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The influence of boulders in high gradient gravel‐bed rivers can be significant. Yet few studies have isolated their role in regulating bedload. It is hypothesized that boulder relative submergence and the corresponding eddies developing around boulders affect the frequency of bedload pulsations and the location of sediment deposits. Results show the occurrence of two distinct timescales in bedload exiting a boulder array, which were identified via time series analysis. These are the small‐scale periodicity, PS, and the large‐scale periodicity, PL. PS was identified in the range of 4–6 min and is believed to result from congested bedload movement due to reduced conveyance area within the array. PL was identified in the range of 8–46 min. It is suggested that PL corresponds to large bedload releases around boulders, which the authors consider to be caused by feedbacks between boulder eddies and bedload deposits. It is also found that boulder submergence and Froude number, Fr, influence the location of predominant deposition. At High Relative Submergence, deposition occurs in the boulder wake regions. At Low Relative Submergence, deposition instead occurs upstream of boulders in locations that depend on Fr. For Fr < 1, material deposits in the stoss of boulders due to the necklace structure of the horseshoe vortex. However, for Fr > 1, material deposits at the flanks of boulders due to the influence of local wave crests around boulders. The trapping efficiency of boulders reduces the dimensionless mean bedload transport rate by three orders of magnitude compared to conditions without boulders. Key Points: Distinct timescales of bedload transport fluctuations through a boulder array are identifiedKey hydraulic mechanisms in the vicinity of boulders influence boulder controls on bed morphology and bedload transportBoulder relative submergence and Froude number describe the nature of the flow in the boulder vicinity and location of depositional patches [ABSTRACT FROM AUTHOR]

A generalized probabilistic model is developed in this study to predict sediment entrainment under the incipient motion, rolling, and pickup modes. A novelty of the proposed model is that it incorporates in its formulation the probability density function of the bed shear stress, instead of the near-bed velocity fluctuations, to account for the effects of both flow turbulence and bed surface irregularity on sediment entrainment. The proposed model incorporates in its formulation the collective effects of three parameters describing bed surface irregularity, namely the relative roughness, the volumetric fraction and relative position of sediment particles within the active layer. Another key feature of the model is that it provides a criterion for estimating the lift and drag coefficients jointly based on the recognition that lift and drag forces acting on sediment particles are interdependent and vary with particle protrusion and packing density. The model was validated using laboratory data of both fine and coarse sediment and was compared with previously published models. The study results show that all the examined models perform adequately for the fine sediment data, where the sediment particles have more uniform gradation and relative roughness is not a factor. The proposed model was particularly suited for the coarse sediment data, where the increased bed irregularity was captured by the new parameters introduced in the model formulation. As a result, the proposed model yielded smaller prediction errors and physically acceptable values for the lift coefficient compared to the other models in case of the coarse sediment data. [ABSTRACT FROM AUTHOR]

A reliable depth-integrated model that is suited for capturing the complex flow found with an array of submerged boulders over a permeable rough bed can be an attractive tool for river management. This paper presents a new nonhydrostatic quasi-three-dimensional (3D) calculation method called the general bottom velocity computation of the fourth-degree polynomial equation for vertical distribution of velocity coupled with the dynamic wall law (GBVC4-DWL). The computational domain of the GBVC4-DWL method considers the presence of the boulders, a vortex layer on the bed surface, and a roughness layer under the bed surface. The novelty of this study is that it introduces a dynamic rough wall law for the bottom boundary condition that includes the continuity and momentum equations for vortex and roughness layers to evaluate the nonequilibrium flow induced by the boulders. Comparisons of the results of the present method with previous experimental results and results of previous calculation methods indicate that the present method exhibits considerable improvements in calculating the velocity distribution over a rough bed with isolated submerged boulders. [ABSTRACT FROM AUTHOR]

Radio frequency identification (RFID) technology enables bidirectional, remote communication between a reader and a transponder (or tag) with a unique ID via an excitation antenna. This study provides a framework for estimating the burial depth of a transponder from a fixed location as a means of assessing scour depth or for other riverine applications. In doing so, a low frequency (LF), passive RFID system is used, which operates at a resonance frequency of 134.2 kHz and can penetrate through saturated sediments. The objective of this research is the development and validation of a semitheoretical expression that relates the decay of the received input voltage (VIN) at the reader with the transponder burial depth or detection distance, d, through a series of well-controlled experiments. This study examines the correspondence between VIN and d in air, as well as in water, gravel, and sand, and assesses the role of transponder orientation (perpendicular and parallel with respect to the excitation antenna) on the received VIN. It is found that VIN exhibits a universal behavior as a function of d as it decays inversely with the cube of the distance (∼d-3) not only for air but also for water, gravel, and sand. More importantly, it is shown that the orientation angle between the excitation and the transponder miniature antennas as well as the sediment-bed composition/texture (e.g., sand, clay, gravel) surrounding the transponder can have a significant effect on the magnitude of the VIN and on the decay rate of the VIN versus d curve. A change in the transponder orientation from perpendicular to parallel reduces the VIN by one order of magnitude and the maximum detection d by 26-76% for the different media. The greatest reduction in VIN occurs for sand, likely due to its smaller void ratio that causes excessive defragmentation of the RF waves. These promising findings allow a relatively accurate, remote estimation of d using the inexpensive LF, passive RFID technology and warrant future research and development on this topic. [ABSTRACT FROM AUTHOR]

The purpose of this study is to develop a relationship for predicting the bedload rate from the acoustic signal of a geophone, under the rolling and saltating bedload transport modes. Controlled experiments corresponding to near-incipient, marginal, and general bedload motion were conducted. The geophone recorded impacts and resulting acoustic signal impulses at the lower “Frequency 1” (100–200 kHz) and the higher “Frequency 4” (380–480 kHz) ranges. Rolling particles produced stronger responses in Frequency 1 and weaker in Frequency 4 due to rotational vibrations. Instead, saltating particles generated stronger responses in Frequency 4 and weaker in Frequency 1 because of spheroid vibrations. The impulse in both Frequency 1 and 4 was related to bedload transport, as it accounts for the number and magnitude of the signal spikes due to the particle impacts. This study complements efforts for quantifying bedload transport using geophones by relating bedload to impulse for rolling and saltation. [ABSTRACT FROM PUBLISHER]

Abstract: The emphasis of this paper is on the fractal-analysis of irregular objects like particle clusters that fill the two-dimensional Euclidean space R 2. A common fractal descriptor of such objects is D L (1< D L <2), which defines the fractal dimension of the object outline and is determined by the divider method. In this case, an object may possibly exhibit only two statistically self-similar scales, namely ‘structural’ and ‘textural’. The structural fractal dimension describes the form structure (or the degree of convolution) of the object perimeter and the textural describes the crenellations (or edge effects) found on the object perimeter. Recent studies have shown that the D L does not uniquely define the morphology of complex objects like clusters as it does not include the morphologic attributes, associated with the objects enclosed projected area. A key contribution of this work is the recognition that the ‘total areal’ fractal dimension of the object, D AT (1< D AT <2) offers a unique description of cluster morphology as it accounts for the collective contributions from the crenellations found on the object perimeter and its form structure, as well as contributions from the object core structure or equivalently object projected area. The D AT , which is theoretically interrelated to D L , satisfies the key self-similarity principle of fractals and is employed here to differentiate among four cluster morphologic groups observed in field and laboratory studies, namely, in-line clusters with elongation ratio, ER <5 and ER >5, pseudo-triangle, and -rhomboid. The analysis for this study is performed by applying the box-counting method for analyzing cluster planview images from four groups of cluster morphologies derived from synthetic, laboratory, and field data sets. The D AT is determined via Richardson plots by estimating the slope of the best-fit line over the entire range of box sizes. Doing so, provides a single aggregate dimension that includes the embedded effects from the objects projected area and perimeter. The results show that the average and its standard deviation can effectively discriminate the four cluster morphologic groups. The provides a clear demarcation between the nonlinear morphologies and the in-line morphology with ER >5. The analysis also shows that the in-line clusters with ER <5 change between pseudo-linear and pseudo-nonlinear morphologies. Moreover, it is found that most morphologies in the field are statistically well represented by the corresponding laboratory and synthetic morphologies. Finally, the analysis of the laboratory cluster data reveals the utility of for portraying the correspondence between cluster morphology and physical processes responsible for cluster formation and morphologic evolution, such as flow and sediment supply. Future research should build on the knowledge gained on this topic and further examine the links between the fractal dimension of different cluster morphologies and the physical processes that produce the characteristic scale captured by . [Copyright &y& Elsevier]