Linking fluvial bed sediment transport across scales

Zhang, Yong; Meerschaert, Mark M.; Packman, Aaron I.

doi:10.1029/2012gl053476

Cited by 78 publications

(99 citation statements)

References 20 publications

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“…The previous discussion has confirmed that the partial transport process of nonuniform bedload is time scale dependent (see for example, Nikora et al, 2002;Zhang et al, 2012). Moreover, the spatial nonlocal feature shown in Fig.…”

Section: Stochastic Model Analysissupporting

confidence: 49%

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Understanding partial bed-load transport: Experiments and stochastic model analysis

Sun

Chen

Zhang

et al. 2015

Journal of Hydrology

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s u m m a r yThe complex dynamics of partial bed-load transport in a series of well-controlled laboratory experiments are explored systematically and simulated by a stochastic model in this study. Flume experiments show that the leading front of bed-load on a 20-m-long, mixed-size gravel-bed moves anomalously, where the transient transport rate of the accelerating front varies with the observation time scale. In addition, observations show that moving particles may experience bimodal transport (i.e., coexistence of long trapping time and large jump length) related to bed coarsening and the formation of clusters on a heterogeneous gravel-bed, which is distinguished from the traditional theory of hiding-exposing interactions among mixed-size particles. A fractional derivative model is finally applied to characterize the overall behavior of partial bed-load transport, including the coexistence of the sub-diffusion and non-local feature caused by turbulence and the micro-relief within an armor layer.

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Section: Stochastic Model Analysissupporting

confidence: 49%

“…Furthermore, the transition from super-dispersion to sub-diffusion was observed and modeled by Martin et al (2012). Zhang et al (2012) proposed a tempered random walk model to describe the transition from super-dispersion to sub-dispersion, and the final convergence to Fickian dispersion for bedload sediment transport.…”

Section: Introductionmentioning

confidence: 99%

Understanding partial bed-load transport: Experiments and stochastic model analysis

Sun

Chen

Zhang

et al. 2015

Journal of Hydrology

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“…Furthermore, recent studies highlighted that the scaling behavior within a particular scale range as well as the boundaries between the ranges may depend on specific transport conditions or motion modes [5,10,14,18,22]. For instance, the transition from the intermediate scale range to the global range, expressed in terms of tu Ã =d (t is time, u Ã is friction velocity, d is particle diameter) has been found to vary from tens [14,17] to hundreds [3,22]. This discrepancy is likely to be a result of using the same dimensionless argument tu Ã =d for all scale ranges while it may be applicable only at shorter times corresponding to the local and intermediate scale ranges where particle dynamics effects are dominant.…”

Section: Introductionmentioning

confidence: 99%

Diffusion of bedload particles in open-channel flows: distribution of travel times and second-order statistics of particle trajectories

et al. 2015

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The motion of bedload particles is diffusive and occurs within at least three scale ranges: local, intermediate and global, each of which with a distinctly different diffusion regime. However, these regimes, extensions of the scale ranges and boundaries between them remain to be better defined and quantified. These issues are explored using a Lagrangian model of saltating grains over the uniform fixed bed. The model combines deterministic particle motion dynamics with stochastic characteristics such as probability distributions of step lengths and resting times. Specifically, it is proposed that a memoryless exponential distribution is an appropriate model for the distribution of rest periods while the probability that a particle stops after a current jump follows a binomial distribution, which is a distribution with lack of memory as well. These distributions are incorporated in the deterministic Lagrangian model of saltating grains and extensive numerical simulations are conducted for the identification of the diffusive behavior of particles at different time scales. Based on the simulations and physical considerations, the local, intermediate, and global scale ranges are quantified and the transitions from one range to another are studied for a spectrum of motion parameters. The obtained results demonstrate that two different time scales should be considered for parameterization of diffusive behavior within intermediate and global scale ranges and for defining the localintermediate and intermediate-global boundaries. The simulations highlight the importance of the distributions of the step lengths and resting times for the identification of the boundaries (or transition intervals) between the scale ranges.

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“…The dispersion rate, expressed as the variance of the tracers location, depends on the observation time scale (Nikora et al, 2002;Zhang et al, 2012). At long time, the variance increases linearly with time (Sayre and Hubbell, 1965;Zhang et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…, indicates anomalous diffusion (Nikora et al, 2002;Zhang et al, 2012). In the meantime, its skewness increases as γ ∝ t 4 .…”

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Advection and dispersion of bedload tracers

Lajeunesse¹,

Devauchelle²,

James³

2017

Preprint

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We use the erosion-deposition model introduced by Charru et al. (2004) to simulate numerically the evolution of a plume of bedload tracers entrained by a steady flow. In this model, the propagation of the plume results from the stochastic exchange of particles between the bed and the bedload layer. We find a transition between two asymptotic regimes. At early time, the tracers, initially at rest, are progressively set into motion by the flow. During this entrainment regime, the plume, strongly skewed in 5 the direction of propagation, continuously accelerates while spreading non-linearly. With time, the skewness of the plume eventually reaches a maximum value before decreasing. This marks the transition to an advection-diffusion regime in which the plume becomes increasingly symmetrical, spreads linearly, and advances at constant velocity. We derive analytically the expressions of the position, the variance and the skewness of the plume, and investigate their asymptotic regimes. Our model assumes steady state. In the field, however, bedload transport is intermittent. We show that the asymptotic regimes become 10 insensitive to this intermittency when expressed in terms of the distance traveled by the plume. If this finding applies to the field, it might provide an estimate for the average bedload transport rate.

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Linking fluvial bed sediment transport across scales

Cited by 78 publications

References 20 publications

Understanding partial bed-load transport: Experiments and stochastic model analysis

Understanding partial bed-load transport: Experiments and stochastic model analysis

Diffusion of bedload particles in open-channel flows: distribution of travel times and second-order statistics of particle trajectories

Advection and dispersion of bedload tracers

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