1,720,978 research outputs found
Sediment residence time distributions: theory and application from bed elevation measurements
No full text[1] Travel distance and residence time probability distributions are the key components of stochastic models for coarse sediment transport. Residence time for individual grains is difficult to measure, and residence time distributions appropriate to field and laboratory settings are typically inferred theoretically or from overall transport characteristics. However, bed elevation time series collected using sonar transducers and lidar can be translated into empirical residence time distributions at each elevation in the bed and for the entire bed thickness. Sediment residence time at a given depth can be conceptualized as a stochastic return time process on a finite interval. Overall sediment residence time is an average of residence times at all depths weighted by the likelihood of deposition at each depth. Theory and experiment show that when tracers are seeded on the bed surface, power law residence time will be observed until a timescale set by the bed thickness and bed fluctuation statistics. After this time, the long-time (global) residence time distribution will take exponential form. Crossover time is the time of transition from power law to exponential behavior. The crossover time in flume studies can be on the order of seconds to minutes, while that in rivers can be days to years
Measurement and validation for the twelve month particulate matter study Hong Kong
No full textReport prepared for Environmental Protection Department, Government of Hong Kon
A vector based 3D sediment entrainment model for X-ray computed tomography scanned riverbed grains
No full textA vector-based 3D rolling motion sediment entrainment model was developed with application to X-ray computed tomography (XCT) scanned riverbed grains. VectorEntrainment3D extracts grain characteristics and locates all grain-to-grain contact points from XCT scanned images of riverbed samples in an effort to estimate a threshold of entrainment critical shear stress for all surface grains in the sample. A vector-based 3D moment balance about a rotation axis is used to calculate a critical shear stress for each 'viable pair' of contact points for a single coarse surface grain, the smallest value of which is the entrainment threshold solution for that grain. An empirical cohesive force model is used to estimate the resistance force associated with coarse grain contact with a fine-grain matrix. Once a critical shear stress solution is found, three entrainment angles are calculated: the bearing and tilt angles describing the orientation of the grain's plane of rotation, which are determined by two contact points forming the axis of rotation; and the pivot angle describing the forward rotation of the grain, which lies within the plane of rotation
X-ray computed tomography reveals that grain protrusion controls entrainment shear stress for entrainment of fluvial gravels: Dataset
No full textThis is the dataset that accompanies a paper in Geology: Hodge RA, Voepel H, Leyland J, Sear DA, Ahmed S (2020). X-ray computed tomography reveals that grain protrusion controls entrainment shear stress for entrainment of fluvial gravels. Geology, 48(2), 149-153. The aim of this work was to understand how the properties of a sediment grain in a river bed affect the forces required to entrain that grain. This dataset presents the properties of 1055 sediment grains, which were meaured using CT scanning.</span
Modeling temporal trends in bedload transport in gravel-bed streams using hierarchical mixed-effects models
No full textIn this paper, we used a bedload transport data set collected at North Fork Caspar Creek, California, to examine temporal variation in sediment transport rate over a 7-year period. Using a hierarchical mixed-effects model, we examined across and within-event variation to determine whether the bedload–shear stress relation trends over time. The relation between bedload transport and shear stress was modeled using log(Qb) = a + B*log(T) + E, where a and B are constants and E is an error term. Depending on the length of observation, a and B can vary over several orders of magnitude, making modeling of transport based on flow challenging and highly inaccurate. We found a higher order yearly relation between bedload and shear stress, indicating systematic changes to the system over time. In the absence of significant additions to the system, a decreases roughly linearly over time, while B does not show any trend. From the systematic decline in a, we infer changes to sediment availability in the stream over time. Mixed-effects models have the potential to be a useful predictive tool in fluvial geomorphology, as they are more powerful at detecting trends in sediment transport rates than individual linear regressions
Displacement characteristics of coarse fluvial bed sediment
Get PDF[1] Previous work highlights the need for data collection to identify appropriate models for temporal evolution of tracer dispersal in rivers. Results of 64 gravel-bed field tracer experiments covering a wide range of flow and sediment supply regimes are compiled here to determine the probabilistic character of gravel transport. We focus on whether particle travel distances and waits are thin- or heavy-tailed. While heavy-tailed travel distance distributions are observed between successive monitoring events in different hydrological and sediment supply regimes, heavy-tailedness does not persist through total travel distance over multiple monitoring events, suggesting that individual monitoring events occur before particle travel distance exceeds the characteristic correlation length for the channel (such that particles that start in fast paths remain in fast paths and particles in slow paths remain in slow paths). After a large number of transport events, super-diffusive spreading was not observed at any of the gravel bed streams. Continuous-time tracking of x, y, z coordinates of tracers in natural streams is necessary to capture exact step and waiting time distributions
Development of a vector-based 3D grain entrainment model with application to X-ray computed tomography (XCT) scanned riverbed sediment
Get PDFSediment transport equations typically produce transport rates that are biased by orders of magnitude. A causal component of this inaccuracy is the inability to represent complex grain‐scale interactions controlling entrainment. Grain‐scale incipient motion has long been modelled using geometric relationships based on simplified particle geometry and two‐dimensional (2D) force or moment balances. However, this approach neglects many complexities of real grains, including grain shape, cohesion and the angle of entrainment relative to flow direction. To better represent this complexity, we develop the first vector‐based, fully three‐dimensional (3D) grain rotation entrainment model that can be used to resolve any entrainment formulation in 3D, and which also includes the effect of matrix cohesion. To apply this model we use X‐ray computed tomography to quantify the 3D structure of water‐worked river grains. We compare our 3D model results with those derived from application of a 2D entrainment model. We find that the 2D approach produces estimates of dimensionless critical shear stress ( urn:x-wiley:esp:media:esp4608:esp4608-math-0001) that are an order of magnitude lower than our 3D model. We demonstrate that it is more appropriate to use the c‐axis when calculating 2D projections, which increases values of urn:x-wiley:esp:media:esp4608:esp4608-math-0002 to more closely match our 3D estimates. The 3D model reveals that the main controls on critical shear stress in our samples are projection of grains, cohesive effects from a fine‐grained matrix, and bearing angle for the plane of rotation (the lateral angle of departure from downstream flow that, in part, defines the grain's direction of pivot about an axis formed by two contact points in 3D). The structural precision of our 3D model demonstrates sources of geometric error inherent in 2D models. By improving flow properties to better replicate local hydraulics in our 3D model, entrainment modelling of scanned riverbed grains has the potential for benchmarking 2D model enhancements
Improving predictions of critical shear stress in gravel bed rivers: Identifying the onset of sediment transport and quantifying sediment structure
Get PDFUnderstanding when gravel moves in river beds is essential for a range of different applications but is still surprisingly hard to predict. Here we consider how our ability to predict critical shear stress (τ c ) is being improved by recent advances in two areas: (1) identifying the onset of bedload transport; and (2) quantifying grain‐scale gravel bed structure. This paper addresses these areas through both an in‐depth review and a comparison of new datasets of gravel structure collected using three different methods. We focus on advances in these two areas because of the need to understand how the conditions for sediment entrainment vary spatially and temporally, and because spatial and temporal changes in grain‐scale structure are likely to be a major driver of changes in τ c . We use data collected from a small gravel‐bed stream using direct field‐based measurements, terrestrial laser scanning (TLS) and computed tomography (CT) scanning, which is the first time that these methods have been directly compared. Using each method, we measure structure‐relevant metrics including grain size distribution, grain protrusion and fine matrix content. We find that all three methods produce consistent measures of grain size, but that there is less agreement between measurements of grain protrusion and fine matrix content
Mapping seasonal human mobility across Africa using mobile phone location history and geospatial data
No full textSeasonal human mobility data are essential for understanding socioeconomic and environmental dynamics, yet much of Africa lacks comprehensive mobility datasets. Human movement, shaped by economic needs, family responsibilities, seasonal climatic variations, and displacements, is poorly documented in many regions due to limitations of traditional methods like censuses and surveys. This study addresses these gaps by leveraging the Google Aggregated Mobility Research Dataset (GAMRD) and a Bayesian spatiotemporal framework to estimate pre-pandemic monthly mobility flows at both national and regional scales across Africa for 2018–2019. We analysed 25 countries with complete GAMRD data and developed regional models to estimate mobility in 28 additional countries with sparse or missing records, filling critical data gaps. Key predictors, including GDP per capita, underweight children, infant mortality, environmental variables like stream runoff and evapotranspiration, and covariate interactions, revealed the complexity of mobility drivers. This approach provides robust estimates of seasonal mobility changes in data-limited areas, and offers a foundational understanding of African mobility dynamics, which highlights the value of innovative modelling and novel sources to bridge data gaps for supporting regional planning and policy-making
Drivers of Spatial Dispersion and Residence Time of Coarse Sediment in Gravel-Bed Rivers
No full textTransport of coarse sediment in gravel-bed streams alternates between mobile and immobile phases. Mobilized sediment disperses primarily in the streamwise and vertical directions. While travel times of sediment in the channel are brief, rest times between periods of mobilization can be relatively extensive. Both phases of transport are investigated with a focus on physical drivers and interactions between dispersive behavior and properties related to sediment, morphology and hydrology. This novel approach illustrates transport mechanisms to be either static or dynamic. Uniquely identified tracer stones are used in field and flume experiments to study dispersive characteristics of coarse sediment in gravel-bed channels. This study interrogates tracer data from previous flume experiments and three field studies, the Allt Dubhaig, Monachyle Burn and East Creek, to investigate dynamics of vertical mixing and streamwise travel distances with particle characteristics, morphologic features and flow conditions.Sorting on stone shape during vertical mixing is negligible while streamwise travel distance is significant after sufficient cumulative flooding durations. Sorting occurs dynamically on shape geometry where differences in axis ratios are prominent with significance order C/A>C/B>B/A. Sorting on stone size is static along vertical and dynamic in streamwise directions where sorting is ordered from large to small stones into the channel substrate and downstream. Speed and strength of linear dynamic response to sorting on stone shape and size is highly variable. Channels with less-developed morphology undergo complicated, dynamic vertical mixing patterns where flow has strong interaction with sediment and morphologic features. As channel morphology develops, influence on vertical mixing shifts from flow-channel interaction to morphologic features. Flood duration controls how far travel distances spread while channel energy controls how it is distributed along the channel. Stream power and vertical mixing have high short-term correlation that diminishes over time. Residence time distributions, which characterize the immobile phase of sediment transport, are easily computed from bed elevation time series, and have common distributional form. Travel distance is not correlated with burial depth. However, since residence time is related to vertical mixing and correlated with travel distance through virtual velocity, it may be a key factor linking streamwise and vertical dispersion
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