Erosional perturbations from changes in climate or tectonics are recorded in the profiles of bedrock rivers, but these signals can be challenging to unravel in settings with non-uniform lithology. In horizontally layered rocks, the surface lithology at a given location varies through time as different layers of rock are exposed. Recent modeling studies have used the Stream Power Model (SPM) to highlight complex variations in erosion rates that arise in bedrock rivers incising through layered rocks. However, these studies do not capture the effects of coarse sediment load on channel evolution. We use the “Stream Power with Alluvium Conservation and Entrainment” (SPACE) model to explore how sediment cover influences landscape evolution and modulates the topographic expression of erodibility contrasts in horizontally layered rocks. We simulate river evolution through alternating layers of hard and soft rock over million-year timescales, with a constant uplift rate of 1 mm/year. Compared to the SPM, model runs with sediment cover have systematically higher channel steepness values in soft rock layers and lower channel steepness values in hard rock layers. As sediment cover effects increase, the contrast in steepness between the two rock types decreases. Effective bedrock erodibilities back-calculated assuming the SPM are strongly influenced by sediment cover. We also find that sediment cover can significantly increase total relief and timescales of adjustment towards landscape-averaged steady-state topography and erosion rates.

A better understanding of how vegetation influences alluvial channels could improve (a) assessments of channel stability and flood risks, (b) applications of vegetation as a river management tool, and (c) predictions of channel responses to climate change and other human impacts. We take advantage of a natural field experiment in the semi-arid to arid Henry Mountains, Utah, USA: Large spatial differences in bed and bank vegetation are found along some alluvial channels due to localized perennial springs caused by aquicludes in the underlying bedrock. Airborne LiDAR topography and flood modeling are used to constrain channel morphology, vegetation density, and flow velocity at different flood discharges for three spring-fed reaches along intermittently-flowing streams. The spatial distribution of vegetation quantitatively influences both the magnitude and direction of channel adjustment. Reaches with abundant bed vegetation are significantly wider (by an average of ≈ 50%), with shallower flows and lower velocities, than reaches with little bed vegetation. Reaches with dense channel bank vegetation are ≈ 25% narrower and ≈ 25% deeper than sparsely-vegetated reaches. We interpret that sediment grain size influences the spatial distribution of vegetation within spring reaches, but that bank vegetation may be more important than grain size for “threshold” width adjustments. Widths, depths and velocities are fairly insensitive to whether local hydraulic roughness is parameterized in terms of local vegetation density or is assumed spatially constant, suggesting that the underlying “bare earth” topography of the channel bed, banks and floodplain exerts more control on local flow than does local vegetation density.

Bedload movement is fundamentally probabilistic. Our quantitative understanding of gravel transport is particularly limited when flow conditions just exceed thresholds of motion, in part because of difficulties in measuring transport statistics during floods. We used accelerometer-embedded tracer clasts to precisely measure the timing of grain motions and rests during snowmelt floods in Halfmoon Creek, a gravel-bed mountain stream in Colorado, USA. These new data let us explore how probabilities of tracer movement vary with snowmelt discharge. Bedload hysteresis occurred over both daily and seasonal timescales, and included clockwise, counter-clockwise, and figure-eight patterns. We quantitatively explain these observations in terms of how thresholds of motion progressively evolved over 22 days during a seasonal snowmelt flood. Our results suggest that thresholds of motion are functions of both (a) cumulative shear stress and (b) temporal changes in shear stress during floods.

We quantify how changes in natural flood discharge control bedload rest time distributions and may influence particle diffusion through mountain river networks. We embedded accelerometers and gyroscopes into artificial cobbles deployed in Halfmoon Creek, Colorado, USA, and measured bedload transport during 28 daily snowmelt flood hydrographs in 2015. From the motion sensor data we calculate motion and rest distributions over ~6 orders of temporal magnitude, from ~2 seconds to ~1 month. Motion durations follow a thin-tailed exponential distribution. Rests >12 hours can be well fit by both truncated Pareto distributions and exponentially-tempered Pareto distributions, suggesting ambiguity in whether rests remain heavy-tailed or transition to thin tails at even longer timescales. Rest time scaling varies not only with timescale but also with flow intensity, becoming less heavy-tailed as shear stress increases. A rest time scaling break at ~12 hours may be caused by daily discharge cyclicity.