Introducing and Evaluating the Effectiveness of Various Image Processing Algorithms in Determining Hydraulic Raughness Using Gradation Curve in Gravel Bed Rivers

Document Type : Research Article

Authors

1 IKIU

2 Assistant Professor, Imam Khomeini International University

3 Kharazmi University.

Abstract

The importance and role of bed roughness in conducting hydraulic flow studies and sediments,
especially in river simulation models, are not covered by any of the experts in this area. For this
reason, researchers used simple methods such as direct measurement using ruller or calipers or
mechanical sieving for many years to determine the size of roughness of bed particles. In recent years,
with the advancement of technology and the promotion of digital photography cameras, various
algorithms and software for automated analysis of bed surface data are provided using digital images
taken from the river bed. But so far, no comparative study has been conducted regarding the
comparison of the results of different methods and their validation and only researchers have been
evaluating and commenting on the shape of the gradation curve and the particle diameters. In this
study, imaging of one kilometer from the bed of the Kordan river in the west of the Alborz province,
and then the images obtained in nature, as well as images taken from the particles collected from the
bed in the laboratory with three different image processing methods and in two backgrounds with
different colors have been analyzed and compared with the results of the sieve analysis method. Based
on the results, it can be said that the presentation of an acceptable gradation curve does not mean the
accuracy of image methods, and these methods are sometimes found to have a notable error in the
counting of particles, which, by shrinking the image field or increasing the number of fine particles in
the image or the presence of particles with longitudinal elongation, this error will be tangible and
indescribable. Factors such as how adjacent particles are placed, the color and appearance of
aggregates, the distribution of light in the image, and the algorithm used to process the image on the
grain size curve, are effective. Therefore, using these methods in estimating hydraulic roughness
should be done with sufficient accuracy.

Keywords


حسن‌نژاد شریفی، ف.، صمدی، ا.، عزیزیان قطار، ا. (a1395) "ارزیابی عملکرد روش پردازش تصویر در تخمین ضریب زبری مانینگ در لایه سطحی بستر رودخانه‌ها". مجله تحقیقات آب و خاک ایران. 47 (4): 722- 711.
حسن‌نژاد شریفی، ف.، صمدی، ا.، عزیزیان قطار، ا. (b1395). "تحلیل حساسیت روش پردازش تصاویر در برآورد منحنی دانه‌بندی رسوبات سطحی بستر رودخانه نسبت به اندازه سطح رسوبی". مجله پژوهش آب ایران. 23: 142- 133.
زارعی، م.، مهاجری، س. ح.، صمدی، ا. (1396). "ارزیابی نتایج روشهای مختلف پردازش تصویر برای تهیه منحنی دانه­بندی بستر آبراهه­های شنی". شانزدهمین کنفرانس هیدرولیک ایران، دانشگاه محقق اردبیلی، اردبیل، ایران.
صادقی، س.ح. و قره‌محمودلی، س. (1392). "تحلیل دقت دانه‌بندی رسوبات بستر با استفاده از پردازش تصاویر حاصل از دوربین‌های با قدرت تفکیک مختلف". نشریه علمی- پژوهشی مهندسی و مدیریت آبخیز. 5 (2): 124- 115.
صمدی، ا. و عزیزیان، ا. (1394). "ارزیابی اثر توان تفکیک‌های مختلف تصویر بر نحوه استخراج منحنی دانه‌بندی مصالح سطحی بستر رودخانه به روش پردازش تصویر". نخستین کنگره ملی آبیاری و زهکشی ایران. دانشگاه فردوسی مشهد. مشهد. ایران. 23-24 اردیبهشت.
عبد شریف اصفهانی، م.، کرباسی، م.، رجبی هشجین، م. و کیاسالاری، ا. (1384). "معرفی روش عکس‌برداری شبکه‌ای از بستر رودخانه در تعیین دانه‌بندی لایه محافظ یک بستر درشت‌دانه (مطالعه موردی: رودخانه کرج)".‌ پنجمین‌کنفرانس هیدرولیک ایران. دانشگاه شهید باهنر. کرمان. 19- 17 آبان.
عزیزیان، ا.، مرشدی، ف. و آرین، ا. (1391). "استفاده از تکنیک پردازش تصویر جهت استخراج منحنی دانه‌بندی مصالح سطحی بستر رودخانه". نهمین سمینار بین‌المللی مهندسی رودخانه. دانشگاه شهید چمران. اهواز. ایران. 5- 3 بهمن.
سازمان مدیریت و برنامه‌ریزی کشور. (1394). راهنمای تعیین ضریب زبری هیدرولیکی رودخانه‌ها، نشریه شماره 688، سازمان مدیریت و برنامه‌ریزی کشور.
Adams, R.D. (2013). “Tool for Automated Image Based Grain Sizing”, MSc Thesis, Department of Civil and Environmental Engineering, Brigham Young University.
American Society for Testing and Materials (ASTM). (2006). “Standard test method for sieve analysis of fine and coarse aggregates”. C136 / C136M: 14.
Aquaveo LLC. (2013). “Hydraulic Toolbox”. Provo, Utah.
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: 539–549.
Bergendahl, B.S., and Arneson, L.A. (2014). “FHWA Hydraulic Toolbox”, v.4.2, Desktop Reference Guide, FHWA, Lakewood, CO.
Buffin-Bélanger, T., and Roy, A.G. (1998). “Effects of a pebble cluster on the turbulent structure of a depth-limited flow in a gravel-bed river”, Geomorphology, 25: 249-267.
Buscombe, D., Rubin, D.M., and Warrick, J.A. (2010). “A universal approximation of grain size from images of noncohesive sediment”. Journal of Geophysical Research, 115(F02015).
Butler, J.B., Lane, S.N., and Chandler, J.H. (2001). “Automated extraction of grain-size data from gravel surfaces using digital image processing”, J. Hydraul. Res., 39: 519–529.
Carbonneau, P.E., Lane, S.N., and Bergeron, N.E. (2004). “Catchment-scale mapping of surface grain size in gravel bed rivers using airborne digital imagery”. WRR 40(W07202).
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.
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.
Detert, M., and Weitbrecht, V. (2012). “Automatic object detection to analyze the geometry of gravel grains – a free stand-alone tool”. River Flow 2012, R.M. Muños, ed., Taylor & Francis Group, London, ISBN 978-0-415-62129-8, 595-600.
Detert, M., and Weitbrecht, V. (2013). “User guide to gravelometric image analysis by BASEGRAIN”, In: Advances in River Sediment Research, S. Fukuoka, H. Nakagawa, T. Sumi, H. Zhang, eds., Taylor & Francis Group, London, ISBN 978-1-138-00062-9, 1789-1795.
Fehr, R. (1987). “Einfache Bestimmung der Korngrössenverteilung von Geschiebematerial mit Hilfe der Linienzahlanalyse (Simple detection of grain size distribution of sediment material using line-count analysis)”. Schweizer Ingenieur undArchitekt 105(38); 1104–1109. (In German)
Ferreira, T., and Rasband, W.S. (2012).  “ImageJ, User Guide”, IJ 1.46r, U.S. National Institutes of Health, Bethesda, Maryland, USA, imagej.nih.gov/ij/docs/ guide/, 2010-2012.
Graf, W. and Altinakar, M. (1998). Fluvial Hydraulics, Wiley, New York.
Graham, D.J., Reid, I., and Rice, S.P. (2005a). “Automated sizing of coarse grained sediments: Image-processing procedures”.  Mathematical Geology, 37(1): 1-28.
Graham, D.J., Rice, S.P., and Reid, I. (2005b). “A transferable method for the automated grain sizing of river gravels”. Water Resources Research, 41, W07020.
Heritage, G.L., and Milan, D.J. (2009). “Terrestrial Laser scanning of grain roughness in a gravel-bed river”. Geomor. 113, 4–11.
Mohajeri, 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.I., Goring D.G. and Biggs B.F. (1998). "On gravel-bed roughness characterization". Water Resources Research. 34, 517-527.
Nikora, V., Goring, D., McEwan, I., and Griffiths, G. (2001). “Spatially Averaged Open-Channel Flow over Rough Bed”, Journal of Hydraulic Engineering, 127: 123–133.
Nikora, V., McEwan, I., McLean, S., Coleman, S., Pokrajac, D., and Walters, R. (2007). “Double-averaging concept for rough-bed open-channel and overland flows: Theoretical background”, Journal of Hydraulic Engineering. 133(8): 873-883.
Parker, G. (1991). “Selective sorting and abrasion of river gravel. II: Applications”. J. of Hyd. Eng., 117(2): 150-171.
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, US.
Rasband, W.S. (2012). “ImageJ”, U.S. National Institutes of Health, Bethesda, Maryland, USA, 1997–2012.
Rice, S.P. (1999). “The nature and controls on downstream fining within sedimentary links”. J. of Sed. Res., 69(1): 32–39.
Sadeghi, S.H.R., Khaledi Darvishan, A.A.V., and Vafakhah, M. (2007). “Study on Channel Hydraulic Characteristics on Morphometric Variations of Bed Materials”, Journal of Hydraulics, 2: 1-10. (In Farsi)
Stähly, S., Friedrich, H., and Detert, M. (2017). “Size Ratio of Fluvial Grains’ Intermediate Axes Assessed by Image Processing and Square-Hole Sieving”, Journal of Hydraulic Engineering, American Society of Civil Engineers, 143(6): 06017005-1 to 06017005-6.
Strom, 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: 461–473.
Webb, R.H., and Leake, S.A. (2006). “Ground-water surface-water interactions and long-term change in riverine riparian vegetation in the southwestern United States”, Journal of Hydrology, 320: 302-323.
Weichert, R., Wickenhäuser, M., Bezzola, G.R., and Minor, H.-E. (2004). “Grain size analysis for coarse river beds using digital imagery processing”. Proc. RF 2004, Naples, Italy, 753–760.
Volume 13, Issue 4 - Serial Number 134
February 2019
Pages 93-110
  • Receive Date: 26 October 2018
  • Revise Date: 23 November 2018
  • Accept Date: 30 November 2018
  • First Publish Date: 21 January 2019