Effect of bed-load concentration on friction factor in narrow channels

Calomino, Francesco; Gaudio, Roberto; Miglio, Antonio

doi:10.1201/b16998-37

Cited by 7 publications

(5 citation statements)

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“…The second important result to be discussed is that bed load increases flow resistance. This has been demonstrated experimentally by many researchers over the last 10 years [ Smart and Jaeggi , 1983; Rickenmann , 1990; Baiamonte and Ferro , 1997; Song et al , 1998; Bergeron and Carbonneau , 1999; Carbonneau and Bergeron , 2000; Omid et al , 2003; Calomino et al , 2004; Gao and Abrahams , 2004; Mahdavi and Omid , 2004; Campbell et al , 2005], and the generally accepted view is that bed load extracts momentum from the flow, which causes a reduction in flow velocity and increases the apparent roughness length in proportions that are related to the thickness of the moving sediment layer [ Owen , 1964; Dietrich , 1982; Wiberg and Rubin , 1989]. In addition, the wakes that are shed as sediment grains are accelerated by the flow produce a roughness layer that develops well beyond the top of the saltation layer, affecting the mean velocity profile [ Bergeron and Carbonneau , 1999; Carbonneau and Bergeron , 2000], in a similar way to what was described for fixed beds on steep slopes.…”

Section: Discussionmentioning

confidence: 76%

“…Although a feedback mechanism of this sort has long been suspected, recent studies have clearly demonstrated that, over flat beds, bed load can dramatically increase flow resistance when compared to clear water flows [ Smart and Jaeggi , 1983; Rickenmann , 1990; Baiamonte and Ferro , 1997; Song et al , 1998; Bergeron and Carbonneau , 1999; Carbonneau and Bergeron , 2000; Omid et al , 2003; Calomino et al , 2004; Gao and Abrahams , 2004; Mahdavi and Omid , 2004; Campbell et al , 2005; Hu and Abrahams , 2005]. Some authors [ Engelund and Hansen , 1967; Smart and Jaeggi , 1983] proposed flow resistance and bed load equations derived jointly and implicitly including this type of possible feedback mechanism, but they worked with relatively high‐flow conditions, whereas gravel bed river flow conditions are rarely far above incipient motion conditions [ Parker , 1978; Andrews , 1983; Mueller et al , 2005; Ryan et al , 2002; Parker et al , 2007].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Feedback between bed load transport and flow resistance in gravel and cobble bed rivers

Recking¹,

Frey²,

Paquier³

et al. 2008

Water Resources Research

115

154

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[1] To calculate bed load, engineers often use flow resistance equations that provide estimates of bed shear stress. In these equations, on the basis of the estimate of the appropriate hydraulic radius associated with the bed only, the bed roughness k s is commonly set as a constant, whatever the bed load intensity. However, several studies have confirmed the existence of feedback mechanisms between flow resistance and bed load, suggesting that a flow-dependent bed roughness should be used. Therefore, using a data set composed of 2282 flume and field experimental values, this study investigated the importance of these feedback effects. New flow resistance equations were proposed for three flow domains: domain 1 corresponds to no bed load and a constant bed roughness k s = D (where D is a representative grain diameter), whereas domain 3 corresponds to a high bed load transport rate over a flat bed with a constant bed roughness k s = 2.6D. Between these two domains, a transitional domain 2 was identified, for which the bed roughness evolved from D to 2.6D with increasing flow conditions. In this domain, the Darcy-Weisbach resistance coefficient f can be approximated using a constant for a given slope. The results using this new flow resistance equation proved to be more accurate than those using equations obtained from simple fittings of logarithmic laws to mean values. The data set indicates that distinguishing domains 2 and 3 is still relevant for bed load. In particular, the data indicate a slope dependence in domain 2 but not in domain 3. A bed load model, based on the tractive force concept, is proposed. Finally, flow resistance and bed load equations were used together to calculate both shear stress and bed load from the flow discharge, the slope, and the grain diameter for each run of the data set. Efficiency tests indicate that new equations (implicitly taking a feedback mechanism into account) can reduce the error by a factor of 2 when compared to other equations currently in use, showing that feedback between flow resistance and bed load can improve field bed load modeling.Citation: Recking, A., P. Frey, A. Paquier, P. Belleudy, and J. Y. Champagne (2008), Feedback between bed load transport and flow resistance in gravel and cobble bed rivers, Water Resour. Res., 44, W05412,

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Section: Discussionmentioning

confidence: 76%

Section: Introductionmentioning

confidence: 99%

Feedback between bed load transport and flow resistance in gravel and cobble bed rivers

Recking¹,

Frey²,

Paquier³

et al. 2008

Water Resources Research

115

154

View full text Add to dashboard Cite

show abstract

“…Following Powell [2], flow resistance is composed of the boundary resistance, vegetation resistance [3][4][5][6][7], channel resistance [8][9][10][11][12], spill resistance [13][14][15][16][17][18] and sediment transport resistance [19][20][21][22][23][24][25] and affects bed shear stress and energy dissipation. The challenge in river hydraulics is to achieve the complexity of flow resistance through physical relationships and engineering approaches to gain knowledge about flow velocities, water depths, bed shear stresses and energy losses in channels [2].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Hydrodynamics Simulated by 1D, 2D and 3D Models Focusing on Bed Shear Stresses

Glock

Tritthart

Habersack

et al. 2019

Water

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For centuries, scientists have been attempting to map complex hydraulic processes to empirical formulas using different flow resistance definitions, which are further applied in numerical models. Now questions arise as to how consistent the simulated results are between the model dimensions and what influence different morphologies and flow conditions have. For this reason, 1D, 2D and 3D simulations were performed and compared with each other in three study areas with up to three different discharges. A standardized, relative comparison of the models shows that after successful calibration at measured water levels, the associated 2D/1D and 3D/1D ratios are almost unity, while bed shear stresses in the 3D models are only about 62–86% of the simulated 1D values and 90–100% in the case of 2D/1D. Reasons for this can be found in different roughness definitions, in simplified geometries, in different calculation approaches, as well as in influences of the turbulence closure. Moreover, decreasing 3D/1D ratios of shear stresses were found with increasing discharges and with increasing slopes, while the equivalent 2D/1D ratios remain almost unchanged. The findings of this study should be taken into account, particularly in subsequent sediment transport simulations, as these calculations are often based on shear stresses.

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“…The turbulent characteristics of flow were examined and evaluated by various researchers for plain bed, mobile bed and for vegetated channel viz. flow resistance in mobile bed, rough immobile beds and clear water flows (Best et al 1997;Song et al 1998;Calomino et al 2004), quantification of near-bed turbulence parameters (Dey et al 2012), changes in flow velocity distribution and turbulence characteristics in connection with the specific roughness of flexible submerged macrophytes (Stephan and Gutknecht 2002), effect of two forms of flexible vegetation on the turbulence structure within the submerged canopy and in the surface flow region (Wilson et al 2003), mean velocity profiles and turbulence characteristics above flexible wheat (Jarvela 2005) and turbulence structures and coherent motion in vegetated canopy (Nezu and Sanjou 2008). Sundar et al (2011) have examined the effect of vegetation on run-up and wall pressures due to cnoidal waves.…”

Section: Introductionmentioning

confidence: 99%

Analysing turbulence characteristics of flow over submerged flexible vegetated channel

Shivpure

Devi

Kumar

2015

ISH Journal of Hydraulic Engineering

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Experimental investigation has been done to access turbulence characteristics just above the sparse flexible submerged vegetation zone in open-channel flow. The experimentation has been done in a tilting flume with bed covered by artificial vegetation and arranged in a regular staggered configuration. The applicability of log law is analysed above the vegetated canopy. Turbulent parameters such as velocity profiles, Reynolds stresses, turbulent intensities, quadrant analysis, turbulent production and diffusion, dissipation and stream power have been appraised to understand the hydrodynamics of vegetated channel. Results show that the log law is valid above the canopy of submerged vegetation with decreased Von-Karman constant. Maximum value of turbulent intensities and Reynolds stresses has been found above the canopy. Quadrant analysis shows that sweeps and ejections events are more dominating factors in submerged vegetated channel.

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Effect of bed-load concentration on friction factor in narrow channels

Cited by 7 publications

References 0 publications

Feedback between bed load transport and flow resistance in gravel and cobble bed rivers

Feedback between bed load transport and flow resistance in gravel and cobble bed rivers

Comparison of Hydrodynamics Simulated by 1D, 2D and 3D Models Focusing on Bed Shear Stresses

Analysing turbulence characteristics of flow over submerged flexible vegetated channel

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