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9.5: Sediment Transport - Geosciences

9.5: Sediment Transport - Geosciences


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The Bernoulli Effect

A higher pressure above grains than below them can “pull” grains off the bed into the flow. The pressure difference comes from a difference in water (or air) speed above and below the grain. As water flows faster, there are fewer collisions between the water and the surface it flows over than there are between standing water and a similar surface. Pressure is due to collisions. Thus, fewer collisions means lower pressure. The upstream side of a grain experiences the most collisions because the water is flowing into it. The downstream side experiences the fewest collisions, and the sides of the grain experience fewer collisions where flow is faster and more where the flow is slower. The net result is a low pressure zone above and slightly downstream of a grain. If the force exerted by this pressure difference is larger than the force of gravity, the grain will lift off the bed. This lift due to the pressure difference is the Bernouli Effect.

Which Grains Move?

Which grains get entrained in the flow depends on their size and density (how much they weigh) because that determines the force of gravity holding them down. It also depends on the shape of the grain. A grain with a large area to experience the low pressure (like a plate) will be more susceptible to being picked up than a round grain of the same mass (although flat grains may see a smaller flow difference from top to bottom if the boundary layer is thick, and thus flat grains may experience a lower Bernoulli Effect per unit area.) The other thing that really matters is the position of a grain relative to surrounding grains. If a grain is sandwiched between larger grains, i.e. in their flow shadows, it will not experience as big a pressure difference as if it is on a flat surface. Also, if a grain is upstream of a big grain, it has to be lifted over it, so it has to experience enough force to lift it high into the flow. Thus, things can be complicated if you are trying to predict the behavior of a specific grain. However, experiments and theory provide statistically meaningful predictions for how grains behave on average.

Bedload and Suspended Load Transport

Two things can happen once a grain is lifted into the flow: 1) it can fall back down or 2) it can stay there. It depends on how quickly the grain settles out versus how turbulent the water is (back to Re...). Bedload refers to the grains that are transported along the sedimentary bed, e.g. grains that are rolling and being lifted off the bed, but they fall back quickly. The name bedload comes from the fact that the grains moving by traction and saltation never get too far from the bed and “load” is an engineering term for the amount of sediment transported by a river. Rolling grains are in traction. Grains that are pulled off the bed with the Bernoulli effect but are large enough that gravity causes them to fall “quickly” back to the bed are said to be saltating. (The word saltating refers to the way salt from a salt shaker bounces when it is shaken onto a hard surface. The word is derived from a Latin word meaning dance.) Bedload grains are the ones that form sedimentary structures in flowing water.

Here is a playlist with movies related to sediment transport: Sumnerd’s Sed Transport Playlist

Suspended sediment consists of grains that are light or small enough that they do not settle out of the water; the turbulent bursts of water keep them in the flow (see brown water in the photo). The more turbulence in the water, e.g. the higher the Reynolds number, the larger the grains in suspension will be. The upward motions of turbulent flow are faster than the rate these grains settle, so gravity is counteracted and they stay “floating” in the water even though they are denser than the water. Very small grains do not settle out of flows unless the Reynolds number is low, which means that the flows need to be either have a very low flow speed or be very shallow.

YouTube video of white clay in a turbulent flow in a flume: http://tinyurl.com/78kg3z The pulsing in the flow is (probably) due to the pump that is making the water flow.

The video below shows both suspended and bedload transport. The water is cloudy due to suspended grains, and pebbles can be seen rolling on the bed.

Hjulstrom Diagram

The flows that are required to pick up grains of certain sizes have been extensively studied in experiments and the results are plotted in Hjulstrom (or Shields) diagrams. Hjulstrom diagrams show grain entrainment on a plot of log grain size versus log flow speed. This diagram shows the areas where grains of different sizes are left on the bed, where they get moved sometimes (this is the gray zone), and where they get lifted up often and eroded away. Note that larger grains require higher flows - in general. The water speed that is required to transport a grain is call the critical velocity. This is important. If there is gravel in a sedimentary deposit, you can say that the water flow had to be above the critical threshold for it to get there! That might require a fast flowing river or strong wave action, and thus, a large part of narrowing down the depositional environment has already been done!

Here is the Hjulstrom Diagram we will use (or the one in the Nichols text, which has additional information on it):

If the flow speed and grain size are in the field labeled "Deposition", grains of this size will not be lifted into the flow, and if they are already moving, they will be deposited onto the sediment surface. If the flow speed and grain size are in the field labeled "Transport", grains in motion are likely to continue in motion. A few grains will be deposited and a few grains will be eroded, but there will not be a significant change in the number of grains that move. If the flow speed and grain size are in the field labeled "Erosion", more grains will be transported than deposited until the flow is transporting as many grains as it can, e.g. it is at its "carrying capacity" for sediment.

The boundaries for deposition, transport and erosion shift with changing flow depth. For example, deeper flows can move larger grains at the same flow velocity because they are more turbulent:

[Re = dfrac{l imes u imes ho}{µ} ag{3.1}]

and (l) is larger. This is because deeper flows can have larger variations in flow speed and the laminar flow layers are very thin. They can have bursts of very rapid flow relative to the average flow speed and these bursts can pick up larger grains.

Caution

Actual flow characteristics are much more complex in detail than just Hjulstrom diagrams, which summarize a lot of characteristics into two axes. However, like a lot of people, we will use the diagram anyway, because it is very useful as a rule of thumb. Just remember that it does not accurately represent what will happen in detail - it represents a reasonable guess.

Silt and Clay Transport

Notice that for the small end of grain size, the speed of flow required for erosion actually increases. One reason small grains are hard to erode is that they tend not to stick up through the laminar sublayer; they are just too small. Thus, thinner boundary layers are necessary to roll them or for the pressure differences to pick them up off the bed. Also, the surfaces of clay minerals tend to be charged and the grains stick together. This is most obvious when big clumps of mud stick to your shoes. That just does not happen with sand (unless there is something gross in it). The stickiness of the clay grains makes them difficult to erode, so faster water flows (a greater pressure difference or larger turbulent burst down to the sediment surface) are required to move them. The smaller the grains, the more surface charges stick the grains together, thus the stronger the flow needed to erode them. The stickiness of the clay grains also depends on the amount of water between them and the mineralogy, so there is a big gray zone where a clay may or may not erode.

In the Hjulstrom diagram, there is an interesting area where the flow is not strong enough to move any of the particles on the bed, but those that are in the suspended load do not settle out either. This zone includes many of the waters on the surface of the Earth. In flows with any velocity or that are very deep, (Re) is high enough to keep some clay in suspension. Clay deposition usually occurs very slowly, e.g. when the rate of settling is just slightly faster than the average rate at which turbulence moves clay particles upward or when the clays clump together to form larger grains (which is common when fresh and salty waters mix).

Miscellaneous Notes

A few more words about saltation: Saltation is a very interesting and important process in sediment transport, because the force of the impact when the grains land tends to knock new grains up into the flow even if the flow is not fast enough to lift them with the Bernoulli Effect. These new grains can kick up more grains when they land, etc. This increases the rate of sediment transport above the amount the flow can lift grains off of the bed. This is one of the causes of the gray zone in the Hjulstrom diagram at larger grain sizes. Once saltation starts, it can trigger sediment transport that would not otherwise occur.

Deposition: Deposition is the accumulation of grains. If a flow starts slowly and gains speed, it will start to move larger and larger grains. As it slows down, it can only move the smaller ones. Deposition happens when a flow slows down and starts to leave grains on the bed. The combination of changing average flow speeds and local variations in flow speed caused by topography on the bed give rise to very informative sedimentary structures – including cross stratification - which are extremely useful for interpreting depositional environments.


9.5: Sediment Transport - Geosciences

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9.5 Sedimentary Structures and Fossils

Through careful observation over the past few centuries, geologists have discovered that the accumulation of sediments and sedimentary rocks takes place according to some important geological principles that can be summarized as follows:

  • The principle of original horizontality states that sediments accumulate in essentially horizontal layers. The implication is that tilted sedimentary layers observed today must have been subjected to tectonic forces that tilted them.
  • The principle of superposition states that sedimentary layers are deposited in sequence, and that unless the entire sequence has been turned over by tectonic processes, the layers at the bottom are older than those at the top.
  • The principle of inclusions states that any rock fragments in a sedimentary layer must be older than the layer that contains them. For example, the cobbles in a conglomerate must have been formed before the conglomerate.
  • The principle of faunal succession states that there is a well-defined order in which organisms have evolved through geological time, and therefore the identification of specific fossils in a rock can be used to determine its age.

These and other principles are discussed in more detail in Chapter 19.

In addition to these principles that apply to all sedimentary rocks, a number of other important characteristics of sedimentary processes lead to the development of distinctive sedimentary features in specific sedimentary environments. By understanding the origins of these features, we can make some very useful inferences about the processes and depositional environment that ultimately resulted in the rocks that we are studying.

Bedding refers to sedimentary layers that can be distinguished from one another on the basis of characteristics such as texture, composition, colour, or weathering characteristics (Figure 9.22). They may also be similar layers separated by partings, narrow regions marking weaker surfaces where erosion is enhanced. Bedding is an indication of changes in depositional processes that may be related to seasonal differences, changes in climate, changes in locations of rivers or deltas, or tectonic changes. Bedding can form in almost any depositional environment.

Figure 9.22 Beds in the Triassic Sulphur Mt. Formation near Exshaw, Alberta. Bedding is defined by differences in colour and texture, and also by partings (darker lines) between beds that may otherwise appear to be similar. Source: Steven Earle (2015) CC BY 4.0 view source

Cross-bedding is bedding that contains angled layers. It forms when sediments are deposited by flowing water or wind (Figure 9.23). Cross-beds in streams tend to be on the scale of cm to tens of cm, while those in aeolian (wind deposited) sediments can be on the scale of metres.

Figure 9.23 Cross-bedded Jurassic Navajo Formation aeolian sandstone at Zion National Park, Utah. In most of the layers the cross-beds dip down toward the right, implying wind direction from right to left during deposition. One bed dips in the opposite direction, implying a different wind direction. Source: Steven Earle (2015) CC BY 4.0 view source

Cross-beds form as sediments are deposited on the leading edge of an advancing ripple or dune. Each layer is related to a different ripple that advances in the flow direction, and is partially eroded by the following ripple (Figure 9.23). Cross-bedding is a very important sedimentary structure to recognize because it can provide information on the direction of current flows and, when analyzed in detail, on other features like the rate of flow and the amount of sediment available.

Figure 9.24 Formation of cross-beds as a series of ripples or dunes that migrate with the flow. Each ripple advances forward (right to left in this view) as more sediment is deposited on its leading face. Source: Steven Earle (2015) CC BY 4.0 view source

Ripples, which are associated with the formation of cross-bedding under unidirectional flow, may be preserved on the surfaces of sedimentary beds. Ripples formed in flowing water can also help to determine flow direction because they tend to have their steepest surface facing down-flow. Ripples can also form from back-and-forth flows, like at a beach, but these do not leave cross-beds, and are symmetrical, without one side steeper than the other.

Graded bedding is characterized by a change in grain size from bottom to top within a single bed. “Normal” graded beds are coarse at the bottom and become finer toward the top (Figure 9.25), a product of deposition from a slowing current. Some graded beds are reversed (coarser at the top), and this normally results from deposition by a fast-moving debris flow. Most graded beds form in a submarine fan environment, where sediment-rich flows descend periodically from a shallow marine shelf down a slope and onto the deeper sea floor.

Figure 9.25 Graded bedding going from pebbles at the bottom to sand at the top. Source: Cropped from James St. John (2018) CC BY 2.0 view source

In a stream environment, boulders, cobbles, and pebbles can become imbricated, meaning that they are generally tilted in the same direction. Clasts in streams tend to tilt with their upper ends pointing downstream, because this is the most stable position with respect to the stream flow (Figure 9.26).

Figure 9.26 Imbrication of clasts in a fluvial environment. Source: Steven Earle (2015) CC BY 4.0 view source

Mud cracks form when a shallow body of water (e.g., a tidal flat or pond), into which muddy sediments have been deposited, dries up and cracks (Figure 9.27). This happens because the clay in the upper mud layers shrinks upon drying.

Figure 9.27 Mud cracks in a tidal flat in England. Source: Alan Parkinson (2000) CC BY-SA 2.0 view source

The various structures described above are critical to understanding and interpreting the formation of sedimentary rocks. In addition to these structures, geologists also look very closely at sedimentary grains to determine their mineralogy or lithology (in order to make inferences about the type of source rock and the weathering processes), their degree of rounding, their sizes, and the extent to which they have been sorted by transportation and depositional processes.

A Note About Fossils

Fossils are not covered in detail in this book, but they are extremely important for understanding sedimentary rocks. Fossils can be used to date sedimentary rocks, but just as importantly, they tell us a great deal about the depositional environment of the sediments and the climate at the time: they can help to differentiate marine, aquatic, and terrestrial environments estimate the depth of the water detect the existence of currents and estimate average temperature and precipitation.

Exercise: Interpreting Past Environments

Sedimentary rocks can tell us a great deal about the environmental conditions that existed during the time of their formation. For each of the following rocks, make some inferences about the following:

  • source rock
  • weathering
  • sediment transportation (medium of transport, transport distance)
  • depositional conditions

Quartz sandstone: no feldspar, well-sorted and well-rounded quartz grains, cross-bedded

Feldspathic sandstone and mudstone: feldspar, volcanic fragments, angular grains, repetitive graded bedding from sandstone upwards to mudstone

Conglomerate: well-rounded pebbles and cobbles of granite and basalt imbrication

Breccia: poorly sorted, angular limestone fragments orange-red matrix


3.2 Sediment transport

In Fig. 6 we present the instantaneous sediment transport rate Qs measured by the light table during each experiment. Sediment transport is reported every 5 min, as described in Sect. 2. Accuracy of the results is estimated by comparing the light table data with the data measured by the trap. Results show that for our experiments, the light table method has good accuracy in terms of the sediment transport rate, with an overestimation by 4 % on average (111 samples and a standard deviation of 14.5 %). A total of 70 out of 111 samples show an accuracy of ±10 %, and 93 out of 111 samples show an accuracy of ±20 %. Details of this uncertainty analysis are presented in the Supplement.

It can be seen in Fig. 6a that the temporal variation of sediment transport rate during the conditioning phase follows the same trend in all six experiments. That is, the sediment transport rate decreases significantly during the conditioning phase, with the decreasing rate being very large at the beginning and then gradually dropping. In the first 15 min, the sediment transport rates drop from more than 500 kg/h to less than 100 kg/h. Afterwards, it takes about another 2 h for the sediment transport rates to drop to close to 1 kg/h. The sediment transport rate eventually approaches a small and relatively constant value after about 8 h of conditioning flow. For REF2 (15) and REF6 (15), which have the longest conditioning phase, the sediment transport rates between t=8 h and the end of conditioning phase ( t=15 h) show mean values of 0.35 kg/h (standard deviation = 0.22 kg/h) and 0.37 kg/h (standard deviation = 0.24 kg/h), respectively. Nevertheless, there are random high points in the sediment transport rate even after 8 h, despite no sediment feed from the inlet. These spikes imply that partial destruction (or reorganization) of the bed structure occurs even after a long duration of conditioning.

Previous researchers (Haynes and Pender, 2007 Masteller and Finnegan, 2017) have suggested that an exponential function can be implemented to describe such a decrease of sediment transport rate under conditioning flow. Additional analysis is implemented in the Supplement to fit REF2 (15) and REF6 (15) (which have the longest duration of conditioning phase) against a two-parameter exponential function. Results show that the exponential function can describe the general decreasing trend of sediment transport rate during the conditioning phase, except at the beginning of the experiment where the decrease of sediment transport rate is much more significant than that predicted by the exponential function. Readers can refer to the Supplement for more details.

Figure 6Instantaneous sediment transport rate measured by the light table during (a) the conditioning phase and (b) the hydrograph phase. (c) Intra-step temporal change rate of Qs normalized against Qsa for each hydrograph step. Qs is the sediment transport rate, and Qsa is the averaged sediment transport rate of a given hydrograph step.

Figure 6b presents the instantaneous sediment transport rate during the hydrograph phase. Results show that variation of sediment transport rate among different experiments prevails in the first step of the hydrograph, with the highest sediment transport rate for the experiment with the shortest conditioning duration (REF7 (0.25)) and the smallest sediment transport rate for the experiment with the longest conditioning duration (REF6 (15)). Such variation among experiments, however, diminishes towards the end of step 1 and is not observed in the following three steps of the hydrograph, with the line for each experiment collapsing together in the figure. Such adjustments of sediment transport rate are consistent with the process of channel deformation shown in Fig. 3. Thus, for both sediment transport and channel deformation, results of REF7 (0.25) deviate from other experiments in step 1 (larger sediment transport rate and more degradation in REF7 (0.25)) but collapse with other experiments in the following three steps.

Results in Fig. 6b also show large variations of sediment transport rate during each step of the hydrograph. Such intra-step variations of sediment transport rate are investigated in Fig. 6c, with the x axis being the averaged sediment transport rate of each step Qsa and the y axis being d(Qs / Q sa ) / d t . The value of d(Qs / Q sa ) / d t is estimated by linear regression. Here the instantaneous sediment transport rate Qs is scaled against the average sediment transport rate of the corresponding step Qsa in order to facilitate the comparison among different hydrograph steps.

Results in Fig. 6c show that a large fraction of the data (11 out of 20) exhibit a decreasing trend in time for Qs (i.e., a negative value in vertical coordinate). Basically, the larger the averaged sediment transport rate Qsa , the larger the rate of reduction in Qs . Ferrer-Boix and Hassan (2015) observed similar declines in sediment transport during their water pulse experiments. They attributed this to (1) the presence of bed structures, which could have reduced skin friction up to 20 %, and (2) streamwise changes in the patterns of bed surface sorting. Out of 20 datasets, 5 exhibit some temporally increasing trend in Qs (though this is not as evident as the decreasing trend mentioned before). They are REF5 (5), REF3 (10), REF6 (15) during the first step and REF7 (0.25), REF4 (2) during the third step. This shows that for the three experiments with a long conditioning duration, Qs is very low at the end of the conditioning phase, and the first step of the hydrograph sees a temporally increasing trend in Qs , whereas for the two experiments with a short conditioning phase, Qs is still high at the end of the conditioning, and thus the sediment transport rate keeps decreasing during the first step until an increasing trend in Qs is observed in the third step, at which point the water and sediment supply become evidently higher. The decreasing and increasing trends of Qs during steps of the hydrograph reflect the transient adjustments of the bed to the changed water and sediment supply before equilibrium is achieved.

Sediment collected in the trap or tailbox at the flume outlet allows us to plot the total amount of sediment output during each step of the hydrograph. Figure 7a shows the total sediment output during the entire hydrograph. It can be seen that the effect of conditioning duration on the total sediment output during the entire hydrograph phase is not evident: a longer duration of conditioning flow does not necessarily lead to a smaller (or larger) sediment output. The largest sediment output occurs in REF7 (0.25), which is 55 % larger than the sediment output in REF3 (10), which has the smallest output, but is about the same as (only 4 % larger than) the sediment output in REF6 (15). We further calculate the correlation coefficient between the total sediment output and the duration of conditioning flow and obtain a value of r = - 0.14 , indicating that there is almost no correlation between the two parameters.

Figure 7Sediment output measured at a trap during (a) the whole hydrograph, (b) step 1 of the hydrograph, (c) step 2 of the hydrograph, (d) step 3 of the hydrograph, and (e) step 4 of the hydrograph.

However, if we study the sediment transport during each step of the hydrograph, we can find that in step 1 REF7 (0.25) has much larger sediment output than the other experiments, as shown in Fig. 7b. For Step 1, the sediment output is 1.1 in REF6 (15) 3.4–4.4 kg in REF4 (2), REF5 (5), and REF 3(10) and increases sharply to 23.4 kg in REF7 (0.25) (which is more than 20 times that in REF6 (15)). This agrees with the results for instantaneous sediment transport rate shown in Fig. 6b and shows that the duration of conditioning flow can influence the sediment transport at the beginning of the subsequent flood, with a longer conditioning phase leading to less sediment transport. When the duration of conditioning flow is over 2 h, the subsequent sediment transport rate becomes rather insensitive to further increase of conditioning duration, indicating that the reorganization of the river bed under conditioning flow is mostly finished within 2 h. The effects of stress history on subsequent sediment transport can hardly be observed during step 2 of the hydrograph (Fig. 7c). Sediment output in REF7 (0.25) reduces significantly to a similar magnitude to the other experiments because most of the loose bed material in REF7 (0.25) has been moved by the end of step 1. More specifically, the volumes of sediment output in this step range between 3.1 and 8.6 kg, with the largest output occurring in REF5 (5) and the minimum output occurring in REF3 (10). We further calculate the correlation coefficient between sediment output and conditioning duration and obtain a value of r = - 0.61 , indicating that a longer conditioning duration can no longer lead to a larger sediment output in this step. In Step 3 of the hydrograph (Fig. 7d), sediment output in REF7 (0.25) and REF4 (2) is larger than in other three experiments, which have longer conditioning phases. However, in this step the sediment output in REF7 (0.25) is no more than 3 times that of the sediment output in REF3 (10), which has the minimum sediment output. This difference of sediment output among experiments is not as significant as in step 1. In the last step of the hydrograph, with the flow discharge and sediment supply approaching their peaks, the difference in sediment output among the five experiments again becomes small, with the values ranging between 72.1 kg in REF4 (2) and 119.6 kg in REF6 (15). This demonstrates that little influence of stress history remains in this step.

Figure 8 shows the temporal variation of the grain size distribution of the bed load. Here Dl10 , Dl50 , and Dl90 denote grain sizes such that 10 %, 50 %, and 90 % are finer in the bed load, respectively. Accuracy of the measurements is estimated by comparing the light table data with the trap data. Results show that for our experiments, the light table method has good accuracy in terms of the median size of bed load ( Dl50 ), with an overestimation by 3 % on average (111 samples and a standard deviation of 40.1 %). Measurements of Dl10 and Dl90 show less accuracy, with an underestimation by 20 % on average (111 samples and a standard deviation of 39.0 %) for Dl10 and an overestimation by 30 % on average (111 samples and a standard deviation of 26.5 %) for Dl90 . Details concerning this uncertainty analysis are presented in the Supplement.

The value of Dl10 shows a decreasing trend during the conditioning phase (Fig. 8a), with a value of more than 2 mm at the beginning to about 0.6 mm after 15 h, in spite of the large fluctuations before 8 h. The decrease of Dl10 reflects an increase in the fraction of the finest sediment in bed load. In the first two steps of the hydrograph (Fig. 8b), the value of Dl10 is relatively stable for experiments with long conditioning phases (i.e., REF6 (15) and REF3 (10)) but shows a decreasing trend along with fluctuations for experiments with short conditioning phases (i.e., REF7 (0.25), REF4 (2), and REF5 (5)). The last two steps of the hydrograph see an evident increase in the value of Dl10 compared with the first two steps, due to the increase of flow discharge and sediment supply (Fig. 8b). We note that such an increase in the Dl10 is larger than the standard deviation of measurements, as shown above.

Figure 8c and d show the temporal variation of Dl50 . Compared with that of Dl10 , the temporal variation of Dl50 shows more significant fluctuations during the conditioning phase (especially after t=10 h), as well as at the beginning of the hydrograph. This can be shown by the coefficient of variation (cv) of the grain size. For the conditioning phase (after t=10 h), the cv of Dl10 shows an average value of 0.05, whereas the cv of Dl50 shows an average value of 1.44. For step 1 of the hydrograph phase, the cv of Dl10 shows an average value of 0.35, whereas the cv of Dl50 shows an average value of 0.66. For step 2 of the hydrograph phase, the cv of Dl10 shows an average value of 0.12, whereas the cv of Dl50 shows an average value of 0.54. As for the temporal variation of Dl90 (in Fig. 8e and f), the fluctuations are still significant, with the average cv being 0.61, 0.34, and 0.27 for the conditioning phase (after t=10 h), step 1 of hydrograph phase, and step 2 of hydrograph phase, respectively. Besides, there is no significant increase or decrease of Dl90 during the experiment. This indicates that the transport of the coarsest sediment is not sensitive to the variation of our experimental conditions. The more significant fluctuations in Dl50 and Dl90 might be attributed to the fact that during relatively low flow coarse sediment is more likely to be near the threshold of motion and move intermittently, e.g., as individual grains, as opposed to the more continuous movement for fine sediment. These fluctuations gradually diminish with the increase of flow and sediment supply, as the static armor on bed surface transits to mobile armor and the movement of coarse grains becomes more continuous.

Figure 8Temporal adjustments of characteristic grain sizes of bed load: (a) Dl10 during conditioning phase, (b) Dl10 during hydrograph phase, (c) Dl50 during conditioning phase, (d) Dl50 during hydrograph phase, (e) Dl90 during conditioning phase, and (f) Dl90 during hydrograph phase.

With the fractional sediment transport rate measured by the light table, we also analyze the sediment mobility of each size range during the experiment. Results show that sediment transport rate is characterized by equal mobility (i.e., the GSD of sediment load matches the GSD of sediment on bed surface) at the beginning of the conditioning phase but moves to partial or selective mobility after a relatively long conditioning phase and during the first two steps of the hydrograph. However, with the increase of flow discharge and sediment supply, the sediment transport regime gradually returns to equal mobility during the last two steps of the hydrograph. Details of the analysis are presented in the Supplement.


Affiliations

State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China

Shuai Wang, Bojie Fu, Yihe Lü, Xiaoming Feng & Yafeng Wang

Joint Center for Global Change Studies, Beijing 100875, China

Shuai Wang, Bojie Fu, Yihe Lü, Xiaoming Feng & Yafeng Wang

College of Urban and Environmental Sciences, Peking University, Beijing 100871, China

Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China

Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ, 91191 Gif-sur-Yvette, France


The Impact of Winter Storms on Sediment Transport Through a Narrow Strait, Bohai, China

The Yellow River is one of the most significant sources of terrestrial sediment to the global seas, and the Bohai Strait is the only pathway that delivers Yellow River-derived sediments from the shallow Bohai Sea to the Yellow Sea. To investigate sediment transport processes through the strait under the influence of storms (strong northerly winds) that frequently occur in winter, we deployed two sets of observing platforms equipped with Acoustic Doppler Current Profilers (ADCP) and a suite of other sensors in the strait in January 2018. Aided by a system of high-resolution models, we reconstructed sediment dynamics in response to the strong northerly wind of a winter storm. Model results show that the instantaneous suspended sediment flux (SSF) is highly aligned with tidal currents, while the net sediment flux has a clear dependence on variations in exchange flow and sediment resuspension. Enhanced coastal currents, intensified wave motions, and higher suspended sediment concentrations indicate that the through-strait sediment flux during outflows is greater than during inflow conditions. Such SSF asymmetries are believed responsible for the net sediment export through the Bohai Strait in wintertime. Diagnostic analyses provided insights into the dynamic mechanisms of exchange flow variations influenced by both the strong northerly winds and the wind-triggered coastal trapped waves in the shallow, narrow strait via geostrophic effects. This study highlights the importance of storm-induced horizontal exchange processes in a coupled bay-shelf system.

Plain Language Summary

The aim of this study is to characterize the dominant processes that control net wintertime sediment fluxes through a narrow strait. Flows, waves, and sediment concentration were measured in the strait during a winter storm. A well-validated model showed that wintertime flows in the strait are dominated by alternating, strait-wide inflow and outflow. Occasionally, however, inflows and outflows are concurrent over different sections of the strait. Based on a numerical model, our calculations of sediment flux for the entire winter revealed that large net sediment flux occurred when both winds and waves were strong. These results provide a better understanding of how sediment transport in a bay-shelf system has driven by both local and remote forcing mechanisms.


Watch the video: HEC-RAS 2D Sediment Modeling