Articles | Volume 4, issue 3
Research article
 | Highlight paper
29 Aug 2016
Research article | Highlight paper |  | 29 Aug 2016

Gravel threshold of motion: a state function of sediment transport disequilibrium?

Joel P. L. Johnson

Abstract. In most sediment transport models, a threshold variable dictates the shear stress at which non-negligible bedload transport begins. Previous work has demonstrated that nondimensional transport thresholds (τc*) vary with many factors related not only to grain size and shape, but also with characteristics of the local bed surface and sediment transport rate (qs). I propose a new model in which qs-dependent τc*, notated as τc(qs)*, evolves as a power-law function of net erosion or deposition. In the model, net entrainment is assumed to progressively remove more mobile particles while leaving behind more stable grains, gradually increasing τc(qs)* and reducing transport rates. Net deposition tends to fill in topographic lows, progressively leading to less stable distributions of surface grains, decreasing τc(qs)* and increasing transport rates. Model parameters are calibrated based on laboratory flume experiments that explore transport disequilibrium. The τc(qs)* equation is then incorporated into a simple morphodynamic model. The evolution of τc(qs)* is a negative feedback on morphologic change, while also allowing reaches to equilibrate to sediment supply at different slopes. Finally, τc(qs)* is interpreted to be an important but nonunique state variable for morphodynamics, in a manner consistent with state variables such as temperature in thermodynamics.

Short summary
Accurately predicting gravel transport rates in mountain rivers is difficult because of feedbacks with channel morphology. River bed surfaces evolve during floods, influencing transport rates. I propose that the threshold of gravel motion is a state variable for channel reach evolution. I develop a new model to predict how transport thresholds evolve as a function of transport rate, and then use laboratory flume experiments to calibrate and validate the model.