Journal Article

A Novel Laboratory Technique for Measuring Grain‐Size‐Specific Transport Characteristics of Bed Load Pulses

Reiterer, Kevin, Gold, Thomas, Habersack, Helmut, Sindelar, Christine, Hauer, Christoph

2024

Overview

Although several laboratory studies on the propagation of bed load pulses were carried out in the last decades, most studies neglect grain‐size‐specific aspects or use invasive measurement techniques. To remedy the situation, we present a novel, time‐efficient and non‐destructive laboratory technique to investigate grain‐size‐specific transport characteristics of bed load pulses. The method consists of a through‐water, high‐resolution image acquisition followed by the application of a supervised color classification algorithm (Gaussian Maximum Likelihood Classification). The analyzed bed load pulse consisted of five different grain size classes of dyed quartz sand and gravel, each having a unique color. The initial experimental bed was uni‐colored and contained the same size fractions as the augmented pulse. Quality assessment based on a confusion matrix approach and basic random sampling showed a high classification performance. By statistically analyzing the temporal and spatial color distribution of the experimental reach, characteristic parameters to describe the propagation behavior were determined. The bed load pulse presented in the application example initially showed strong deviations in the grain‐size‐specific advection and dispersion, and advection proved to be predominant in the transport process. Plain Language Summary In the present paper we introduce a novel laboratory method to investigate the grain‐size‐specific transport behavior of bed load pulses. A bedload pulse is a sudden increase in sand and gravel moving along the bottom of a river. We supplied a multi‐colored sediment input representing the downstream propagating pulse on a uni‐color experimental bed which contained the same size fractions than the pulse. Here, five different colors, each indicating a specific grain size fraction, were used as input. By automatically detecting the transported grains due to its color, we were able to analyze the grain‐size‐specific spreading and transport characteristics of the pulse. Therefore, we used high‐resolution photographs of our bed surface and applied a classification algorithm termed Gaussian Maximum Likelihood Classification. A quality assessment revealed a high classification accuracy of the used method. During the experiment, coarser fractions initially showed higher transport velocities. The transport process was dominated by a downstream shift (advection) of the plume rather than by the longitudinal spreading (dispersion). Key Points A novel image‐based, non‐destructive laboratory method to investigate grain‐size‐specific transport of bed load pulses is presented In addition to bed load pulse studies, the proposed method has high potential for other applications in sediment research The pulse in the application example evolves by a combination of advection and dispersion with a predominant advective component

• Publisher: John Wiley & Sons, Inc,Wiley
• Subject: Advection / Algorithms / Bed load / bed load pulse / bedload / Classification / clustering / Color / Colour / Dispersion / Gaussian maximum likelihood classification / Grain size / Gravel / Image acquisition / Laboratories / laboratory techniques / Measurement techniques / Particle size / Pulse propagation / Quality assessment / Quality control / quartz / Random sampling / Sand / Sand & gravel / sediment research / Sediment transport / statistical analysis / Statistical sampling / Transport phenomena / Transport processes / Transport properties / water