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Accurate measurement of bedload is challenging, considering its spatial and temporal variability. Various indirect acoustic techniques are often used for estimating the bedload rate and total bedload mass. Estimating the grain size distribution for a bedload event of relatively short duration, taking the smaller bedload particles into account, is difficult. In the current study, an impact plate with two sensors, namely, an accelerometer and a geophone, is tested in a laboratory flume. Available bedload grains are sorted into different grain size classes, and two sets of experiments are conducted. Single-grain/multigrain particles and mixed-grain particles are considered in the single-class and multiclass experiments, respectively. Three different grain mixtures with variable fineness are fed to the plate in the mixed-grain experiment. The present setup can detect bedload grains from 2.36 to about 150 mm, which is an improvement over other indirect methods. A hybrid analysis methodology to predict the grain size distribution using signals from both sensors is developed. The grain size distributions (GSDs) are estimated with a maximum deviation of 22%, which is expected to improve further with data from longer bedload events. [ABSTRACT FROM AUTHOR]

Riverbeds often fine downstream, with a gravel‐bedded reach, a relatively abrupt gravel‐sand transition (GST), and a sand‐bedded reach. Underlying this behavior, bed grain size distributions are often bimodal, with a relative paucity (gap) around the range 1–5 mm. There is no general morphodynamic model capable of producing the grain size gap and gravel‐sand transition autogenically from a unimodal sediment supply. Here we use a one‐dimensional morphodynamic model including size‐specific bedload and suspended load transport, to show that bimodality readily evolves autogenically even under unimodal sediment feed. A GST forms when we include a floodplain width that abruptly increases at some point. Upstream of the transition, non‐gap gravel ceases to move and gap sediment is preferentially transported. At the transition, non‐gap sand rapidly deposits from suspension, enhancing gap sediment mobility and diluting its presence on the bed. Plain Language Summary: The bed surface layer of many rivers is a mixture of sand and gravel. This mixture is described by the probability distribution of grain sizes, and in particular by the median size. Consider the long profile of such a river. Surface median size commonly becomes finer downstream, but often changes abruptly from a value above 5 mm to a value below 1 mm over a short reach. The range 1–5 mm is termed "gap sediment." Here we explain how this abrupt change evolves, even when there is no deficit of gap sediment supplied to the reach, and even though particle abrasion is not included. The grain size distribution autogenically develops two peaks, one in the sand range and one in the gravel range above 5 mm. When abrupt floodplain widening is included, the gravel peak is stronger in the upper reach and the sand peak is stronger in the lower reach, leading to a relatively abrupt gravel‐sand transition. Gap sediment can be diluted both upstream and downstream by a combination of effects due to bedload and suspended load, so that it dominates nowhere in the grain size distribution. Key Points: Numerical simulations show that bed bimodality evolves autogenically, even with unimodal sediment feed and no abrasionAbrupt floodplain widening can lead to the formation of a distinct gravel‐sand transitionThe behavior can be explained by preferential mobility of 1–5 mm sediment over a sand bed combined with fallout of sand from suspension [ABSTRACT FROM AUTHOR]

Gravel replenishment is one existing solution for restoring riverbeds below dams. Prediction of erosion processes is crucial for river management planning of efficient replenishment. This study investigates the capacity of a large-scale, two-dimensional morphodynamic model to reproduce berm erosion and sediment wave propagation. The model enables quantification of the efficiency of several management scenarios according to berm geometry, location and sediment supply condition (dam closed or not during floods). Results show that replenishment efficiency is strongly dependent on the berm geometry and sediment supply. Berms should be located as close as possible to the low-flow channel and be as long as possible. Desynchronization between hydrographs and sedigraphs could be responsible for propagating sediment deficit which reduces the efficiency of replenishment. This model is a powerful management tool for the design of replenishment operations and the main conclusions of this work could be extended to other sites. [ABSTRACT FROM AUTHOR]

Recent theoretical models and field observations suggest that fluvial bedload flux can be estimated from seismic energy measured within appropriate frequency bands. We present an application of the Tsai et al. (2012, https://doi.org/10.1029/2011gl050255) bedload seismic model to an ephemeral channel located in the semi‐arid southwestern US and incorporate modifications to better estimate bedload flux in this environment. To test the model, we collected streambank seismic signals and directly measured bedload flux during four flash‐floods. Bedload predictions calculated by inversion from the Tsai model underestimated bedload flux observations by one‐to‐two orders of magnitude at low stages. However, model predictions were better for moderate flow depths (>50 cm), where saltation is expected to dominate bedload transport. We explored three differences between the model assumptions and our field conditions: (a) rolling and sliding particles have different impact frequencies than saltating particles; (b) the velocity and angle of impact of rolling particles onto the riverbed differ; and (c) the fine‐grained alluvial character of this and similar riverbeds leads to inelastic impacts, as opposed to the originally conceptualized elastic impacts onto rigid bedrock. We modified the original model to assume inelastic bed impacts and to incorporate rolling and sliding by adjusting the statistical distributions of bedload impact frequency, velocity, and angle. Our modified "multiple‐transport‐mode bedload seismic model" decreased error relative to observations to less than one order of magnitude across all measured flow conditions. Further investigations in other environmental settings are required to demonstrate the robustness and general applicability of the model. Plain Language Summary: The conveyance of sediments in rivers, especially of coarse‐grained sediment on the riverbed, is a basic geomorphic mechanism influencing short‐term river ecology, management, and engineering as well as long‐term landscape evolution. To better predict bedload transport rates, researchers have used seismic sensors to record ground vibration due to the impacts of bedload particles on the riverbed. We revised a physics‐based model developed by Tsai et al. (2012, https://doi.org/10.1029/2011gl050255) to estimate bedload sediment transport in an ephemeral channel in the semi‐arid southwestern US. To test the model, we collected nearby seismic signals during flash floods and simultaneously monitored water depth and bedload transport at one‐minute intervals. We modified the original model to better represent alluvial rivers by adding a representation of rolling and sliding particles to the hopping particles already considered in the physics of seismic waves generated by bedload transport. Our modified "multi‐mode bedload seismic model" yields a better result compared to the original Tsai et al. (2012, https://doi.org/10.1029/2011gl050255) model in our test river. The modified model is not only applicable for the ephemeral channels on which this study is focused but also is potentially applicable to a wide range of river conditions in different environmental settings. Key Points: The Tsai et al. (2012, https://doi.org/10.1029/2011gl050255) model underestimates bedload flux at low water depth by 1–2 orders of magnitude in an alluvial channelWe modified the original model to incorporate rolling and sliding by adjusting bedload impact frequency, velocity, and angleThe modified model decreases flux error relative to observations to less than one order of magnitude across all measured water depths [ABSTRACT FROM AUTHOR]

Bedload transport is a natural process that strongly affects the Earth's surface system. An important component of quantifying bedload transport flux and establishing early warning systems is the identification of the onset of bedload motion. Bedload transport can be monitored with high temporal resolution using passive acoustic methods, for example, hydrophones. Yet, an efficient method for identifying the onset of bedload transport from long‐term continuous acoustic data is still lacking. Benford's Law defines a probability distribution of the first‐digit of data sets and has been used to identify anomalies. Here, we apply Benford's law to continuous acoustic recordings from Baiyang hydrometric station, a tributary of Liwu River, Taroko National Park, Taiwan at the frequency of 32 kHz from stationary hydrophones deployed for 3 years since 2019. We construct a workflow to parse sound combinations of bedload transportation and analyze them in the context of hydrometric sensing constraining the onset, and recession of bedload transport. We identified three separate sound classes in the data related to the noise produced by the motion of pebbles, water flow, and air. We identify two bedload transport events that lasted 17 and 45 hr, respectively, covering about 0.35% of the total recorded time. The workflow could be transferred to other different catchments, events, or data sets. Due to the influence of instrument and background noise on the regularity of the residuals of the first‐digit, we recommend identifying the first‐digit distribution of the background noise and ruling it out before implementing this workflow. Plain Language Summary: Long‐term, high‐frequency monitoring of Earth surface processes brings huge data sets that can be of high quality. Benford's Law defines the specific probability distribution of the first‐digit of the data sets and has been used to identify anomalies and high‐energy events. We provide a workflow for applying Benford's Law to identify the onset of the motion of coarse sediment along the river bed at a time resolution of seconds. Since Benford's Law has demonstrated usefulness in acoustic amplitude analysis in this study, it could serve as a tool for identifying anomalous events in any kind of real‐time data series, which could be beneficial for generating event samples for machine learning applications. Key Points: Long‐term, high‐frequency acoustic monitoring constitutes huge‐volume data sets with a low signal‐to‐noise ratioThe distinct first‐digit distribution between signal and noise can used to filter out 99% of background noise from acoustic recordingsWe applied the method to a three‐year‐long acoustic data set in Baiyang, identifying two bedload transportation events [ABSTRACT FROM AUTHOR]

Flash floods in ephemeral streams are rare, short and difficult to forecast and thus to monitor. During these events, bedload transport reaches very high rates and most sediment transport occurs within a limited number of hours during the course of a year. Because monitoring of bedload in ephemeral rivers is challenging, here we present the results of a series of flume experiments designed to simulate short, flashy floods. Since most flume experiments usually involve single events, here we add to existing evidence by testing the effects of sequences of multiple floods in rapid succession. The flume is 10 m long, 0.3 m wide and 0.5 m deep. Two bed sediment mixtures (well sorted and poorly sorted) with similar median grain size but a different standard deviation were used. Bedload was monitored continuously during each hydrograph, but no sediment was fed. The flume experiments used six triangular hydrographs with peak flows ranging from 0.0147 to 0.02 m3 s − 1 and durations ranging from 150 to 400 s. Results indicate that the sediment transport rate decreases progressively from the first to the third hydrograph, and that this pattern is consistent for all permutations of peak discharge and flood duration. In all of the runs, the sediment transport rate at a specified flow was higher during the rising limb than the falling limb of the hydrograph, indicating clockwise hysteresis. Furthermore, in the subsequent repetitions of the same hydrograph, the degree of hysteresis generally diminishes in magnitude from the first to the last repetition for all the experiments, irrespective of their magnitude and duration. [ABSTRACT FROM AUTHOR]

River channels, riparian and floodplain forms and dynamics are all influenced strongly by biological processes. However, the influence of macroinvertebrates on entrainment and transport of river sediments remains poorly understood. We use an energy‐based approach to explore the capacity of benthic animals to move surficial, gravel‐bed particles in field and laboratory settings and use the results to assess the relative significance of biological and physical benthic processes. Our results showed that in 11 British gravel‐bed rivers, the maximum energy content (i.e., calorific content) of macroinvertebrate communities generally matched the flow energy associated with median discharges and, at multiple sites, exceeded that of the 10‐year return interval flood. A series of laboratory experiments used to estimate the minimum energy expended by signal crayfish (Pacifastacus leniusculus) when performing geomorphic work established that crayfish move gravel particles at energy levels below that expected of the flow, complicating direct comparisons of the capacity for macroinvertebrates and fluvial flows to influence bed mobility. Our findings suggest that the influence of macroinvertebrate communities in either promoting or suppressing, the mobilisation of the bed may be large compared to equivalent values of fluvial energy. Based on these findings, we conclude that in the gravel‐bed rivers studied, the macroinvertebrate community's potential to perform geomorphic work matches or exceeds the stream power during most of the year. Although our study examined biological and fluvial energy systems separately, it is important to recognise that in nature, these systems are highly interactive. It follows that utilising the energy framework presented in this paper could lead to rapid advances in both fluvial biogeomorphology and river management and restoration. [ABSTRACT FROM AUTHOR]

Bedload transport can fluctuate considerably over relatively short periods of time and for a given quasi‐constant flow rate. What are the implications of replacing the fluctuating signal with a smoothed signal when calculating bedload transport using averaged values, as is common practice? This question was investigated with the BedloadR code, which allows 1D bedload calculation as well as Monte Carlo simulations using a new data set collected in the Severaisse River (French Ecrins massif). Four bedload equations (Camenen & Larson, 2005, https://doi.org/10.1016/j.ecss.2004.10.019; Meyer‐Peter & Mueller, 1948; Parker, 1990, https://doi.org/10.1080/00221689009499058; Recking, 2013a, https://doi.org/10.1061/(asce)hy.1943‐7900.0000653) were selected for their performance relative to the measured bedload (except for and Meyer‐Peter and Mueller) and because each equation has a different mathematical form and degree of nonlinearity. They were used in a Monte Carlo approach, with input probability distributions fitted to the measured river width, slope, bed grain‐size distribution, and to the associated (computed) Shields stress. The results show that accounting for natural variability in the calculation reproduces bedload fluctuations well. But overall, when calculating the bedload volume transported by a flow event, accounting for variability systematically leads to higher estimated volumes (of the order of 20%) than those obtained with a deterministic approach using average input parameters. This is a direct consequence of the nonlinearity of the equations. Plain Language Summary: Transport of bedload in a river, that is, sediment in motion that stays close to the riverbed, fluctuates a lot over relatively short time periods for a given near‐constant discharge. In this paper, we try to reproduce this natural process. To do this, we use a protocol that involves running a bedload equation several thousand times, slightly and randomly modifying the input data with each run. The results show that by taking into account the natural variability of sediment size or channel geometry, we obtain realistic modeling of bedload transport fluctuations. Key Points: A new field data set is used for computing bedload in a Monte Carlo approachBedload modeling accounting for input variability reproduces bedload fluctuation wellBecause of non‐linearity, volumes computed with input variability are 20% higher [ABSTRACT FROM AUTHOR]

Abstract Riverbeds often fine downstream, with a gravel‐bedded reach, a relatively abrupt gravel‐sand transition (GST), and a sand‐bedded reach. Underlying this behavior, bed grain size distributions are often bimodal, with a relative paucity (gap) around the range 1–5 mm. There is no general morphodynamic model capable of producing the grain size gap and gravel‐sand transition autogenically from a unimodal sediment supply. Here we use a one‐dimensional morphodynamic model including size‐specific bedload and suspended load transport, to show that bimodality readily evolves autogenically even under unimodal sediment feed. A GST forms when we include a floodplain width that abruptly increases at some point. Upstream of the transition, non‐gap gravel ceases to move and gap sediment is preferentially transported. At the transition, non‐gap sand rapidly deposits from suspension, enhancing gap sediment mobility and diluting its presence on the bed.

This paper presents a review of cross-shore sediment transport for non-cohesive sediments in the coastal zone. The principles of sediment incipient motion are introduced. Formulations for the estimation of bedload transport are presented, for currents and combined waves and current flows. A method to consider the effect of sediment heterogeneity on transport, using the hiding–exposure coefficient and hindrance factor, is depicted. Total transport resulting from bedload and transport by suspension is also addressed. New research is encouraged to fill the knowledge gap on this topic. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract Bedload transport is a natural process that strongly affects the Earth's surface system. An important component of quantifying bedload transport flux and establishing early warning systems is the identification of the onset of bedload motion. Bedload transport can be monitored with high temporal resolution using passive acoustic methods, for example, hydrophones. Yet, an efficient method for identifying the onset of bedload transport from long‐term continuous acoustic data is still lacking. Benford's Law defines a probability distribution of the first‐digit of data sets and has been used to identify anomalies. Here, we apply Benford's law to continuous acoustic recordings from Baiyang hydrometric station, a tributary of Liwu River, Taroko National Park, Taiwan at the frequency of 32 kHz from stationary hydrophones deployed for 3 years since 2019. We construct a workflow to parse sound combinations of bedload transportation and analyze them in the context of hydrometric sensing constraining the onset, and recession of bedload transport. We identified three separate sound classes in the data related to the noise produced by the motion of pebbles, water flow, and air. We identify two bedload transport events that lasted 17 and 45 hr, respectively, covering about 0.35% of the total recorded time. The workflow could be transferred to other different catchments, events, or data sets. Due to the influence of instrument and background noise on the regularity of the residuals of the first‐digit, we recommend identifying the first‐digit distribution of the background noise and ruling it out before implementing this workflow.

There is abundant evidence from fluvial landforms and deposits that Mars had rivers that actively transported sediment and shaped its surface. Sediment transport equations are playing a key role in quantifying river processes from these observations, which continue to increase in quality and quantity. In this study, we review sediment transport equations developed on Earth and isolate the effect of gravity for the case of an alluvial channel. We compare 33 formulas used to calculate the sediment transport rate, under transport‐limited conditions, for grain sizes that range from silt to boulders and a lognormal sediment distribution. Results indicate that for a given discharge, channel morphology and grain size, the lower gravity on Mars compared to Earth results in: (a) larger grains mobilized on Mars and transported in suspension, and (b) larger suspended sediment transport rates on Mars and therefore larger total transport rates. Importantly, the effect of gravity is different for bed load and suspended load, with nonlinearity at the bed load‐suspended load transition zone. Therefore, typical total‐load transport relations that do not distinguish between bedload and suspended load are not appropriate for other planets as they simplify the effect of gravity. Gravity‐driven differences in fluvial sediment transport should produce differences in sediment sorting, morphology and stratigraphy between Earth and Mars. Additionally, our results show how Earth‐derived fluvial sediment transport theory can be applied beyond Mars to other planets and moons. Plain Language Summary: There is much evidence that Mars had rivers that actively transported sediment and shaped its surface. Preserved ancient landscapes altered by water provide valuable insights into past processes on the planet's surface and the presence of water. To better understand these landforms, we rely on knowledge gained from systems on Earth. However, is it fair to do so when the gravity on Mars is much lower? How does gravity affect sediment transport and the landforms created by water? In this study, we isolate the effect of gravity on sediment transport by water with an analytical river model. We used 32 sediment transport formulas to compare sediment transport rates on Earth and Mars for the same conditions except gravity. The results show that larger grains are picked up by the flow on Mars and the transport rate of sediment traveling in suspension is higher, and therefore total transport as well. Because grains transported near and on the bed are less affected than the grains in suspension, the effect of gravity varies with the way of transport and hence grain size. Therefore, gravity‐driven differences in sediment transport by water should produce differences in sediment sorting, morphology and stratigraphy between Earth and Mars. Key Points: Fluvial sediment transport rates are higher on Mars than on Earth for the same discharge and channel geometryGravity affects suspended sediment transport more than bed load transport and could hence lead to differences in morphology and stratigraphyTotal load sediment transport equations should be avoided on other planets and moons due to simplified attribution of gravity [ABSTRACT FROM AUTHOR]

Predicting transport rates is difficult for the morphological features of marine, river, and coastal ecosystems. To design a model bed load sediment transport rate along with the surface layer, a mesh-based numerical method is used, and for the sediment transport the governing equations are employed and depth-averaged is used to create open channel flow and in three-dimensional horizontal space the evaluation is performed. By utilizing the governing equations, the open channel flow discretization and the numerical hydrodynamic model of sediment transport rate are calculated, and in the flow channel by using the solution method the settling velocity is determined. The complex issues involved nonlinear equations for the numerical modelling with solution methodology. The chicken swarm optimization algorithm is revealed by multi-objective metaheuristics optimization, and a better outcome is acquired by optimization. Finally, if polygonal mesh modelling is used in the diversion flow channel and curved bend channel, several experimental models were employed in the model experiments. A numerical measured and improved model is used to estimate the results in comparison, and the optimally developed model forecast rates with accuracy. In some open-channel flows such as reservoirs and rivers, the struggling flow and bed load sediment transport were dealt with in this model. Based on the results obtained, the proposed technique demonstrates significant improvements in both accuracy and prediction performance compared to the existing techniques. The proposed technique achieves an accuracy of 96.87%, outperforming the BCNN technique with an accuracy of 89.77% and the H-ANN-FA technique with an accuracy of 84.65%. Moreover, the proposed technique exhibits a lower RMSE value of 0.12, indicating a substantial reduction in the average deviation between predicted and observed values. Based on the NSE and R2 results, the proposed technique demonstrates remarkable improvements in prediction accuracy compared to the other techniques. The proposed technique achieves an NSE value of 0.998 and R2 value of 0.99, compared to the existing technique with an improvement of 46.47% and 11.24%. [ABSTRACT FROM AUTHOR]

Flash floods in ephemeral streams are rare, short and difficult to forecast and thus to monitor. During these events, bedload transport reaches very high rates and most sediment transport occurs within a limited number of hours during the course of a year. Because monitoring of bedload in ephemeral rivers is challenging, here we present the results of a series of flume experiments designed to simulate short, flashy floods. Since most flume experiments usually involve single events, here we add to existing evidence by testing the effects of sequences of multiple floods in rapid succession. The flume is 10 m long, 0.3 m wide and 0.5 m deep. Two bed sediment mixtures (well sorted and poorly sorted) with similar median grain size but a different standard deviation were used. Bedload was monitored continuously during each hydrograph, but no sediment was fed. The flume experiments used six triangular hydrographs with peak flows ranging from 0.0147 to 0.02 m3s−1 and durations ranging from 150 to 400 s. Results indicate that the sediment transport rate decreases progressively from the first to the third hydrograph, and that this pattern is consistent for all permutations of peak discharge and flood duration. In all of the runs, the sediment transport rate at a specified flow was higher during the rising limb than the falling limb of the hydrograph, indicating clockwise hysteresis. Furthermore, in the subsequent repetitions of the same hydrograph, the degree of hysteresis generally diminishes in magnitude from the first to the last repetition for all the experiments, irrespective of their magnitude and duration.

This paper presents a review of cross-shore sediment transport for non-cohesive sediments in the coastal zone. The principles of sediment incipient motion are introduced. Formulations for the estimation of bedload transport are presented, for currents and combined waves and current flows. A method to consider the effect of sediment heterogeneity on transport, using the hiding–exposure coefficient and hindrance factor, is depicted. Total transport resulting from bedload and transport by suspension is also addressed. New research is encouraged to fill the knowledge gap on this topic.

An accurate assessment of sediment transport can assist land and resource managers in any region. The primary objective of this study was to develop a distributed hydrological model for calculating rainfall-runoff coupled with sediment transport to provide a practical method for estimating sediment transport in western Heilongjiang Province, China. The Alun River Basin, which has typical meteorological and hydrological characteristics of western Heilongjiang Province, was chosen as the study area. A sediment transport calculation module was developed based on physically based formulas for the suspended load and bedload, which was coupled with a numerical model of the physical distributed rainfall-runoff process. The model’s ability was validated by comparing the sediment sampling survey results of the particle size group distribution (PSGD) in the flow and the corresponding value of the model calculation results for a control case. The root mean square error ( RMSE ) and the mean absolute error ( MAE ) were mostly 15%. The results provide a basis for the assessment of sediment transport and the development of a numerical platform for modeling hydrological processes coupled with land surface processes in western Heilongjiang Province, China.

River sediment budgets are prepared globally, under different conditions and requirements. This paper proposes a general methodology for sediment budgeting – the River Sediment Budget Approach (RSBA), to demonstrate the challenges and opportunities involved in establishing a sediment budget. The methodological approach focuses on the bedload, suspended sediment load as well as changes in the river bed and morphology. Four approaches are provided for sediment budgeting, which can be used individually or in combination and are selected based on the time scale and data availability. If measurement data is available or can still be undertaken, a (i) field-based approach is selected. Specifically, the morphological changes or data required for formulas can be gathered using a (ii) GIS-based approach. When calculations are carried out without measured data, a (iii) formula-based approach is pursued. Due to the numerous budgets already conducted and sediment data already measured, an approach dependent on (iv) literature data and estimations can also be considered. Due to the complexity of sediment dynamics in rivers, strict rules are not beneficial in sediment budgeting and, to avoid misinterpretation, it is essential to validate the results. • A budget approach (RSBA) with a hierarchical decision matrix. • Sediment budgets as a methodology to budget suspended sediment and bedload at different temporal and spatial scales. • Opportunities for sediment budgeting with weak datasets. [ABSTRACT FROM AUTHOR]

• Lateral sediment flux from hillslopes is directly connected to the curve number. • The curve number summarized the resistance from the soil-group complex. • The lateral sedimentologic connectivity was well represented by the curve number. • The soil-cover complex in a watershed is closely related to watershed erodibility. The flux of suspended sediment and bedload in a watershed is closely linked to the resistance of soil, known as erodibility. However, the relation between the resistance generated by soil to sediment transport from the hillslope to the river flow is still a challenge. Typically, the bedload flux is related to the shear stress of the main channel. However, the link between lateral sediment flux from hillslopes to suspended sediment flux of the main channel and the relation between bedload and suspended sediment flux to soil erodibility need to be developed. For three Brazilian watersheds, suspended sediment and bedload transport, soils, and hydrological data were obtained to determine watershed soil erodibility. The landscape connectivity expressed by hydrological-sediment connectivity was applied to determine the lateral sediment transport to the primary watershed channel. The flow resistance and lateral suspended sediment discharge were represented by the curve number, which summarized the resistance from the soil-group complex leading to soil erodibility. The curve number addressed the lateral flow and suspended sediment transport to represent the lateral connectivity on the landscape. Sediment transport (sand and suspended sediment) from hillslopes was added to the bedload transport along the longitudinal axis of the watershed, and the watershed soil erodibility (K W) was, thus, obtained for each of the three evaluated watersheds. [ABSTRACT FROM AUTHOR]