Revisiting the automated grain sizing technique (AGS) for characterizing grain size distribution

ABSTRACT

The automated grain sizing technique (AGS) has been widely used to characterize grain size distribution of a channel bed. A handful number of literatures have been made available in portraying the wide range of AGS application for river and coastal studies. However, the accuracy of this technique is subject to further validation and verification. The accuracy of the AGS technique is lessened due to distortions of image, relief, or tilt. This paper discusses the consistency of the AGS technique at different ground sampling distances, and the implementation of correction factors to modify the grain size distribution (GSD) curve of the AGS technique on fine and coarse fractions. Through a discrepancy ratio test, the GSD curve from the AGS technique was compared with those of the conventional sieving and pebble-counting methods. It was observed that relief distortion did not have a significant impact on the GSD curve. However, textural presence in sediment particles led to ‘over-segmentation,’ which complicated the edge detection of an individual particle. The introduction of correction factors, using least square regression equation, was able to correct those errors by reducing and maintaining the discrepancy ratio to 0.688–1.283 for fine fractions, and 0.758–1.125 for coarse fractions.

KEYWORDS:

• Automated grain sizing
• grain size distribution
• river bed material
• sieving
• relief distortion

Acknowledgement

A special gratitude to Nur Ayuni Zaiddin and Nur Sara Hazeqqa Johari, the GRA under this grant who helped on the field sampling and laboratory analysis. The writers are also grateful to the anonymous reviewers for their comments that helped improve the paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was partially funded by the Fundamental Research Grant Scheme [FRGS/1/2020/TK0/UMT/02/9] under the Ministry of Higher Education (MOHE) Malaysia.