Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30135
Estimation of the Parameters of Muskingum Methods for the Prediction of the Flood Depth in the Moudjar River Catchment

Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

Abstract:

The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1474811

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 575

References:


[1] A. O. Akan,“Open Channel Hydraulics. Elsevier, New York, NY, USA”. 2006
[2] Aijia Ouyang, Zhuo Tang, Kenli Li, Ahmed Sallam, and Edwin Sha, 2014. “Estimating Parameters Of Muskingum Model Using An Adaptive Hybrid Pso Algorithm”. Int. J. Patt. Recogn. Artif. Intell. 28, 01, February 2014https://doi.org/10.1142/S0218001414590034.
[3] Al-Humoud, J. M. and Esen, I. I, 2006. Approximate Methods for the Estimation of Muskingum Flood Routing Parameters Water Resour Manage (2006) 20: 979. https://doi.org/10.1007/s11269-006-9018-2.
[4] Choudhury, P, Shrivastava, RK and Narulkar, SM. 2002. Flood routing in river networks using equivalent Muskingum inflow. Journal ofHydrologic Engineering 7(6): 413­419.
[5] Gelegenis, JJ and Sergio, ES. 2000. Analysis of Muskingum equation based flood routing schemes. Journal of Hydrologic Engineering, 5 (1):102-105.
[6] J. A. Cunge, “On the subject of a flood propagation computational method (Muskingum method)”. Journal of Hydraulic Research, 1969, 7(2): 205-230.
[7] J. Joo, T. Kjeldsen, H.-J. Kim, H. Lee, 2014. “A comparison of two event-based flood models (ReFH-rainfall runoff model and HEC-HMS) at two Korean catchments, Bukil and Jeungpyeong”, KSCE J. Civ. Eng. 18 (2014) 330–343. http://dx.doi.org/10.1007/s12205-013-0348-3.
[8] M. Azam, H. S. Kim, S. J. Maeng, 2017. “Development of flood alert application in Mushim stream watershed Korea”. International Journal of Disaster Risk Reduction, 2017, 21: 11–26.
[9] M. H. Tewolde, and J. C. Smithers, “Flood routing in ungauged catchments using Muskingum methods”. Water SA, 2006, 32(3), 379-388.
[10] Moramarco, T., Fan, Y., Bras, R. L., 1999. Analytical solution for channel routing with uniform lateral inflow. ASCE, J. Hydraul.Eng.125, 707–713.
[11] Ponce, V. M. and Hawkins, R. H. (1996) Runoff curve number: has it reached maturity. Journal of Hydrologic Engineering ASCE 1, 11–19.
[12] T. Haktanir, and H. Ozmen, 1997. “Comparison of hydraulic and hydrologic routing on three long reservoirs”.Journal of Hydraulic Engineering, 1997 123(2), 153-156. (doi:10.1061/(ASCE)0733-9429(1997)123:2(153)).
[13] Xiao-Meng Song, Fan-Zhe Kong, Zhao-Xia Zhu3. 2011. “Application of Muskingum routing method with variable parameters in ungauged basin”. Water Science and Engineering, 2011, 4(1), pp 1-12.
[14] Zhou Sheng, Aijia Ouyang, Li-Bin Liu, and Gonglin Yuan, 2014. “A Novel Parameter Estimation Method for Muskingum Model Using New Newton-Type Trust Region Algorithm”. Mathematical Problems in Engineering. Vol. 2014, pp. 1–7. http://dx.doi.org/10.1155/2014/634852.