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

References

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Journal of Hydraulics
Volume 13, Issue 4 - Serial Number 134
February 2019
Pages 93-110

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History

  • Receive Date: 26 October 2018
  • Revise Date: 23 November 2018
  • Accept Date: 30 November 2018

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