OJMH  Vol.3 No.3 , July 2013
HEC-RAS Model for Mannnig’s Roughness: A Case Study
Channel roughness is considered as the most sensitive parameter in development of hydraulic models for flood forecasting and flood inundation mapping. Hence, it is essential to calibrate the channel roughness coefficient (Mannnig’s n value) for various river reaches through simulation of floods. In the present study it is attempted to calibrate and validate Mannnig’s n value using HEC-RAS for Mahanadi Riverin Odisha (India). For calibration of Mannnig’s n value, the floods for the years 2001 and 2003 have been considered. The calibrated model, in terms of channel roughness, has been used to simulate the flood for year2006 inthe same river reach. The performance of the calibrated and validated HEC-RAS based model has been tested using Nash and Sutcliffe efficiency. It is concluded from the simulation study that optimum Mannnig’s n value that can be used effectively for Khairmal to Barmul reach of Mahanadi Riveris 0.029. It is also verified that the peak flood discharge and time to reach peak value computed using Mannnig’s n of 0.029 showed only an error of 5.42% as compared with the observed flood data of year 2006.

Cite this paper
P. Parhi, "HEC-RAS Model for Mannnig’s Roughness: A Case Study," Open Journal of Modern Hydrology, Vol. 3 No. 3, 2013, pp. 97-101. doi: 10.4236/ojmh.2013.33013.

[1]   W.-M. Bao, X.-Q. Zhang and S.-M. Qu, “Dynamic Correction of Roughness in the Hydrodynamic Model,” Journal of Hydrodynamics, Vol. 21, No. 2, 2009, pp. 255-263. doi:10.1016/S1001-6058(08)60143-2

[2]   R. Ramesh, B. Datta, S. Bhallamudi and A. Narayana, “Optimal Estimation of Roughness in Open-Channel Flows,” Journal of Hydraulic Engineering, Vol. 126, No. 4, 1997, pp. 299-303. doi:10.1061/(ASCE)0733-9429(2000)126:4(299)

[3]   HEC-RAS, “User Manual,” US Army Corps of Engineers, Hydrologic Engineering Center, Davis Version 4.0, 2008.

[4]   S. Patro, C. Chatterjee, S. Mohanty, R. Singh and N. S. Raghuwanshi, “Flood Inundation Modeling Using Mike Flood and Remote Sensing Data,” Journal of the Indian Society of Remote Sensing, Vol. 37, No. 1, 2009, pp. 107-118. doi:10.1007/s12524-009-0002-1

[5]   N. Usul and T. Burak, “Flood Forecasting and Analysis within the Ulus Basin, Turkey, Using Geographic Information Systems,” Natural Hazards, Vol. 39, No. 2, 2006, pp. 213-229. doi:10.1007/s11069-006-0024-8

[6]   R. Vijay, A. Sargoankar and A. Gupta, “Hydrodynamic Simulation of River Yamuna for Riverbed Assessment: A Case Study of Delhi Region,” Environmental Monitoring Assessment, Vol. 130, No. 1-3, 2007, pp. 381-387. doi:10.1007/s10661-006-9405-4

[7]   P. K. Parhi, R. N. Sankhua and G. P. Roy, “Calibration of Channel Roughness of Mahanadi River (India) Using HEC-RAS Model,” Journal of Water Resources and Protection, Vol. 4, No. 10, 2012, pp. 847-850. doi:10.4236/jwarp.2012.410098

[8]   A. M. Wasantha Lal, “Calibration of Riverbed Roughness,” Journal of Hydraulic Engineering, Vol. 121, No. 9, 1995, pp. 664-671. doi:10.1061/(ASCE)0733-9429(1995)121:9(664)

[9]   P. V. Timbadiya, P. L. Patel and P. D. Porey, “Calibration of HEC-RAS Model on Prediction of Flood for Lower Tapi River, India,” Journal of Water Resources and Protection, Vol. 3, No. 11, 2011, pp. 805-811. doi:10.4236/jwarp.2011.311090

[10]   R. Doherty, “Calibration of HEC-RAS Models for Rating Curve Development in Semi Arid Regions of Western Australia,” AHA 2010 Conference, Perth, 2010.

[11]   HEC-RAS, “Hydraulic Reference Manual,” US Army Corps of Engineers, Hydrologic Engineering Center, Davis Version 4.0, 2008.

[12]   P. K. Mishra and S. Behera, “Flood Management Planning in the Mahanadi River Basin Odisha,” 7th International R&D Conference, Bhubaneswar, 4-6 February 2009, pp. 149-150.

[13]   J. E. Nash and J. V. Sutcliffe, “River Flow Forecasting through Conceptual Models, Part I—A Discussion of Principles,” Journal of Hydrology, Vol. 10, No. 3, 1970, pp. 282-290. doi:10.1016/0022-1694(70)90255-6

[14]   V. T. Chow, “Open Channel Hydraulics,” McGraw Hill Book Company, New York, 1959.