Istrazivanja i projektovanja za privreduJournal of Applied Engineering Science


DOI: 10.5937/jaes0-37455 
This is an open access article distributed under the CC BY 4.0
Creative Commons License

Volume 20 article 1041 pages: 1366-1377

Jasem Alhumoud
Civil Engineering Department, College of Engineering and Petroleum, Kuwait University

There are several mathematical procedures that deal with hydrologic flood routing. The Muskingum technique is one of the most common techniques used for flood routing for river reach. From the hydrologic point of view, flood routing in a stream is used to predict the flood discharge, or storage, at any downstream station in a stream channel from a known discharge, or stage, at an upstream station. Hydrologic routing is an approximate technique. However, it provides relatively easy alternative, for solving flood routing problems. It is based on the storage and the continuity equations. In principle hydrologic routing employs historical data on inflow and outflow discharges in the reach under study. The Muskingum method is the particular one to be considered in this paper, describing three procedures, other than the classical trial and error procedure, for solving flood routing.

View article

The author is highly thankful to the distinguished reviewers of the paper for their insightful comments and suggestions.

1.      Fenton, J. D. (2019). Flood routing methods, Journal of Hydrology, 570: 251-264.

2.      Chow, V., Maidment, D. and Mays, L. (1988)Applies hydrology. McGraw-Hill Book Company, Singapore.

3.      Nagesh, K. D., Baliarsinghb, F., and Raju, K. S. (2011). Extended Muskingum method for flood routing, Journal of Hydro-environment Research, 5(2): 127-135.

4.      Guang, W. and Singh, V (1992). Muskingum Method with Variable Parameters for Flood Routing in Channels. Journal of Hydrology, 134: 57-76.

5.      O‚ÄôSullivan, J. J., Ahilan, S. and Bruen, M. (2012). A modified Muskingum routing approach for floodplain flows: Theory and practice, Journal of Hydrology, 470(12): 239-254.

6.      Ayvaz, M. T. and Gurarslan, G. (2017). A new partitioning approach for nonlinear Muskingum flood routing models with lateral flow contribution, Journal of Hydrology, 553: 142-159.

7.      Cai, X., Li, Y., Guo, X. and Wu, W. (2014). Mathematical model for flood routing based on cellular automaton, Water Science and Engineering, 7(2): 133-142.

8.      Akbari, R. and Masoud-Reza, H. (2021). Parameter estimation of Muskingum model using grey wolf optimizer algorithm, MethodsX, 8: 1-15.

9.      Alhumoud, J.M. and Esen, I.I. (2006)Approximate methods for the estimation of Muskingum flood routing parameters. Water Resources Management, 20(6): 230-245.

10.   MUZIKI, J. (2016). Meshless Solution of Incompressible Flow Over Backward-Facing Step, Civil and Environmental Engineering, 12(11): 63-68.

11.   Fenton, J. (2019)Flood routing methods. Journal of Hydrology, 570: 251-264.

12.   Al-Juboori, O.A., Hatim, A.R. and Mahjoob, A.M.R. (2021). Investigating the Critical Success Factors for Water Supply Projects: Case of Iraq, Civil and Environmental Engineering, 17(2): 438-449.

13.   Reggiani, P. and Todini, E. (2018)On the validity range and conservation properties of diffusion analogy and variable parameter Muskingum. Journal of Hydrology, 563: 167-180.

14.   Yoon, J. and Padmanabhan, G. (1993)Parameter Estimation of Linear and Nonlinear Muskingum Models. Journal of Water Resource, ASCE, 119(5): 600-610.

15.   Perumala, M., Tayfurb, G., Madhusudana R. C. and Gurarsland, G. (2017). Evaluation of a physically based quasi-linear and a conceptually based nonlinear Muskingum methods, Journal of Hydrology, 546: 437-449.

16.   McCarthy, G.T. (1938). The Unit Hydrograph and Flood Routing. Presented at Conference of North Atlantic   Division, U.S. Army Corps of Engineers.

17.   Nandia, S. and Redd, M. J. (2022). An integrated approach to streamflow estimation and flood inundation mapping using VIC, RAPID and LISFLOOD-FP, Journal of Hydrology, 610: 1-13.

18.   Barbetta, S., Coccia, G., Moramarco, T. and Todini, E. (2018)Real-time flood forecasting downstream river confluences using a Bayesian approach. Journal of Hydrology, 565: 516-523.

19.   Khalifeh, S., Esmaili, K., Khodashenas, S. R. and Akbarifard, S. (2020). Data on optimization of the non-linear Muskingum flood routing in Kardeh River using Goa algorithm, Data in Brief, 30: 1-7.

20.   Kim, D. (2018)High-spatial-resolution streamflow estimation at ungauged river sites or gauged sites with missing data using the National Hydrography Dataset (NHD) and U.S. Geological Survey (USGS) streamflow data. Journal of Hydrology, 565: 819-834.

21. A.     Munar, A., Cavalcanti, J., Bravo, J., and Fragoso, C. (2018)Coupling large-scale hydrological and hydrodynamic modeling: Toward a better comprehension of watershed-shallow lake processes. Journal of Hydrology, 564: 424-441.

22.   Hammer, M. and Mckichan, K. (1981)Hydrology and quality of water resources. John Wiley and sons, Inc. USA.

23.   Hjelmfelt, A. and Cassiday, I. (1974)Hydrology for engineers and planners. Iowa State, USA.