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Knowing the amount of sediment transported in rivers is important in river and hydraulic engineering. In essence, sediment transport process is very complex, whose direct measurement is not only challenging but also costly. In this regard, several equations have been developed to estimate sediment discharge, while their estimations may be an order of magnitudes different from one another under specific circumstances. In a bid to improve the estimation of sediment transport, this study proposed a new data-driven equation based on 543 reliable field measurements at 25 rivers using the Modified honey bee mating optimization (MHBMO) algorithm. The data include mean flow velocity, water surface slope, mean flow depth, median particle size, water surface width, suspended load, and bed load measured in the field. The performance of the new equation was compared to those of Yang, Engelund and Hansen, Shen and Hung, and Ackers and White using 6 metrics. Moreover, another nature-inspired optimization algorithm, i.e., genetic algorithm (GA) was employed to enhance the comparison. Based on the results, the MHBMO-based equation outperformed other estimation models and served as the best method in the ranking analysis. For instance, it improves the determination coefficient of Yang's equation, which is one of the widely-used equations recommended by the United States Bureau of Reclamation by 15.2%. Despite being ranked the second, the GA-based equation was only marginally less precise than the MHBMO-based model. Furthermore, the sensitivity analysis indicates that the sediment load is mostly sensitive to mean flow depth. Finally, it is postulated that applications of nature-inspired algorithms can help to improve the estimation of sediment transport. [ABSTRACT FROM AUTHOR]

Prediction of bedload rates in gravel-bed rivers at low-to-moderate flow conditions, where bedload movement is intermittent, remains a challenging problem. While the virtual velocity concept provides a useful approach to bedload rate estimation in the intermittent movement regime, virtual velocity estimation remains hindered by a lack of tools for predicting mean sediment resting time. As a first step toward sediment resting time estimation in gravel beds, the present study develops a semi-theoretical resting time model applicable to nonuniform gravel-sized spherical particles. The model is based on the consideration that interactions of near-bed flow with bed material lead to mobilization of individual resting particles during hydrodynamic momentum transfer events (i.e., impulses). Thus, resting time is affected by impulse magnitude and timing. The primary premise underpinning model development is that an instantaneous velocity time-series generation approach based on the velocity spectrum can be used to mimic hydrodynamic impulses and simulate resting times. Based on past findings, two model parameters are considered important to advancing resting time predictions in gravel beds. First, the relative particle size allows size-fractional resting time predictions for a nonuniform sediment mixture. Second, the hindrance coefficient accounts for hiding effects and enables resting time predictions for different bed structure types. To provide calibration and verification data, laboratory experiments documenting impulse statistics and mean resting times for a range of flow and relative particle size conditions were also performed. The verified model exhibits mean resting times with similar magnitude and trends with increasing stress compared with experimental verification data. [ABSTRACT FROM AUTHOR]

Sediment bed surfaces exist widely in natural rivers, and many aspects in river dynamics are closely relevant to bed surface roughness, such as flow structure, river resistance and sediment transport. As two important parameters for quantifying bed surface roughness, how average particle size and non-uniformity affect bed surface structure is unknown. Therefore, nine groups of sediment samples with different average particle sizes or different non-uniformities were firstly prepared by screening dry natural sediments. Then, the prepared sediment samples were used to manually pave nine groups of bed surfaces, and the high-precise bed surface digital elevations were obtained by a handheld 3D laser scanner. Finally, the effects exerted by the average particle size and non-uniformity on the bed surface fractal properties were discussed. The results showed that there is only a scale-free range in a profile or a two-dimensional specific direction of a bed surface with normal-distributed particle gradation. The averaged scale-free upper limit in the two-dimensional specific directions and that related to many profiles are less affected by the non-uniformity, but more affected by the average particle size. For the bed surfaces with the same non-uniformity, when the average particle size is smaller than 15 mm, the larger the average particle size is, the smaller the fractal dimension is, but the larger the scale coefficient is; when the average particle size is larger than 15 mm, the larger the average particle size is, the larger the fractal dimension and the scale coefficient are, while for the bed surfaces with the same average particle size, the non-uniformity has no significant effects on the fractal dimension and the scale coefficient. The averaged scale coefficient in the two-dimensional specific directions of an isotropic bed surface and that related to many profiles are approximately equal, but the averaged fractal dimension in the two-dimensional specific directions is obviously larger than that plus 1 related to many profiles. [ABSTRACT FROM AUTHOR]

The manuscript presents the results of an aggradation experiment performed in a laboratory channel with supercritical flow. The channel was fed with a stationary sediment load exceeding the transport capacity of the flow in the initial condition, thus inducing sediment aggradation and an increase of the bed slope. The experiment is part of a laboratory campaign mimicking sediment overloading in mountain rivers, a process that can determine increased hydraulic risk levels at key spots. A crucial issue in measuring sediment aggradation is the definition and determination of the bed elevation, this issue being quite relevant in experiments with a relatively large transport capacity, where a thick bed-load layer exists and hinders the possibility to determine with confidence a reference bed elevation. The determination of the bed elevation, in turn, impacts the quantification of a number of properties, including the initial sediment transport capacity of the flow, temporal scales of the aggradation process, water depth and Froude number. The manuscript presents a sensitivity analysis of the results to two extreme definitions for the bed elevation: the first one locates the bed at the upper edge of the bed-load layer, while the second one at the lower edge of the bed-load layer where the particles do not move. The presentation of the two alternatives is focused on the experimental methods they use, consistently with the intent of the special issue. Furthermore, it is demonstrated that the definition of the bed elevation also has a major impact on numerical models of the process. The experimental results have been reproduced numerically, demonstrating that the calibration parameters returning a best fit are also impacted significantly by how the bed is defined. The preferred definition for analyzing an experimental campaign is locating the bed below the bed-load layer. [ABSTRACT FROM AUTHOR]

Establishing and operating a harmonized sediment monitoring system along large rivers such as the Danube River is a challenging international task. As an element of such a system, a new monitoring site with state-of-the-art instrumentation is currently under development in the Upper-Hungarian section of the Danube River. The monitoring station will consist of a near-bank optical backscatter sensor and a horizontal acoustic Doppler current profiler (H-ADCP). As previous studies showed, the suspended sediment concentration (SSC) that is continuously measured with near-bank sensors can significantly enhance the temporal resolution of sediment transport monitoring. However, sediment plumes from tributary inflows upstream of the monitoring station can alter the detected near-bank concentrations, eventually biasing the sediment load estimation. Such an influence is likely in the cross-section of the planned monitoring station, therefore, a thorough preliminary analysis of the cross-sectional variation of the SSC was performed, based on expeditionary sediment measurement campaigns. Between 2018 and 2021 24 campaigns were carried out at different hydrological regimes, where physical sediment samplings together with fixed and moving boat ADCP measurements were performed. The cross-sectional variability of SSC and its influence on the sediment load estimations were assessed based on the moving boat ADCP measurements, after calibrating the backscatter signal with more than 500 physical samples. Based on the results, we identified different cross-sectional patterns of the SSC which is apparently governed by: (i) the actual hydrological situation considering both the main river and the tributary, and (ii) the local river morphology. Based on our findings, we suggested a correction method that accounts for the above effects, using which the near-bank SSC can be reliably converted into total suspended sediment load. [ABSTRACT FROM AUTHOR]

Knowledge and management of hydraulic processes including flow pattern, sediment transport, and flood level prediction in natural rivers require proper understanding of interactions between flood flow and vegetation in floodplains. This study examined the flow structures and turbulence parameters in an asymmetric non-prismatic compound channel with different vegetation densities in divergent floodplain. Due to existence of vegetation, the bed shear stresses in the middle and end of the divergence floodplain decrease 78.5% and 86%, respectively. Also, the depth-averaged velocity in vegetated floodplain diminishing by about 60% and 69%. The results revealed that the production and dissipation of Reynolds shear stresses and the formed shear layer depend on the vortex shedding frequency formed behind each single rod and is very unstable. Finally, some equations were presented to estimate friction factor based on rod Reynolds number, calculate the frequency of the vortices generated behind the elements and the local drag coefficient. [ABSTRACT FROM AUTHOR]

Trapezoidal-shaped hydrographs are typical of anthropized rivers, as this form is generally associated with the release of water from hydropower dams. To investigate how such unnatural waves can affect bedload rate, preliminary flume experiments were performed in Krakow, Poland, looking at bedload transport rate, bed shear stress and bed morphology. In addition, close-range bed surface photogrammetry was used to investigate bed changes due to the passage of the flood wave. Three scenarios, having the same water volume but different wave magnitudes, were tested. The lowest wave showed almost no sediment transport and no visible changes in bed morphology, while higher waves changed the bed morphology, creating erosion and accumulation zones. The highest wave was characterized by an 8-shaped hysteresis of the bedload rate with a peak during the wave maximum. The lag time between the maximum bedload rate and the wave plateau was longer than expected due to zero-slope conditions. [ABSTRACT FROM AUTHOR]

One of the natural disasters caused by river meandering is riverbank erosion, which creates social, economic, and environmental problems in the riparian zone and serves as a source of increasing sedimentation levels in the river. Riverbank erosion and bank failure create a complex cyclical process, such as riverbank retreat, which cannot be easily measured and predicted by any model. The meandering flow along the Bhagirathi-Hooghly river has created riverbank erosion and riverbank retreat conditions in several areas, through which measuring bank stability and erosion is quite complex. As a result, the BSTEM model, integrating with HEC-RAS, has been used in this article to measure riverbank erosion and retreat accurately. Riverbank erosion and retreat data for 2019–2020 have been simulated based on data observed from 2016 to 2018 for accurate measurement. In addition, the total sediment yielded from the river bank has been calibrated and simulated with the help of sediment transport formulation in HEC-RAS, which indicates a gradual increase in river erosion at present (2019–2020). This model is expected to help formulate government policy on protecting riverbank erosion and river restoration in the future. [ABSTRACT FROM AUTHOR]