The exceptional sediment load of fine-grained dispersal systems: Example of the Yellow River, China

Ma, Hsi-Pin; Nittrouer, Jeffrey A.; Naito, Kensuke; Fu, Xudong; Zhang, Yuanfeng; Moodie, Andrew J.; Wang, Yuanjian; Wang, Baosheng; Parker, Gary

doi:10.1126/sciadv.1603114

Cited by 65 publications

(113 citation statements)

References 59 publications

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“…The closure relationships for sediment and suspended loads are the one used throughout the paper and reported in Appendixes and (Meyer‐Peter Muller formula for the bedload; Meyer‐Peter & Müller, , and the asymptotic approach for the suspended load; Bolla Pittaluga & Seminara, ). Finally, some speculative considerations are also made for partial data on the Yellow River in China (Ma et al, ).…”

Section: Validation and Discussion Of The Resultsmentioning

confidence: 99%

“…A further comment can be made regarding a field work conducted by Ma et al () on the Yellow River, which owes its name to the huge amount of suspended sediment. The main focus of the paper by Ma et al () concerned the correct evaluation of the suspended load, which was underestimated by one order of magnitude when classical formulas were used. Our interest has instead been on the 1.5‐km‐long longitudinal section of bathymetry surveyed by Ma et al () near one of the river banks.…”

Section: Validation and Discussion Of The Resultsmentioning

confidence: 99%

“…In particular, bathymetry data from the Mississippi river (Ramirez & Allison, ) and a straight artificial channel in the Netherlands (Eekhout et al, ) are used. In addition, some speculative considerations are made pertaining to partial data on the Yellow River in China (Ma et al, ).…”

Section: Introductionmentioning

confidence: 99%

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Finite Amplitude of Free Alternate Bars With Suspended Load

Bertagni¹,

Camporeale²

2018

Water Resources Research

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River bars are macroscale sediment patterns, whose main geometrical features (wavelength and amplitude) depend on the mutual interactions between hydrodynamics and sediment transport. River bars develop as an instability of the plane bed to an infinitesimal perturbation, which grows in time to eventually reach a finite amplitude. We here determine, with reference to both bed and suspended loads, a closed form for the finite amplitude, through the nonlinear Center Manifold Projection technique. Results show that suspension plays a destabilizing role in bar instability, affecting both the bar wavelength (linear analysis) and the bar amplitude (weakly nonlinear analysis). This proves the importance of considering suspended load for practical purposes. The outcomes of the model are satisfactorily compared with field observations.

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Section: Validation and Discussion Of The Resultsmentioning

confidence: 99%

Section: Validation and Discussion Of The Resultsmentioning

confidence: 99%

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Finite Amplitude of Free Alternate Bars With Suspended Load

Bertagni¹,

Camporeale²

2018

Water Resources Research

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“…Satellite remote sensing data are used to document Yellow River delta and delta lobe progradation over the last ∼45 years (Bi et al, 2014;Chu et al, 2006;Fan et al, 2006;van Gelder et al, 1994;Wu et al, 2017;Xu, 2003;Yu et al, 2011;Zhang et al, 2016Zhang et al, , 2017. Previous studies focused on the radially averaged delta progradation rate, but a direct measure of lobe progradation rate is needed to validate the present numerical model.…”

Section: Measuring Progradation Of the Yellow River Deltamentioning

confidence: 99%

“…where C f = 0.001 is the dimensionless coefficient of friction for the Yellow River (Ma et al, 2017), Fr 2 = Q 2 w ∕gB 2 H 3 is the Froude number for a rectangular channel, g is the gravitational acceleration constant, and B is the width of the flow, set by the channel width B c in the confined fluvial portion of the model domain and increasing by dB∕dx = 2 tan , where = 5 • for the geometric approximation of a spreading plume beyond the river mouth, as measured relative to the flow centerline (supporting information S1; Chatanantavet et al, 2012;Lamb et al, 2012). A spreading plume abruptly increases the cross-sectional area of the flow beyond the river mouth such that the water surface elevation at the river mouth is relatively fixed regardless of the river discharge (e.g., Chatanantavet et al, 2012;Lamb et al, 2012;Rajaratnam, 1976;Rowland et al, 2009).…”

Section: Model Designmentioning

confidence: 99%

Modeling Deltaic Lobe‐Building Cycles and Channel Avulsions for the Yellow River Delta, China

Moodie

Nittrouer

et al. 2019

JGR Earth Surface

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River deltas grow by repeating cycles of lobe development punctuated by channel avulsions, so that over time, lobes amalgamate to produce a composite landform. Existing models have shown that backwater hydrodynamics are important in avulsion dynamics, but the effect of lobe progradation on avulsion frequency and location has yet to be explored. Herein, a quasi‐2‐D numerical model incorporating channel avulsion and lobe development cycles is developed. The model is validated by the well‐constrained case of a prograding lobe on the Yellow River delta, China. It is determined that with lobe progradation, avulsion frequency decreases, and avulsion length increases, relative to conditions where a delta lobe does not prograde. Lobe progradation lowers the channel bed gradient, which results in channel aggradation over the delta topset that is focused farther upstream, shifting the avulsion location upstream. Furthermore, the frequency and location of channel avulsions are sensitive to the threshold in channel bed superelevation that triggers an avulsion. For example, avulsions occur less frequently with a larger superelevation threshold, resulting in greater lobe progradation and avulsions that occur farther upstream. When the delta lobe length prior to avulsion is a moderate fraction of the backwater length (0.3– 0.5trueL‾b), the interplay between variable water discharge and lobe progradation together set the avulsion location, and a model capturing both processes is necessary to predict avulsion timing and location. While this study is validated by data from the Yellow River delta, the numerical framework is rooted in physical relationships and can therefore be extended to other deltaic systems.

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The morphology of fluvial‐tidal dunes: Lower Columbia River, Oregon/Washington, USA

Prokocki

Best

Perillo

et al. 2022

Earth Surf Processes Landf

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This article quantifies changes in primary dune morphology of the mesotidal Lower Columbia River (LCR), USA, through ~90 river kilometres of its fluvial‐tidal transition at low‐river stage. Measurements were derived from a multibeam echo sounder dataset that captured bedform dimensions within the thalweg (≥ 9 m depth; H/Hmax ≥ 0.7) of the LCR main channel. Measurements revealed two categories of dunes: (i) fine to medium sand ‘fluvial‐tidal to tidal’ (upstream‐oriented, simple, and two‐dimensional) low‐angle dunes (heights ≈ 0.3–0.8 m; wavelengths ≈ 10–25 m; mean lee‐angles ≈ 7°–11°), and (ii) medium to coarse sand ‘fluvial’ (downstream‐oriented, compound, and 2.5‐dimensional to three‐dimensional) low‐angle dunes (heights ≈ 1.5–3 m; wavelengths ≈ 60–110 m; mean lee‐angles ≈ 11°–18°). At low‐river stage, where H/Hmax ≥ 0.7, approximately 86% of the fluvial‐tidal transition is populated by ‘fluvial’ dunes, whilst ~ 14% possesses ‘fluvial‐tidal to tidal’ dunes that form in the downstream‐most reaches. Thus, throughout the majority of the deepest channel segments of the fluvial‐tidal transition, seaward‐oriented river and ebb‐tidal currents govern dune morphology, whilst strong bidirectional tidal‐current influence is restricted to the downstream most reaches of the transition zone. Two mechanisms are reasoned to explain dune low‐angle character: (1) high‐suspended sediment transport near peak tidal‐currents that lowers the leeside‐angles of ‘fluvial‐tidal to tidal’ dunes, and (2) superimposed bedforms that erode the crests, leesides, and stoss‐sides, of ‘fluvial’ dunes, which results in the reduction of leeside‐angles. Fluctuations in river discharge create a ‘dynamic morphology reach’ at depths where H/Hmax ≥ 0.7, which spans river kilometres 12–40 and displays the greatest variation in dune morphology. Similar channel reaches likely exist in fluvial‐tidal transitions with analogous physical characteristics as the LCR and may provide a distinct signature for the fluvial‐tidal transition zone.

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The exceptional sediment load of fine-grained dispersal systems: Example of the Yellow River, China

Abstract: We analyze why the sediment discharges of fine-grained rivers are an order of magnitude larger than predicted by current theory.

Cited by 65 publications

References 59 publications

Finite Amplitude of Free Alternate Bars With Suspended Load

Finite Amplitude of Free Alternate Bars With Suspended Load

Modeling Deltaic Lobe‐Building Cycles and Channel Avulsions for the Yellow River Delta, China

The morphology of fluvial‐tidal dunes: Lower Columbia River, Oregon/Washington, USA

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