-GeoHMS were used to extract channel or watershed characteristics and to divide sub-basins. In addition, the initial and constant-rate method, user synthetic unit hydrograph method, and exponential recession method were used to estimate runoff volumes, the direct runoff hydrograph, and the baseflow hydrograph, respectively. The Muskingum model with variable parameters was then applied in the Louzigou Basin in Henan Province of China, and of the results, the percentages of flood events with a relative error of peak discharge less than 20% and runoff volume less than 10% are both 100%. They also show that the percentages of flood events with coefficients of determination greater than 0.8 are 83.33%, 91.67%, and 87.5%, respectively, for rectangular, triangular, and parabolic cross sections in 24 flood events. Therefore, this method is applicable to ungauged basins.   

     

  • loading
  • Al-Humoud, J. M., and Esen, I. I. 2006. Approximate methods for the estimation of the Muskingum flood routing parameters. Water Resources Management, 20(6), 979-990. [doi: 10.1007/s11269-006-9018-2]
    Bao, W. M. 2006. Hydrologic Forecasting. 3rd ed. Beijing: China Water Conservancy and Water Power Press. (in Chinese)
    Chen, J. J., and Yang, X. H. 2007. Optimal parameter estimation for Muskingum model based on Gray-encoded accelerating genetic algorithm. Communications in Nonlinear Science and Numerical Simulation, 12(5), 849-858. [doi: 10.1016/j.cnsns.2005.06.005]
    Choudhury, P., Shrivastava, R. K., and Narulkar, S. M. 2002. Flood routing in river networks using equivalent Muskingum inflow. Journal of Hydrologic Engineering, 7(6), 413-419. [doi:10.1061/(ASCE)1084-0699 (2002)7:6(413)]
    Chu, H. J., and Chang, L. C. 2009. Applying particle swarm optimization to parameter estimation of the nonlinear Muskingum model. Journal of Hydrologic Engineering, 14(9), 1024-1027. [doi:10.1061/ (ASCE)HE.1943-5584.0000070]
    Cunge, J. A. 1969. On the subject of a flood propagation computational method (Muskingum method). Journal of Hydraulic Research, 7(2), 205-230. [doi: 10.1080/00221686909500264]
    Das, A. 2004. Parameter estimation for Muskingum models. Journal of Irrigation and Drainage Engineering, 130(2), 140-147. [doi: 10.1061/(ASCE)0733-9437(2004)130:2(140)]
    Das, A. 2007. Chance-constrained optimization-based parameter estimation for Muskingum models. Journal of Irrigation and Drainage Engineering, 133(5), 487-494. [doi:10.1061/(ASCE)0733-9437(2007)133:5 (487)]
    Fread, D. L. 1983. A “Unified” Coefficient Routing Model. Silver Spring: Hydrologic Research Laboratory.
    Geem, Z. W. 2006. Parameter estimation for the nonlinear Muskingum model using the BFGS technique. Journal of Irrigation and Drainage Engineering, 132(5), 474-478. [doi:10.1061/(ASCE)0733-9437(2006) 132:5(474)]
    Haktanir, T., and Ozmen, H. 1997. Comparison of hydraulic and hydrologic routing on three long reservoirs. Journal of Hydraulic Engineering, 123(2), 153-156. [doi: 10.1061/(ASCE)0733-9429(1997)123:2(153)]
    Hashmi, D. 1993. Flow Routing Model for Upper Indus River (Pakistan). Ph. D. Dissertation. Vancouver: The University of British Columbia.
    Kim, J. H., Geem, Z. W., and Kim, E. S. 2001. Parameter estimation of the nonlinear Muskingum model using harmony search. Journal of the American Water Resources Association, 37(5), 1131-1138. [doi:10.1111/ j.1752-1688.2001.tb03627.x]
    Kong, F. Z., Li, Y., and Zhu, C. X. 2007. A method deriving unit hydrographs based on area-time relationship. Journal of China University of Mining and Technology, 36(3), 356-359. (in Chinese)
    Kong, F. Z., and Wang, X. Z. 2008. Method estimating Muskingum model parameters based on physical characteristics of a river reach. Journal of China University of Mining and Technology, 37(4), 494-497. (in Chinese)
    Kshirsagar, M. M., Rajagopalan, B., and Lal, U. 1995. Optimal parameter estimation for Muskingum routing with ungauged lateral inflow. Journal of Hydrology, 169(1-4), 25-35. [doi:10.1016/0022-1694(94) 02670-7]
    Kundzewicz, Z. W., and Strupczewski, W. G. 1982. Approximate translation in the Muskingum model. Hydrological Sciences Journal, 27(1), 19-27. [doi: 10.1080/02626668209491082]
    Li, M., Shao, Q., Zhang, L., and Chiew, F. H. S. 2010. A new regionalization approach and its application to predict flow duration curve in ungauged basins. Journal of Hydrology, 389(1-2), 137-145. [doi:10.1016/j.jhydrol. 2010.05.039]
    Li, Y. 2008. Application Research of Distributed Hydrological Model in Ungaged Basins. M. E. Dissertation. Xuzhou: China University of Mining and Technology. (in Chinese)
    Lin, S. Y. 2001. Hydrological Forecasting. Beijing: China Water Conservancy and Water Power Press. (in Chinese)
    Lu, F., Jiang, Y. Z., Wang, H., and Niu, C. W. 2008. Application of multi-agent genetic algorithm to parameter estimation of Muskingum model. Journal of Hydraulic Engineering, 39(3), 289-294. (in Chinese)
    Luo, J. G., and Xie, J. C. 2010. Parameter estimation for nonlinear Muskingum model based on immune clonal selection algorithm. Journal of Hydrologic Engineering, 15(10), 844-851. [doi:10.1061/(ASCE) HE.1943-5584.0000244]
    McCarthy, G. T. 1938. The Unit Hydrograph and Flood Routing. Providence: U.S. Army Corps of Engineers.
    Oleyiblo, J. O., and Li, Z. J. 2010. Application of HEC-HMS for flood forecasting in Misai and Wan’an catchments in China. Water Science and Engineering, 3(1), 14-22. [doi:10.3882/j.issn.1674-2370. 2010.01.002]
    Rui, X. F., Liu, F. G., and Yu, M. 2008. Discussion of Muskingum method parameter X. Water Science and Engineering, 1(3), 16-23. [doi: 10.3882/j.issn.1674-2370.2008.03.002]
    Sivapalan, M., Takeuchi, K., Franks, S. W., Gupta, V. K., Karambiri, H., Lakshmi, V., Liang, X., McDonnell, J. J., Mendiondo, E. M., O’Connell, P. E., et al. 2003. IAHS decade on predictions in ungauged basins (PUB), 2003-2012: Shaping an exciting future for the hydrological sciences. Hydrological Sciences Journal, 48(6), 857-880. [doi: 10.1623/hysj.48.6.857.51421]
    Tewolde, M. H., and Smithers, J. C. 2006. Flood routing in ungauged catchments using Muskingum methods. Water SA, 32(3), 379-388.
    Todini, E. 2007. A mass conservative and water storage consistent variable parameter Muskingum-Cunge approach. Hydrology and Earth System Sciences Discussions, 11(4), 1549-1592. [doi:10.5194/hessd-4- 1549-2007]
    Wilson, B. N., and Ruffini, J. R. 1988. Comparison of physically-based Muskingum methods. Transactions of the American Society of Agricultural Engineers, 31(1), 91-97.
    Yadav, M., Wagener, T., and Gupta, H. 2007. Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins. Advances in Water Resources, 30(8), 1756-1774. [doi: 10.1016/j.advwatres.2007.01.005]
    Yang, X. H., and Li, J. Q. 2008. Chaos high efficient genetic algorithm for parameter optimization of Muskingum routing model. Journal of Hydroelectric Engineering, 27(2), 40-44. (in Chinese)
    Yoon, J., and Padmanabhan, G. 1993. Parameter estimation of linear and nonlinear Muskingum models. Journal of Water Resources Planning and Management, 119(5), 600-610. [doi:10.1061/(ASCE)0733- 9496(1993) 119:5(600)]
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (3624) PDF downloads(6937) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return