Interplay between grain protrusion and sediment entrainment in an experimental flume

Abstract

Bed load sediment transport is typically formulated as a nonlinear function of the shear stress exerted on the bed in excess of a critical value. However, due to the inherent spatial variability in grain packing and protrusion on water‐worked beds, the critical stress used in transport models represents a spatial averaging of the critical entrainment stresses of many individual particles on the bed. We perform a series of flume experiments in which we quantify, for the first time, the evolution of topography on the particle scale during low‐flow periods. We link this topography to subsequent bed load sediment transport rates and explore implications for particle critical stresses. We exploit the observed dependence of bed load flux on antecedent low‐flow duration to isolate the relationship between grain protrusion and bed load flux over a wide array of transport rates at the same applied stress. A synthesis of high‐resolution bed topography surveys and bed load flux data show that bed load transport rates characteristic of gravel channels are governed by the portion of grains that protrude highest above the bed and that this portion corresponds to ~1–5% of the total bed elevation distribution in our experiments. This result supports the argument that only a small portion of grain entrainment thresholds for a riverbed is exceeded during transport. Further, these results emphasize that subtle changes in bed topography can have dramatic effects on bed load sediment transport. We also find that transport of these highest protruding particles enhances the local erosion of surrounding grains.

The Physics of Sediment Transport Initiation, Cessation, and Entrainment Across Aeolian and Fluvial Environments

“…The existence of this class of creep implies that sediment is likely always transported (albeit slowly) for arbitrarily small values of , even in the absence of turbulence. Another recent experimental flume study (Masteller and Finnegan, ) showed a similar result, where conditioning a bed by applying weak fluid flow led to zero net transport but a smoother bed profile with fewer protruding grains. Then, when the fluid flow rate was increased to a value associated with significant transport for a conditioned bed, sediment transport rates were smaller when compared with an unconditioned bed.…”

Breaking from the average: Why large grains matter in gravel‐bed streams

“…Several studies have found that the mobility of large grains controls the availability of bulk material (Warburton, ; Lenzi et al. ; Masteller and Finnegan, ), as they act to trap mobile finer grains, thereby decreasing their proportion in the bedload (Wilcock and McArdell, ). Thus, when large grains become entrained they are not only adding themselves to the bedload but also releasing a large amount of finer material below.…”

The SPACE 1.0 model: a Landlab component for 2-D calculation of sediment transport, bedrock erosion, and landscape evolution

“…sure for channel width in which width scales as the square root of water discharge (e.g., Leopold and Maddock, 1953;Wohl and David, 2008), it may be desirable for some applications to add dynamic channel width adjustments to the model, as previous work has suggested that width trades off with slope in transient channels (e.g., Finnegan et al, 2005;Turowski et al, 2006;Wobus et al, 2006;Whittaker et al, 2007;Attal et al, 2008;Lague, 2010;Yanites and Tucker, 2010). One option for incorporating dynamic width is to calculate or approximate shear-stress distributions across channel cross sections (e.g., Kean and Smith, 2004;Wobus et al, 2006Wobus et al, , 2008Turowski et al, 2009).…”

“…Using a distribution of entrainment thresholds helps to account for the observation that incipient sediment motion does not begin at the same threshold value for all particles (e.g., Buffington and Montgomery, 1997). Variability in the threshold for motion is thought to be a function of grain size and shape variations (Kirchner et al, 1990;Wilcock and McArdell, 1997;Prancevic and Lamb, 2015), grain hiding and protrusion effects (Kirchner et al, 1990;Parker, 1990;Wilcock and McArdell, 1997;McEwan and Heald, 2001), bed sorting (Nelson et al, 2009), sediment flux (Johnson, 2016), and flow history (Masteller and Finnegan, 2017). Similarly, the threshold for bedrock erosion can depend on subreach-scale mineralogy, joint spacing and orientation, and the weathered state of the bedrock.…”

“…q is water discharge per unit channel width and may be calculated by any number of methods. The simplest is q = k q A m , where A is drainage area, m is a scaling exponent (generally ≈ 0.5) designed to reflect downstream width changes and discharge-area scaling (Leopold and Maddock, 1953;Snyder et al, 2003b;Wohl and David, 2008), and k q is an empirical constant, with units dependent on the value of m, that is subsumed into K s and the rock erodibility parameter K r . Using the volumetric water flux per unit channel width q results in K s and K r having dimensions of L −1 .…”