Evaluation of Image Processing Technique in Estimating the Manning’s Roughness Coefficient in the Surface Layer of Riverbeds

Document Type : Research Paper

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Abstract

Considering the importance of adequate roughness coefficient estimation in river engineering studies, evaluation of image processing technique in estimating Manning’s roughness coefficient in the surface layer of riverbeds carried out in this study. The mentioned approach evaluation conducted by implementing of sieving analysis and digital image processing methods simultaneously for a 7.5km reach of Shalmanrood River of Gilan. The processing of captured images signifies that this technique has an excellent accuracy in estimating the size of sediment particles (particles with a size of d50 or larger) and can be used to estimate Manning’s roughness coefficient of sediment particles of riverbed, utilizing the given empirical formulas. To evaluate the image processing results in estimating Manning’s coefficient values, one-dimensional modeling by HEC-RAS Hydraulic model was used and the model was conducted through different scenarios. Finally, on given cross sections, the comparison of output hydraulic properties with respect to Cowan’s method results showed that Bray’s empirical formula (d90) will have the best efficiency in estimating the Manning’s roughness coefficients in the surface of riverbed, with a maximum relative difference of 13.7% in top width.

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References

Abdesharif Esfahani, M., Karbasi, M., Rajabi-hashjin, M. and Kiasalari, A. (2005). Introduction of grid photography method of riverbed for determining armored-layer gradation of a coarse-grained bed (Case study: Karaj River). 5th Iranian Hydraulic Conference, 8-10 Nov., Shahid Bahonar University, Kerman, Iran. (In Farsi)
Aberle, J. and Nikora, V. (2006). Statistical properties of armored gravel bed surfaces. Water Resources Research, 42(11), W11414, doi:10.1029/2005WR004674.
Acement, G. S. and Schneider V. R. (1985). Guide for selecting Manning’s roughness coefficent for natural channels and flood plains, Water Resources paper 2339, US Geological survey, Washington DC. (updated 2002), 98 pages.
American Society for Testing and Materials (ASTM). (2006). Standard test method for sieve analysis of fine and coarse aggregates. C136 / C136M: 14.
Azizian, A., Morshedi, F. and Arian, A. (2013). Utilization of image processing technique for obtaining surface material gradation curve of the riverbed. 9th River Engineering International Seminar, 22-24 Jan., Shahid Chamran University, Ahvaz, Iran. (In Farsi)
Beggan, C. and Hamilton, C. W. (2010). New image processing software for analyzing object size-frequency distributions, geometry, orientation, and spatial distribution. Computers & Geosciences, 36(4), 539–549.
Bray, D.I. (1979). Estimating average velocity in gravel-bed rivers: American Society of Civil Engineers, Journal of the Hydraulics Division, 105(HY9), 1103-1122.
Chang, F.J. and Chung, Ch. H. (2012). Estimation of riverbed grain-size distribution using image processing techniques. Journal of Hydrology, 440-441: 102–112.
Cheng, Z. and Liu, H. (2015). Digital grain-size analysis based on autocorrelation algorithm. Sedimentary Geology, 327, 21–31.
Chow, V.T. (1959). Open-channel hydraulics, New York, McGraw-Hill, 680 p.
Chung, Ch. H. and Chang, F.J. (2013). A refined automated grain sizing method for estimating river-bed grain size distribution of digital images. Journal of Hydrology, 486, 224–233.
Cowan, W.L. (1956). Estimating hydraulic roughness coefficients, Agricultural Engineering, 377, 473–475.
Esmaeili Varaki, M., Zamani, A. and Kazemirad, M. (2012a). Numerical simulation of various cut-offs on meandering rivers, a case study: Shalman rood river in Guilan province. 11th Iranian Hydraulic Conference, 6-8 Nov., Urmia University, Urmia, Iran. (In Farsi)
Esmaeili Varaki, M., Shekholeslami, J. and Ashrafzadeh, A. (2012b). Effects of large floods on river morphology and flood zoning in areas vulnerable to damage, case study: Chabookroud river in Guilan province. 1st passive defence conference in Caspian sea basin, University of Guilan, Rasht, Iran. (In Farsi)
Garde, R.J., Ranga Raju, K.G. (1978). Mechanics of Sediment Transportation and Alluvial Stream Problems. Wiley Eastern, New Delhi.
Ghaffari, G. and Mosaedi, A. (2006). Effect of applying different Manning’s roughness coefficient determination methods to estimate the amount of flooding area (Case study, Babolroud River). J. Agric. Sci. Natur. Resour., 12(6), 11 – 20. (In Farsi)
Graham, D. J., Rice, S. P. and Reid, I. (2005). A transferable method for the automated grain sizing of river gravels. Water Resources Research, 41(7), 1-12.
Henderson, F.M. (1966). Open Channel Flow. MacMillan Publishing Co. Inc. New York, USA.
Lane, E.W., and Carlson, E.J. (1953). Some factors affecting the stability of canals constructed in coarse granular materials, Proceedings of International Association of Hydraulic Research, 5th Congress, Minneapolis.
Meyer – Peter, P.E., and Muller, R. (1948). Formulas for Bed Load Transport, Proceedings of the 3rd International Association for Hydraulic Research, Stockholm, 39-64.
Mohajeri, S.H. (2015). An investigation on gravel-bed roughness characterization. Journal of Hydraulics, 9(4), 73-86 (In Farsi).
Mohajeri, S.H., Grizzi, S., Righetti, M., Romano, G.P. and Nikora, V. (2015). The structure of gravel-bed flow with intermediate submergence: A laboratory study. Water Resources Research, 51(11), 9232-9255.
Nikora, V., Goring, D., McEwan, I. and Griffiths, G. (2001). Spatially averaged open-channel flow over rough bed. Journal of Hydraulic Engineering, 127(2), 123–133.
Penders, C.A. (2010). Determining mean grain-size in high gradient streams with autocorrelative digital image processing. Master of Science Thesis, Appalachian State University, Boone, North Carolina, United States.
Publication No. 331-a. (2009). Guideline for Determination of the Hydraulic Roughness Coefficient of Rivers. Draft, Bureau of Engineering and Technical Criterias for Water and Wastewater, Ministry of Energy, Iran. (In Farsi)
Raudkivi, A.J. (1976). Loose Boundary Hydraulics. 2nd ed., Pergamon Press, New York.
Rubin, D.M. (2004). A Simple Autocorrelation Algorithm for Determining Grain Size from Digital Images of Sediment, Journal of Sedimantary Research, 74(1), 160-165.
Rubin, D.M., Chezar, H., Harney, J. N., Topping, D. J., Melis, T. S. and Sherwood, C. R. (2007). Underwater microscope for measuring spatial and temporal changes in bed-sediment grain size. Sedimentary Geology, 202(3), 402–408.
Sadeghi, S. H. and Gharemahmoodli, S. (2013). Accuracy analysis of bed sediment gradation using the processing of images of cameras with different resolutions. Journal of Watershed Engineering and Management, 5(2), 115-124. (In Farsi)
Samadi, A. and Azizian, A. (2015). Evaluating the effect of different image resolutions on obtaining the surface material gradation curve of riverbed using image processing technique. 1st National Congress on Iran’s Irrigation & Drainage, 13-14 May., Ferdowsi University, Mashhad, Iran. (In Farsi)
Storm, K. B., Kuhns, R. D. and Lucas, H. J. (2010). Comparison of automated image-based grain sizing to standard pebble-count methods. Journal of Hydraulic Engineering, 136(8), 461–473.
Strickler A. (1923). Beiträge zur Frage der Geschwindigkeitsformel und der Rauhigkeitszahlen fur Ströme, Kanäle und Geschlossene Leitungen, Berna.
Subramanya, K. (1982). Flow in Open Channels. vol. 1, Tata McGraw-Hill Book Company, New York.
Warrick, J. A., Rubin, D. M., Ruggiero, P., Harney, J. N., Draut, A. E. and Buscombe, D. (2009). Cobble cam: grain-size measurements of sand to boulder from digital photographs and autocorrelation analyses. Earth Surface Processes and Landforms, 34(13), 1811–1821.
Iranian Journal of Soil and Water Research
Volume 47, Issue 4 - Serial Number 4
January 2017
Pages 711-722

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