We calibrated an acoustic pipe microphone system to monitor bedload flux in a sandy, gravel-bed ephemeral channel. Ours is a first attempt to test the limit of an acoustic surrogate bedload system in a channel with a high content of sand. Calibrations varied in quality; significant data subsetting was required to achieve R² values >0.75. Several data quality issues had to be addressed: (1) apparent pulses, which occur when a sensor records an impulse from sediment impacting the surrounding substrate rather than directly impacting the sensor, were frequent, especially at higher signal amplifications. (2) The impact sensors were frequently covered by gravel sheets. This prompted the development of a cover detection protocol that rejected part of the impact sensor record when at least one sensor was partially or fully covered. (3) Because of the lack of sensor sensitivity to impacts of sand-sized particles, which was anticipated, and the considerable sand component of bedload in this channel, a grain size-limited bedload flux was estimated. This was accomplished by sampling the bedload captured by slot samplers and evaluating the variation of grain size with increasing flow strength. This considerably improved the results when compared to attempts at estimating the flux of the entire distribution of grain sizes. This calibration is a successful first attempt, though the impact sensors required several site-specific calibration steps. A universal set of equations using impact sensors to estimate bedload transport of fine-gravel with a large content of sand remains elusive. Notwithstanding, our study demonstrates the utility of impact sensor data, producing relatively low root mean square errors that are independent of measurements of flow strength (i.e. discharge). These tools will be particularly useful in settings that would benefit from new methodologies for estimating bedload transport in sand-rich gravel-bed rivers, such as the American desert Southwest.

Evidence of the effect of unsteady flow on bedload sediment transport is meagre, particularly in desert rivers, despite its scientific, environmental and engineering importance. Our study of the phenomenon was conducted in Nahal Eshtemoa, Israel, an ephemeral river located in a semi-arid area and subjected to flash floods. During four years, we monitored bedload transport and contemporaneous hydraulics, focusing on two intervals during which flow changed most rapidly: (i) the arrival of flood bores over dry river beds and (ii) the propagation of subsequent bores over flowing water. Monitoring involved deployment of plate microphones, video cameras, surface velocity radar and a 3D velocimeter, enabling synchronized and unique data acquisition at high temporal resolution. We hypothesized that turbulence would be considerably elevated during the arrival of a flood bore and that this would induce transient entrainment of bedload. Our results demonstrate that bedload is indeed transported by the bore front and ceases soon after the arrival of most bores, even though water depth continues to rise. Bores arriving on a dry river bed usually generate higher bedload fluxes than bores advancing over flowing water. Elevated values of shear stress, turbulent kinetic energy and water-surface slope occur as a bore impinges but then decrease. This is likely to be the explanation for high transient rates of bedload transport. Once the threshold depth previously determined as inducing continuous bedload motion is attained (≈40 cm), transport rates rise considerably relative to those associated with the bores.

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Hydraulic parameters, including bed shear stress, are challenging to calculate for flash floods. Applying theoretical equations to strongly unsteady flows requires comprehensive and accurate flow data that are difficult to collect for natural events. To empirically evaluate the extent to which simpler calculations can reasonably predict shear stresses in rapidly changing hydrographs, and to determine how bed shear stresses differ for hydraulic bores propagating over dry beds compared to shallow water, we conducted laboratory flume experiments on idealized short-duration flash floods with bores. We compared the Saint-Venant shallow water equation, which theoretically captures the depth-averaged momentum balance of gradually varying unsteady flow to eight simpler methods, with assumptions that are not met in these flows. The Saint-Venant method predicts higher shear stresses immediately after bore arrival, but all of the simpler methods are nonlinearly correlated with the Saint-Venant method even when flow is rapidly changing. While none of the methods we evaluated should strictly apply to rapid changes in depth and velocity of bores, the correlations we found between methods just after bore arrival suggest that, for applications where shear stresses must be calculated but data are insufficient to apply the full Saint-Venant equations, simpler methods may provide meaningful shear stress constraints. Compared to flood bores propagating over a dry bed, bores propagating over shallow flowing water had steeper water surfaces but resulted in significantly lower bed shear stresses immediately after bore arrival.

Bedload transport is a key process in fluvial morphodynamics, but difficult to measure. The advent of seismic monitoring techniques has provided an alternative to in-stream monitoring, which is often costly and cannot be utilized during large floods. Seismic monitoring is a method requiring several steps to convert seismic data into bedload flux data. State-of-the-art conversion approaches exploit physical models predicting the seismic signal generated by bedload transport. However, due to a lack of well-constrained validation data, the accuracy of the resulting inversions is unknown. We use field experiments to constrain a seismic bedload model and compare the results to high-quality independent bedload measurements. Constraining the Green's function (i.e., seismic ground properties) with an active seismic survey resulted in an average absolute difference between modeled and empirically measured seismic bedload power of 11 dB in the relevant frequency band. Using generically estimated Green's function parameters resulted in a difference of 20 dB, thus highlighting the importance of using actual field parameters. Water turbulence and grain hiding are unlikely to be the cause of differences between field observations and our analysis. Rather, they may be either due to the inverted model being particularly sensitive to the coarse tail of the grain-size distribution, which is least well constrained from field observations, or due to the seismic model underestimating effects of the largest grains.

The monitoring of bedload flux under flash flood conditions has been successfully achieved since 1992 using slot samplers in the semiarid Nahal Eshtemoa. In the present study, a surrogate bedload monitoring technique - the Japanese plate microphone - has been deployed and calibrated against data from the slot samplers. Since a slot sampler has a sensitivity threshold that becomes especially important when transport rates are low, different averaging periods should be considered for high and low fluxes. In order to overcome the deficiencies of time-based aggregation used hitherto, we have developed a new method involving mass aggregation and commensurably variable intervals, thereby enabling a more accurate analysis and optimizing the bedload sampler's capabilities. The data derived with this new method has then been utilized to calibrate the Japanese plate microphone. The Eshtemoa is an ephemeral gravel bed channel with a high proportion of fine gravel (< 0.02 m); for these conditions, acoustic sensors have not been calibrated as yet. Two multiple linear regression models incorporating the effect of median bedload grain size on pulse rate have been established to predict bedload flux and cumulative transported bedload mass. The coefficients in these models are statistically significant. Good predictions are obtained for bedload flux (adj. r² = 0.83) and for cumulative bedload mass (adj. r² = 0.98) during flood recession. Overall, the multiple linear regression models, used in conjunction with the mass aggregation method of estimating bedload flux, suggest that field calibration of acoustic devices is feasible under these conditions for ca. 90% of the duration of bedload transport. © 2020 John Wiley & Sons, Ltd.

Colloidal particles removal from water is a challenge in surface water treatment. Previously, we suggested an original technique for colloidal particles separation from water based on physical flow manipulation by an oscillating device. Laboratory experiments and 2D numerical simulation indicated that this technology enhances colloidal particles grouping and enables their rapid, simultaneous aggregation and sedimentation. The 2D model used in that study was unable to fully elucidate the grouping mechanism, settling pattern, or particle trajectories. Here, we extended the numerical simulation from 2D to 3D and examined the system’s distinctive flow field. The flow field was solved with computational fluid dynamics (CFD) simulations in the commercial ANSYS Fluent code and validated by dye injection experiments. The sedimentation patterns could nicely be explained by the computational results. This explanation was strengthened by two-dimensional population balance model simulations, which showed that particles aggregated in two zones trailing the paddle edges. Additionally, the results indicate significantly higher TKE values and faster upward vertical velocities at the higher oscillating frequency, which explains the different sedimentation patterns and removal efficiencies generated by the different oscillation frequencies. The use of 3D numerical simulations will help to better understand and further optimize this novel technology.

Colloid removal in water treatment plants is commonly done by a sequence of processes that includes coagulation, flocculation, sedimentation, and filtration. The current study presents an innovative technique, termed grouping, for the removal of these suspended particles based on physical flow manipulation, which causes the particles to aggregate. Previous results showed that gentle oscillation in a cylindrical container facilitates simultaneous flocculation and sedimentation in the same reactor over shorter periods of time than are possible using the conventional treatment approach. This finding may confer marked improvements on the processes used today by enabling the use of both smaller reactors and less energy. Based on the findings with the cylindrical vessel, here the grouping technique is further examined in a rectangular container and over a range of different initial turbidities. The results indicate that the removal efficiency is higher in the rectangular container under the different initial turbidities tested. In addition, the removal efficiency was shown to remain robust with the decreases in initial turbidity and alum concentrations that occur during treatment. The positive results of our previous study taken together with this finding hint at the strong potential of the grouping technique to improve common flocculation processes.

Rivers are the fluvial conveyor belts routing sediment across the landscape. While there are proper techniques for continuous estimates of the flux of suspended solids, constraining bedload flux is much more challenging, typically involving extensive measurement infrastructure or labor-intensive manual measurements. Seismometers are potentially valuable alternatives to in-stream devices, delivering continuous data with high temporal resolution on the average behavior of a reach. Two models exist to predict the seismic spectra generated by river turbulence and bedload flux. However, these models require estimating a large number of parameters and the spectra usually overlap significantly, which hinders straightforward inversion. We provide three functions contained in the R package “eseis” that allow generic modeling of hydraulic and bedload transport dynamics from seismic data using these models. The underlying Monte Carlo approach creates lookup tables of potential spectra, which are compared against the empirical spectra to identify the best fitting solutions. The method is validated against synthetic data sets and independently measured metrics from the Nahal Eshtemoa, Israel, a flash flood-dominated ephemeral gravel bed river. Our approach reproduces the synthetic time series with average absolute deviations of 0.01–0.04 m (water depth, ranging between 0 and 1 m) and 0.00–0.04 kg/sm (bedload flux, ranging between 0 and 4 kg/sm). The example flash flood water depths and bedload fluxes are reproduced with respective average deviations of 0.10 m and 0.02 kg/sm. Our approach thus provides generic, testable, and reproducible routines for a quantitative description of key metrics, hard to collect by other techniques in a continuous and representative manner.

One of the major challenge in water treatment is the removal of mineral colloids of sub-micron to micron size that, virtually unaffected by gravity, cannot be easily settled out of solution. To aid in the removal of these particles, the coagulation/flocculation process is typically used, which involves the addition of chemicals to neutralize the repulsive electrical forces of the colloids and then mixing to enhance particle aggregation and promote the formation of flocs. The current study proposes an innovative technique for colloid removal based on physical flow manipulation by an oscillating device whose action causes intermittent velocity gradients over time, space and direction. This unique manipulation causes the suspended particles to aggregate and rearrange in separate groups that are amenable to sedimentation. The proposed technique was tested under various operational conditions, including oscillation frequencies, alum doses and with/without rapid mixing. In addition, it was compared to the traditional coagulation/flocculation process in the treatment of similar suspensions. The results indicate that gentle oscillation can promote simultaneous flocculation and sedimentation in the same reactor over short periods of time. This technique, whose implementation can result in reductions to reactor sizes and process times, has a strong potential to improve conventional processes.

Bedload flux under steady flow conditions is calculated by a multitude of available methods and equations. Yet, very little is known about the effect of very unsteady flows, such as flash floods and specifically bores, on bedload flux. The unpredictable nature of the floods together with many logistic difficulties and safety issues in monitoring explain this gap in knowledge. Global climate change may increase flood event occurrence, making their understanding even more crucial. The methodology of our study is based on automatically monitoring bedload flux (Reid slot samplers). Automation allowed high frequency monitoring of hydraulic parameters and bedload flux. Added novelty includes pipe and plate microphones for capturing acoustic signals of bedload sediments and 3-D velocimetry for characterizing turbulence. Alerting sensors and cellular data transmission enabled onsite presence upon bore arrival. Calibration between the acoustic indirect sensors and the direct slot samplers allows determination of bedload flux at a frequency of 1 Hz. Analyses of flood events indicate an increase in turbulent kinetic energy, instantaneous vertical velocities, shear stress and bedload flux during the rising limb within the first two minutes after bore arrival. This has implications for the likely destabilization of the channel bed and for bedload transport after passage of the bore and during subsequent, less unsteady flows.