Water Science and Engineering 2012, 5(3) 243-258 DOI:   10.3882/j.issn.1674-2370.2012.03.001  ISSN: 1674-2370 CN: 32-1785/TV

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open channel flow
flood wave
dynamic wave model
flood routing
numerical experiments
sensitivity analysis
REZA -Barati
SAJJAD -Rahimi
Article by Reza,.B
Article by Sajjad,.R
Article by Gholam Hossein,.A

Analysis of dynamic wave model for flood routing in natural rivers

Reza BARATI*1, Sajjad RAHIMI2, Gholam Hossein AKBARI3

1. Faculty of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran
2. Social Development and Health Promotion Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
3. Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran


 Flooding is a common natural disaster that causes enormous economic, social, and human losses. Of various flood routing methods, the dynamic wave model is one of the best approaches for the prediction of the characteristics of floods during their propagations in natural rivers because all of the terms of the momentum equation are considered in the model. However, no significant research has been conducted on how the model sensitivity affects the accuracy of the downstream hydrograph. In this study, a comprehensive analysis of the input parameters of the dynamic wave model was performed through field applications in natural rivers and routing experiments in artificial channels using the graphical multi-parametric sensitivity analysis (GMPSA). The results indicate that the effects of input parameter errors on the output results are more significant in special situations, such as lower values of Manning’s roughness coefficient and/or a steeper bed slope on the characteristics of a design hydrograph, larger values of the skewness factor and/or time to peak on the channel characteristics, larger values of Manning’s roughness coefficient and/or the bed slope on the space step, and lower values of Manning’s roughness coefficient and/or a steeper bed slope on the time step and weighting factor.

Keywords open channel flow   flood wave   dynamic wave model   flood routing   numerical experiments   sensitivity analysis  
Received 2012-04-16 Revised 2012-07-08 Online: 2012-09-25 
DOI: 10.3882/j.issn.1674-2370.2012.03.001
Corresponding Authors: Reza BARATI
Email: r88barati@gmail.com; reza.barati@modares.ac.ir
About author:

Akan, A. O. 2006. Open Channel Hydraulics. Oxford: Elsevier.
Akbari, G. H., and Barati, R. 2012. Comprehensive analysis of flooding in unmanaged catchments. Proceedings of the Institution of Civil Engineers-Water Management, 165(4), 229-238. [doi:10.1680/ wama.10.00036]
Akbari, G. H., Nezhad, A. H., and Barati, R. 2012. Developing a model for analysis of uncertainties in prediction of floods. Journal of Advanced Research, 3(1), 73-79. [doi:10.1016/j.jare.2011.04.004]
American Society of Civil Engineers (ASCE). 2008. Comments of the American Society of Civil Engineers on the Proposed Revisions to the Economic and Environmental Principles and Guidelines for Water and Related Land Resources Implementation Studies. Washington, D.C.: ASCE.
Anderson, B. G., Rutherfurd, I. D., and Western, A. W. 2006. An analysis of the influence of riparian vegetation on the propagation of flood waves. Environmental Modelling and Software, 21(9), 1290-1296. [doi:10.1016/j.envsoft.2005.04.027]
Barati, R. 2010. Investigation of Flood Routing Methods in Natural Waterways. M. S. Dissertation. Zahedan: University of Sistan and Baluchestan.
Barati, R. 2011a. Discussion of “Parameter Estimation for Nonlinear Muskingum Model based on Immune Clonal Algorithm”. Journal of Hydrologic Engineering, 16(4), 391-393. [doi:10.1061/(ASCE)HE.1943- 5584.0000311]
Barati, R. 2011b. Parameter estimation of nonlinear Muskingum models using Nelder-Mead Simplex algorithm. Journal of Hydrologic Engineering, 16(11), 946-954. [doi:10.1061/(ASCE)HE.1943-5584. 0000379]
Bhunya, P. K., Panda, S. N., and Goel, M. K. 2011. Synthetic unit hydrograph methods: A critical review. The Open Hydrology Journal, 5, 1-8.
Chaudhry, M. H. 1993. Open-Channel Flow. Englewood Cliffs: Prentice Hall.
Chow, V. T., Maidment, D. R., and Mays, L. W. 1988. Applied Hydrology. Singapore: McGraw-Hill Science.
Cunge, J. A., Holly, F. M., and Verwey, A. 1980. Practical Aspects of ComputationalRiver Hydraulics. London: Pitman Publishing Ltd.
Hassan, A., Norio, T., and Nobuyuki, T. 2009. Distributed water balance with river dynamic-diffusive flow routing model. Journal of Hydrodynamics, 21(4), 564-572. [doi:10.1016/S1001-6058(08)60185-7]
Helmiö, T. 2005. Unsteady 1D flow model of a river with partly vegetated floodplains: Application to the Rhine River. Environmental Modelling and Software, 20(3), 361-375. [doi:10.1016/j.envsoft. 2004.02.001]
Kim, J. S., Lee, C. J., Kim, W., and Kim, Y. J. 2010. Roughness coefficient and its uncertainty in gravel-bed river. Water Science and Engineering, 3(2), 217-232. [doi:10.3882/j.issn.1674-2370.2010.02.010]
Kuiry, S. N., Sen, D., and Bates, P. D. 2010. Coupled 1D-Quasi-2D flood inundation model with unstructured grids. Journal of Hydraulic Engineering, 136(8), 493-506. [doi:10.1061/(ASCE)HY.1943-7900.0000211]
McCuen, R. H. 2003. Modeling Hydrologic Change: Statistical Methods. Boca Raton: CRC Press.
McCuen, R. H., and Knight, Z. 2006. Fuzzy analysis of slope-area discharge estimates. Journal of Irrigation and Drainage Engineering, 132(1), 64-69. [doi:10.1061/(ASCE)0733-9437(2009)135:2(149)]
Moghaddam, M. A., and Firoozi, B. 2011. Development of dynamic flood wave routing in natural rivers through implicit numerical method. American Journal of Scientific Research, (14), 6-17.
Moramarco, T., Pandolfo, C., and Singh, V. P. 2008. Accuracy of kinematic wave approximation for flood routing, II: Unsteady analysis. Journal of Hydrologic Engineering, 13(11), 1089-1096. [doi:10.1061/ (ASCE)1084-0699(2008)13:11(1089)]
Perumal, M., and Sahoo, B. 2007. Volume conservation controversy of the variable parameter Muskingum-Cunge method. Journal of Hydraulic Engineering, 134(4), 475-485. [doi:10.1061/(ASCE) 0733-9429(2008)134:4(475)]
Ponce, V. M., and Lugo, A. 2001. Modeling looped ratings in Muskingum-Cunge routing. Journal of Hydrologic Engineering, 6(2), 119-124. [doi:10.1061/(ASCE)1084-0699(2001)6:2(119)]
Refsgaard, J. C., van der Sluijs, J. P., Højberg, A. L., and Vanrolleghem, P. A. 2007. Uncertainty in the environmental modelling process: A framework and guidance. Environmental Modelling and Software, 22(11), 1543-1556. [doi:10.1016/j.envsoft.2007.02.004]
Samani, H. M. V., and Shamsipour, G. A. 2004. Hydrologic flood routing in branched river systems via nonlinear optimization. Journal of Hydraulic Research, 42(1), 55-59. [doi:10.1080/00221686. 2004.9641183]
Song, X. M., Kong, F. Z., and Zhu, Z. X. 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]
Tsai, C. W. 2003. Applicability of kinematic, noninertia, and quasi-steady dynamic wave models to unsteady flow routing. Journal of Hydraulic Engineering, 129(8), 613-627. [doi:10.1061/(ASCE)0733-9429 (2003)129:8(613)]
U.S. Environmental Protection Agency (USEPA). 2003. Draft Guidance on the Development, Evaluation, and Applications of Regulatory Environmental Models. Washington, D.C.: The Council for Regulatory Environmental Modeling.
Venutelli, M. 2002. Stability and accuracy of weighted four-point implicit finite difference schemes for open channel flow. Journal of Hydraulic Engineering, 128(3), 281-288. [doi:10.1061/(ASCE)0733-9429 (2002)128:3(281)]
Venutelli, M. 2011. Analysis of dynamic wave model for unsteady flow in an open channel. Journal of Hydraulic Engineering, 137(9), 1072-1078. [doi:10.1061/(ASCE)HY.1943-7900.0000405)]
Vreugdenhil, C. B. 1994. Numerical Methods for Shallow-Water Flow. Dordrecht: Kluwer Academic Publishers.
Wang, G. T., Chen, S., Boll, J., and Singh, V. P. 2003. Nonlinear convection-diffusion equation with mixing-cell method for channel flood routing. Journal of Hydrologic Engineering, 8(5), 259-265. [doi:10.1061/(ASCE)1084-0699(2003)8:5(259)]
Wang, G. T., Yao, C., Okoren, C., and Chen, S. 2006. 4-Point FDF of Muskingum method based on the complete St Venant equations. Journal of Hydrology, 324(1-4), 339-349. [doi:10.1016/j.jhydrol. 2005.10.010]
Zhang, X. Q., and Bao, W. M. 2012. Modified Saint-Venant equations for flow simulation in tidal rivers. Water Science and Engineering, 5(1), 34-45. [doi:10.3882/j.issn.1674-2370.2012.01.004]
Zhang, Y. 2005. Simulation of open channel network flows using finite element approach. Communications in Nonlinear Science and Numerical Simulation, 10(5), 467-478. [doi:10.1016/j.cnsns.2003.12.006]
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