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A microstructural approach to bed load transport: mean behaviour and fluctuations of particle transport rates

Published online by Cambridge University Press:  10 March 2014

C. Ancey*
Affiliation:
Environmental Hydraulics Laboratory, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
J. Heyman
Affiliation:
Environmental Hydraulics Laboratory, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
*
Email address for correspondence: christophe.ancey@epfl.ch

Abstract

This paper concerns a model of bed load transport, which describes the advection and dispersion of coarse particles carried by a turbulent water stream. The challenge is to develop a microstructural approach that, on the one hand, yields a parsimonious description of particle transport at the microscopic scale and, on the other hand, leads to averaged equations at the macroscopic scale that can be consistently interpreted in light of the continuum equations used in hydraulics. The cornerstone of the theory is the proper determination of the particle flux fluctuations. Apart from turbulence-induced noise, fluctuations in the particle transport rate are generated by particle exchanges with the bed consisting of particle entrainment and deposition. At the particle scale, the evolution of the number of moving particles can be described probabilistically using a coupled set of reaction–diffusion master equations. Theoretically, this is interesting but impractical, as solving the governing equations is fraught with difficulty. Using the Poisson representation, we show that these multivariate master equations can be converted into Fokker–Planck equations without any simplifying approximations. Thus, in the continuum limit, we end up with a Langevin-like stochastic partial differential equation that governs the time and space variations of the probability density function for the number of moving particles. For steady-state flow conditions and a fixed control volume, the probability distributions of the number of moving particles and the particle flux can be calculated analytically. Taking the average of the microscopic governing equations leads to an average mass conservation equation, which takes the form of the classic Exner equation under certain conditions carefully addressed in the paper. Analysis also highlights the specific part played by a process we refer to as collective entrainment, i.e. a nonlinear feedback process in particle entrainment. In the absence of collective entrainment the fluctuations in the number of moving particles are Poissonian, which implies that at the macroscopic scale they act as white noise that mediates bed evolution. In contrast, when collective entrainment occurs, large non-Poissonian fluctuations arise, with the important consequence that the evolution at the macroscopic scale may depart significantly that predicted by the averaged Exner equation. Comparison with experimental data gives satisfactory results for steady-state flows.

Type
Papers
Copyright
© 2014 Cambridge University Press 

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References

Allen, E. J. 2007 Modeling with Itô Stochastic Differential Equations. Springer.Google Scholar
Ancey, C. 2010 Stochastic approximation of the Exner equation under lower-regime conditions. J. Geophys. Res. 115, F00A11.Google Scholar
Ancey, C., Bigillon, F., Frey, P., Lanier, J. & Ducret, R. 2002 Saltating motion of a bead in a rapid water stream. Phys. Rev. E 66, 036306.Google Scholar
Ancey, C., Böhm, T., Jodeau, M. & Frey, P. 2006 Statistical description of sediment transport experiments. Phys. Rev. E 74, 011302.Google Scholar
Ancey, C., Davison, A. C., Böhm, T., Jodeau, M. & Frey, P. 2008 Entrainment and motion of coarse particles in a shallow water stream down a steep slope. J. Fluid Mech. 595, 83114.CrossRefGoogle Scholar
Ballio, F., Nikora, V. & Coleman, S. E. 2013 On the definition of solid discharge in hydro-environment research and applications. J. Hydraul. Res. in press.Google Scholar
Balmforth, N. J. & Provenzale, A. 2001 Patterns of dirt. In Geomorphological Fluid Mechanics (ed. Balmforth, N. J. & Provenzale, A.), pp. 369393. Springer.Google Scholar
Böhm, T., Ancey, C., Frey, P., Reboud, J.-L. & Duccotet, C. 2004 Fluctuations of the solid discharge of gravity-driven particle flows in a turbulent stream. Phys. Rev. E 69, 061307.CrossRefGoogle Scholar
Bohorquez, P. & Darby, S. E. 2008 The use of one- and two-dimensional hydraulic modelling to reconstruct a glacial outburst flood in a steep Alpine valley. J. Hydrol. 361, 240261.CrossRefGoogle Scholar
Bulut, U. & Allen, E. J. 2012 Derivation of SPDEs for correlated random walk transport models in one and two dimensions. Stoch. Anal. Appl. 30, 553567.Google Scholar
Bunte, K. & Abt, S. 2005 Effect of sampling time on measured gravel bed load transport rates in a coarse-bedded stream. Water Resour. Res. 41, W11405.Google Scholar
Campagnol, J., Radice, A. & Ballio, F. 2012 Scale-based statistical analysis of sediment fluxes. Acta Geophys. 60, 17441777.CrossRefGoogle Scholar
Cao, Z., Day, R. & Egashira, S. 2002 Coupled and decoupled numerical modeling of flow and morphological evolution in alluvial rivers. J. Hydraul. Eng. 128, 306321.CrossRefGoogle Scholar
Charru, F. 2011 Hydrodynamic Instabilities. Cambridge University Press.Google Scholar
Chatanantavet, P., Whipple, K. X., Adams, M. A. & Lamb, M. P. 2013 Experimental study on coarse grain saltation dynamics in bedrock channels. J. Geophys. Res. F118, 11611176.CrossRefGoogle Scholar
Church, M. 2006 Bed material transport and the morphology of alluvial river channels. Annu. Rev. Earth Planet. Sci. 34, 325354.Google Scholar
Coleman, S. E. & Nikora, V. I. 2009 Bed and flow dynamics leading to sediment-wave initiation. Water Resour. Res. 45, W04402.CrossRefGoogle Scholar
Colombini, M. & Stocchino, A. 2011 Ripple and dune formation in rivers. J. Fluid Mech. 673, 121131.Google Scholar
Colombini, M. & Stocchino, A. 2012 Three-dimensional river bed forms. J. Fluid Mech. 695, 6380.Google Scholar
Cox, J. C., Ingersoll, J. E. & Ross, S. A. 1985 A theory of the term structure of interest rates. Econometrica 53, 385407.Google Scholar
Cudden, J. R. & Hoey, T. B. 2003 The causes of bedload pulses in a gravel channel: the implications of bedload grain-size distributions. Earth Surf. Process. Landf. 28, 14111428.Google Scholar
Cui, Y., Parker, G., Lisle, T. E., Pizzuto, J. E. & Dodd, A. M. 2005 More on the evolution of bed material waves in alluvial rivers. Earth Surf. Process. Landf. 30, 107114.Google Scholar
Defina, A. 2000 Two-dimensional shallow flow equations for partially dry areas. Water Resour. Res. 36, 32513264.Google Scholar
Dogan, E. & Allen, E. J. 2011 Derivation of stochastic partial differential equations for reaction–diffusion processes. Stoch. Anal. Appl. 29, 424443.CrossRefGoogle Scholar
Dornic, I., Chate, H. & Munoz, M. A. 2005 Integration of Langevin equations with multiplicative noise and the viability of field theories for absorbing phase transitions. Phys. Rev. Lett. 94, 100601.Google Scholar
Einstein, H. A.1950 The bed-load function for sediment transportation in open channel flows. Tech. Rep. Technical Report No. 1026. United States Department of Agriculture.Google Scholar
Fasolato, G., Ronco, P., Langendoen, E. J. & Di Silvio, G. 2011 Validity of uniform flow hypothesis in one-dimensional morphodynamic models. J. Hydraul. Eng. 137, 183195.Google Scholar
Feller, W. 1951 Two singular diffusion problems. Ann. Maths. 54, 173182.Google Scholar
Ferguson, R. I. 2012 River channel slope, flow resistance, and gravel entrainment thresholds. Water Resour. Res. 48, W05517.Google Scholar
Ferguson, R. I. & Church, M. 2009 A critical perspective on 1-D modeling of river processes: gravel load and aggradation in lower Fraser River. Water Resour. Res. 45, W11424.CrossRefGoogle Scholar
Fowler, A. C. 1997 Mathematical Models in the Applied Sciences. Cambridge University Press.Google Scholar
Fowler, A. C., Kopteva, N. & Oakley, C. 2007 The formation of river channels. SIAM J. Appl. Math. 67, 10161040.CrossRefGoogle Scholar
Furbish, D. J., Haff, P. K., Roseberry, J. C. & Schmeeckle, M. W. 2012a A probabilistic description of the bed load sediment flux: 1. Theory. J. Geophys. Res. 117, F03031.Google Scholar
Furbish, D. J., Roseberry, J. C. & Schmeeckle, M. W. 2012b A probabilistic description of the bed load sediment flux: 3. The particle velocity distribution and the diffusive flux. J. Geophys. Res. 117, F03033.Google Scholar
Ganti, et al. 2010.Google Scholar
García, M. H. 2007 Sediment transport and morphodynamics. In Sedimentation Engineering (ed. García, M. H.), ASCE Manuals and Reports on Engineering Practice, vol. 110, pp. 21164. American Society of Civil Engineers.Google Scholar
Gardiner, C. W. 1983 Handbook of Stochastic Methods. Springer.Google Scholar
Gardiner, C. W. & Chaturvedi, S. 1977 The Poisson representation. I. A new technique for chemical master equations. J. Stat. Phys. 17, 429468.Google Scholar
Gillespie, D. T. 1992 Markov Processes: An Introduction for Physical Scientists. Academic Press.Google Scholar
Gillespie, D. T. 2007 Stochastic simulation of chemical kinetics. Annu. Rev. Phys. Chem. 58, 3555.Google Scholar
Gomez, B. 1991 Bedload transport. Earth. Sci. Rev. 31, 89132.CrossRefGoogle Scholar
Graf, W. H. & Altinakar, S. 2005 Transport of sediments. In Encyclopedia of Hydrological Sciences (ed. Andersen, M. G.), John Wiley & Sons.Google Scholar
Hamamori, A.1962 A theoretical investigation on the fluctuations of bed load transport. Tech. Rep. Report R4. Delft Hydraulics Laboratory.Google Scholar
Helbing, D. 2001 Traffic and related self-driven many-particle systems. Rev. Mod. Phys. 73, 10671141.Google Scholar
Heyman, J., Mettra, F., Ma, H. B. & Ancey, C. 2013 Statistics of bedload transport over steep slopes: separation of time scales and collective motion. Geophys. Res. Lett. 40, 128133.Google Scholar
Hita, J. L. & Ortiz de Zárate, J. M. 2013 Spatial correlations in nonequilibrium reaction–diffusion problems by the Gillespie algorithm. Phys. Rev. E 87, 052802.Google Scholar
Hoyle, R. 2006 Pattern Formation. Cambridge University Press.Google Scholar
Iacus, S. M. 2008 Simulation and Inference for Stochastic Differential Equations. Springer.Google Scholar
Jerolmack, D. & Mohrig, D. 2005 A unified model for subaqueous bed form dynamics. Water Resour. Res. 41, W12421.Google Scholar
Katul, G., Wiberg, P., Albertson, J. & Hornberger, G. 2002 A mixing layer theory for flow resistance in shallow streams. Water Resour. Res. 38, 12501258.CrossRefGoogle Scholar
Lajeunesse, E., Malverti, L. & Charru, F. 2010 Bed load transport in turbulent flow at the grain scale: experiments and modeling. J. Geophys. Res. 115, F04001.Google Scholar
Lanzoni, S. 2008 Mathematical modelling of bedload transport over partially dry areas. Acta Geophys. 56 (3), 734752.Google Scholar
Lisle, T. E., Cui, Y., Parker, G., Pizzuto, J. E. & Dodd, A. 2001 The dominance of dispersion in the evolution of bed material waves in gravel-bed rivers. Earth Surf. Process. Landf. 26, 14091420.Google Scholar
Logan, J. D. 2001 Transport Modeling in Hydrogeochemical Systems. Springer.Google Scholar
Martin, R. L., Jerolmack, D. J. & Schumer, R. 2012 The physical basis for anomalous diffusion in bed load transport. J. Geophys. Res. 117, F01018.Google Scholar
Méndez, V., Fedotov, S. & Horsthemke, W. 2010 Reaction-Transport Systems: Mesoscopic Foundations, Fronts, and Spatial Instabilities. Springer.Google Scholar
Minier, J.-P. & Peirano, E. 2001 The pdf approach to turbulent polydispersed two-phase flows. Phys. Rep. 352, 1214.Google Scholar
Niño, Y., Atala, A., Barahona, M. & Aracena, D. 2002 Discrete particle model for analyzing bedform development. J. Hydraul. Eng. 128, 381389.CrossRefGoogle Scholar
Paola, C. 2000 Quantitative models of sedimentary basin filling. Sedimentology 47, 121178.CrossRefGoogle Scholar
Paola, C. & Voller, V. R. 2005 A generalized Exner equation for sediment mass balance. J. Geophys. Res. 110, F04014.Google Scholar
Parés, C. 2006 Numerical methods for nonconservative hyperbolic systems: a theoretical framework. SIAM J. Numer. Anal. 44, 300321.Google Scholar
Parker, G. 2008 Transport of gravel and sediment mixtures. In Sedimentation Engineering: Processes, Measurements, Modeling, and Practice (ed. Garcìa, M.), pp. 165252. ASCE.Google Scholar
Parker, G. & Izumi, N. 2000 Purely erosional cyclic and solitary steps created by flow over a cohesive bed. J. Fluid Mech. 419, 203238.CrossRefGoogle Scholar
Parker, G., Paola, C. & Leclair, S. 2000 Probabilistic Exner sediment continuity equation for mixtures with no active layer. J. Hydraul. Eng. 126, 818826.Google Scholar
Powell, D. M. 1998 Patterns and processes of sediment sorting in gravel-bed rivers. Prog. Phys. Geogr. 22, 132.CrossRefGoogle Scholar
Radice, A. 2009 Use of the Lorenz curve to quantify statistical nonuniformity of sediment transport rate. J. Hydraul. Eng. 135, 320326.Google Scholar
Radice, A., Ballio, F. & Nikora, V. 2009 On statistical properties of bed load sediment concentration. Water Resour. Res. 45, W06501.Google Scholar
Recking, A. 2013 An analysis of nonlinearity effects on bed load transport prediction. J. Geophys. Res. 118, 20090.Google Scholar
Recking, A., Frey, P., Paquier, A., Belleudy, P. & Champagne, J. Y. 2008 Feedback between bed load transport and flow resistance in gravel and cobble bed rivers. Water Resour. Res. 44, W05412.Google Scholar
Recking, A., Liébault, F., Peteuil, C. & Jolimet, T. 2012 Testing bedload transport equations with consideration of time scales. Earth Surf. Process. Landf. 37, 774789.Google Scholar
Rogers, S. S., Waigh, T. A., Zhao, X. & Lu, J. R. 2007 Precise particle tracking against a complicated background: polynomial fitting with Gaussian weight. Phys. Biol. 4, 220227.Google Scholar
Roseberry, J. C., Schmeeckle, M. W. & Furbish, D. J. 2012 A probabilistic description of the bed load sediment flux: 2. Particle activity and motions. J. Geophys. Res. 117, F03032.Google Scholar
Sagués, F., Sancho, J. M. & García-Ojalvo, J. 2007 Spatiotemporal order out of noise. Rev. Mod. Phys. 79, 829882.Google Scholar
Schulz, M. 2008 Chemical reactions and fluctuations: exact substitute processes for diffusion–reaction systems with exclusion rules. Eur. Phys. J. Spec. Top. 161, 150153.Google Scholar
Seminara, G. 2010 Fluvial sedimentary patterns. Annu. Rev. Fluid Mech. 42, 4366.Google Scholar
Singh, A., Fienberg, K., Jerolmack, D. J., Marr, J. & Foufoula-Georgiou, E. 2009 Experimental evidence for statistical scaling and intermittency in sediment transport rates. J. Geophys. Res. 114, 2007JF000963.Google Scholar
Tipper, J. C. 2007 The ‘stochastic river’: the use of budget-capacity modelling as a basis for predicting long-term properties of stratigraphic successions. Sediment Geol. 202, 269280.Google Scholar
Turowski, J. M. 2010 Probability distributions of bed load transport rates: a new derivation and comparison with field data. Water Resour. Res. 46, W08501.Google Scholar
Vollmer, S. & Kleinhans, M. G. 2007 Predicting incipient motion, including the effect of turbulent pressure fluctuations in the bed. Water Resour. Res. 43, W05410.Google Scholar
Wiberg, P. L. & Smith, J. D. 1985 A theoretical model for saltating grains in water. J. Geophys. Res. C 90, 73417354.Google Scholar
Wilcock, P. R., Pitlick, J. & Cui, Y.2009 Sediment transport primer: estimating bed-material transport in gravel-bed rivers. Tech. Rep. US Department of Agriculture, Forest Service, Rocky Mountain Research Station.Google Scholar
Yalin, M. S. 1972 Mechanics of Sediment Transport. Pergamon Press.Google Scholar
Zhang, et al. 2012.Google Scholar
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