Determination of the manning coefficient from measured bed roughness in natural channels

Limerinos, John Thomas

doi:10.3133/wsp1898b

Cited by 52 publications

(6 citation statements)

References 13 publications

(6 reference statements)

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“…The calculations based on the Strickler formula [6] give the best results in the author's interpretation of the formula. The constant term value in Zegzhda formula [7] was found to be 1.0, in agreement with results previously obtained by Limerinos [13].…”

Section: Discussionsupporting

confidence: 89%

“…The analysis of research published on this work shows that the formula of form (4) has been extensively verified based on the field measurements and laboratory data and is recommended for use in calculations by a number of other authors [9][10][11][12][13][14]. These results indicate the increasing hydraulic resistance when passing from experiments in the trays to the river original flows.…”

Section: Grain Roughnessmentioning

confidence: 60%

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Sediment Transport and Water Flow Resistance in Alluvial River Channels: Modified Model of Transport of Non-Uniform Grain-Size Sediments

Gladkov

Habel

Babiński

et al. 2021

Water

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The paper presents recommendations for using the results obtained in sediment transport simulation and modeling of channel deformations in rivers. This work relates to the issues of empirical modeling of the water flow characteristics in natural riverbeds with a movable bottom (alluvial channels) which are extremely complex. The study shows that in the simulation of sediment transport and calculation of channel deformations in the rivers, it is expedient to use the calculation dependences of Chézy’s coefficient for assessing the roughness of the bottom sediment mixture, or the dependences of the form based on the field investigation data. Three models are most commonly used and based on the original formulas of Meyer-Peter and Müller (1948), Einstein (1950) and van Rijn (1984). This work deals with assessing the hydraulic resistance of the channel and improving the river sediment transport model in a simulation of riverbed transformation on the basis of previous research to verify it based on 296 field measurements on the Central-East European lowland rivers. The performed test calculations show that the modified van Rijn formula gives the best results from all the considered variants.

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Section: Discussionsupporting

confidence: 89%

Section: Grain Roughnessmentioning

confidence: 60%

Sediment Transport and Water Flow Resistance in Alluvial River Channels: Modified Model of Transport of Non-Uniform Grain-Size Sediments

Gladkov

Habel

Babiński

et al. 2021

Water

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“…The d 84 , or the particle size that exceeds that of 84 percent of the particles, ranged from 32 to 180 mm, or very coarse gravel to cobble. The computed base n-values from equations by Limerinos (1970) and Rickenmann and Recking (2011) are within the range of n-values given for gravel by Arcement and Schnieder (1989) apart from Tie Canyon Overbank, which had a larger percentage of boulders. (1970).…”

Section: Channel Bed Particle Size and Roughnesssupporting

confidence: 60%

Delineation of flood-inundation areas in Grapevine Canyon near Scotty’s Castle, Death Valley National Park, California

Morris¹,

Welborn²,

Minear³

2020

Scientific Investigations Report

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“…There are many empirical models for directly computing grain roughness, however they were developed across variety of site conditions and therefore each may or may not be relevant to a given application. From the studies of Rickenmann and Recking (2011) and Wang and Dawdy (2014), we obtained nine equations for computing grain roughness in gravel-bedded streams that are either widely used or represent a low or high degree of complexity (Bathurst, 1985;Bray, 1979;Ferguson, 2007;Griffiths, 1981;Hey, 1979;Keulegan, 1938;Leopold & Wolman, 1957;Limerinos, 1970;Smart & Jäggi, 1983;Strickler, 1923; section S1.2). We computed grain roughness using LM gage observations in each of the nine equations and found that the computed grain roughness was nearly constant with streamflow depth in each equation.…”

Section: Shear Stress and Surface Roughnessmentioning

confidence: 99%

A Channel Network Model for Sediment Dynamics Over Watershed Management Time Scales

Beveridge

Istanbulluoglu

Bandaragoda

et al. 2020

J Adv Model Earth Syst

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A mountain watershed network model is presented for use in decadal to centurial estimation of source-to-sink sediment dynamics. The model requires limited input parameters and can be effectively applied over spatial scales relevant to management of reservoirs, lakes, streams, and watersheds (1-100 km 2 ). The model operates over a connected stream network of Strahler-ordered segments. The model is driven by streamflow from a physically based hydrology model and hillslope sediment supply from a stochastic mass wasting algorithm. For each daily time step, segment-scale sediment mass balance is computed using bedload and suspended load transport equations. Sediment transport is partitioned between grain size fractions for bedload as gravel and sand, and for suspended load as sand and mud. Bedload and suspended load can deposit and re-entrain at each segment. We demonstrated the model in the Elwha River Basin, upstream of the former Glines Canyon dam, over the dam's historic 84-year lifespan. The model predicted the lifetime reservoir sedimentation volume within the uncertainty range of the measured volume (13.7-18.5 million m 3 ) for 25 of 28 model instances. Gravel, sand, and mud fraction volumes were predicted within measurement uncertainty ranges for 18 model instances. The network model improved the prediction of sediment yields compared to at-a-station sediment transport capacity relations. The network model also provided spatially and temporally distributed information that allowed for inquiry and understanding of the physical system beyond the sediment yields at the outlet. This work advances cross-disciplinary and application-oriented watershed sediment yield modeling approaches.Plain Language Summary Predicting sediment processes in river systems is challenging. Most methods for doing so in water resource system planning and management are lacking in scientific advancement. However, approaches used in academic research for understanding river sediment processes are often not well suited for practical applications. Academic approaches are often siloed between disciplines and do not holistically address real-world needs. In this study, we developed a new computer model for predicting sediment processes in river systems. We combined academic research approaches from various disciplines to address a practical need of predicting reservoir sediment accumulation in mountainous regions. We demonstrated the model in the Elwha River Basin, upstream of the former Glines Canyon dam, over the dam's historic 84-year lifespan. Our model predicted the volume of sediment that accumulated behind the dam over its lifetime. We also predicted the reservoir sediment accumulation using a traditional approach called sediment rating curves to compare to our model performances. We demonstrated that our model predicted the reservoir sediment accumulation better than the rating curves did, and our model also provided more information about the broader river system than the curves. Overall, our work advances cross-disciplinary and appl...

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Determination of the manning coefficient from measured bed roughness in natural channels

Cited by 52 publications

References 13 publications

Sediment Transport and Water Flow Resistance in Alluvial River Channels: Modified Model of Transport of Non-Uniform Grain-Size Sediments

Sediment Transport and Water Flow Resistance in Alluvial River Channels: Modified Model of Transport of Non-Uniform Grain-Size Sediments

Delineation of flood-inundation areas in Grapevine Canyon near Scotty’s Castle, Death Valley National Park, California

A Channel Network Model for Sediment Dynamics Over Watershed Management Time Scales

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