1] Incipient motion of particles on a river bed can, in principle, be understood and predicted from a balance of the forces acting on the particles. On a natural river bed the exposure of particles to the flow is variable. The effect of exposure on the initiation of motion, including the case of deep embedding, is studied in this paper. So far, the turbulence-induced lifting force has been derived exclusively from examinations of the surface flow. The understanding of destabilization processes of the riverbed is improved when turbulence-induced vertical pressure gradients in the upper sediment layer are included. This is particularly important for particles that lie in the lee of larger ones. An analytical solution for the critical Shields parameter of spherical particles is found, including the effects of pressure fluctuations in the bed, macroscale flow structures, average bed slope, and shallow flow. Existing laboratory data designed to test the effect of exposure and roughness conditions are in excellent agreement with the new model. Citation: Vollmer, S., and M. G. Kleinhans (2007), Predicting incipient motion, including the effect of turbulent pressure fluctuations in the bed, Water Resour. Res., 43, W05410,
Sediments contained in the river bed do not necessarily contribute to morphological change. The finest part of the sediment mixture often fills the pores between the larger grains and can be removed without causing a drop in bed level. The discrimination between pore‐filling load and bed‐structure load, therefore, is of practical importance for morphological predictions. In this study, a new method is proposed to estimate the cut‐off grain size that forms the boundary between pore‐filling load and bed‐structure load. The method evaluates the pore structure of the river bed geometrically. Only detailed grain‐size distributions of the river bed are required as input to the method. A preliminary validation shows that the calculated porosity and cut‐off size values agree well with experimental data. Application of the new cut‐off size method to the river Rhine demonstrates that the estimated cut‐off size decreases in a downstream direction from about 2 to 0·05 mm, covariant with the downstream fining of bed sediments. Grain size fractions that are pore‐filling load in the upstream part of the river thus gradually become bed‐structure load in the downstream part. The estimated (mass) percentage of pore‐filling load in the river bed ranges from 0% in areas with a unimodal river bed, to about 22% in reaches with a bimodal sand‐gravel bed. The estimated bed porosity varies between 0·15 and 0·35, which is considerably less than the often‐used standard value of 0·40. The predicted cut‐off size between pore‐filling load and bed‐structure load (Dc,p) is fundamentally different from the cut‐off size between wash‐load and bed‐material load (Dc,w), irrespective of the method used to determine Dc,p or Dc,w. Dc,w values are in the order of 10−1 mm and mainly dependent on the flow characteristics, whereas Dc,p values are generally much larger (about 100 mm in gravel‐bed rivers) and dependent on the bed composition. Knowledge of Dc,w is important for the prediction of the total sediment transport in a river (including suspended fines that do not interact with the bed), whereas knowledge of Dc,p helps to improve morphological predictions, especially if spatial variations in Dc,p are taken into account. An alternative to using a spatially variable value of Dc,p in morphological models is to use a spatially variable bed porosity, which can also be predicted with the new method. In addition to the morphological benefits, the new method also has sedimentological applications. The possibility to determine quickly whether a sediment mixture is clast‐supported or matrix‐supported may help to better understand downstream fining trends, sediment entrainment thresholds and variations in hydraulic conductivity.
[1] Although porosity is a key property of sediment mixtures, little is known of the natural variations in porosity in fluvial systems. Porosity predictors can help to generate such information. The objective of this study was to determine the accuracy of porosity predictors for fluvial sand-gravel mixtures. In order to do so, porosity measurements were done in the Rhine River, using a diving bell to allow undisturbed sampling under water. In addition, laboratory experiments were conducted, and porosity data from literature were reanalyzed. Measured porosity values range from 0.06 to 0.48. Our study shows that predictors based on the median grain size, the deviation from the Fuller curve, or the sediment standard deviation are unable to reproduce the observed variation in porosity. Predictors based on the entire grain size distribution perform better but are biased and have a large prediction error. This suggests that they do not account correctly for the grain size effect on porosity. On the other hand, parameters such as grain shape and the mechanism of deposition probably also have a distinct influence on porosity. Slightly more accurate predictions can be obtained with tailor-made predictors for the river under interest. Multivariate regression analysis on the Rhine data set produced a predictor with two independent parameters: the sediment standard deviation and the number of grains smaller than 0.5 mm, representing grain mixing effects and adhesion effects, respectively. Despite the shortcomings, porosity predictors provide valuable insights in the spatial variation in porosity, which is demonstrated in a case study for the Rhine River.Citation: Frings, R. M., H. Schüttrumpf, and S. Vollmer (2011), Verification of porosity predictors for fluvial sand-gravel deposits, Water Resour. Res., 47, W07525,
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