A simple physically-based model for predicting sand transport dynamics in the Lower Mekong River

Camenen, B.; Coz, Jérôme Le; Dramais, Guillaume; Peteuil, Christophe; Fretaud, T.; Falgon, A; Dussouillez, Philippe; Moore, Samantha

doi:10.1201/b17133-293

Cited by 8 publications

(10 citation statements)

References 4 publications

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“…In the Supplementary Material (figure 6), the results of sand sediment flux obtained using a sediment transport capacity are presented based on Camenen and Larson (2008) and Camenen et al (2014). Good agreement is observed between the model and data for all stations except for the OBI with a large overestimation is observed.…”

Section: Relationship Between Discharge and Coarse Suspended Sedimentmentioning

confidence: 81%

“…The physical model proposed by Camenen and Larson (2008) and Camenen et al (2014) is relevant because it is based on a large data set including field data. The data show robustness to predict the sands flux (apart for the OBI station).…”

Section: Discussionmentioning

confidence: 99%

“…To evaluate the river bed shear stress, we used stage-discharge-rating curves to estimate hydraulic parameters with a and b fitting coefficients for section-averaged flow velocity and hydraulic radius (Camenen et al 2014).…”

Section: Discharge Rainfall and Sediment Relationshipsmentioning

confidence: 99%

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Rainfall control on Amazon sediment flux: synthesis from 20 years of monitoring

Armijos

Crave

Espinoza

et al. 2020

Environ. Res. Commun.

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The biodiversity and productivity of the Amazon floodplain depend on nutrients and organic matter transported with suspended sediments. Nevertheless, there are still fundamental unknowns about how hydrological and rainfall variability influence sediment flux in the Amazon River. To address this gap, we analyzed 3069 sediment samples collected every 10 days during 1995-2014 at five gauging stations located in the main rivers. We have two distinct fractions of suspended sediments, fine (clay and silt) and coarse (sand), which followed contrasting seasonal and long-term patterns. By taking these dynamics into account, it was estimated, for first time, in the Amazon plain, that the suspended sediment flux separately measured approximately 60% fine and 40% coarse sediment. We find that the fine suspended sediments flux is linked to rainfall and higher coarse suspended sediment flux is related with discharge. Additionally this work presents the time lag between rainfall and discharge, which is related to the upstream area of the gauging. This result is an important contribution to knowledge of biological and geomorphological issues in Amazon basin.

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Section: Relationship Between Discharge and Coarse Suspended Sedimentmentioning

confidence: 81%

Section: Discussionmentioning

confidence: 99%

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Rainfall control on Amazon sediment flux: synthesis from 20 years of monitoring

Armijos

Crave

Espinoza

et al. 2020

Environ. Res. Commun.

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“…Here, the Camenen and Larson (2005) formulae for the estimation of reference concentration ( 0 ) was applied in a multiclass way to the riverbed PSD, and it was assumed that the size fractions did not influence each other and there was a uniform sediment density for all grain sizes (2.65 g cm -3 ). In this formulation, ( 0 ) is a function of the dimensionless grain 20 size * , the local Shields parameter and of the critical Shields parameter for the inception of transport (Camenen et al, 2014):…”

Section: Predicting From the Riverbed Psdmentioning

confidence: 99%

An index concentration method for suspended load monitoring in large rivers of the Amazonian foreland

Santini¹,

Camenen²,

Coz³

et al. 2019

Preprint

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Because increasing climatic variability and anthropic pressures have affected the sediment dynamics of large tropical rivers, long-term sediment concentration series have become crucial for understanding the related socio-economic and environmental impacts. For operational and cost rationalization purposes, index concentrations are often sampled in the flow and used as a surrogate of the cross-sectional average concentration. However, in large rivers where suspended sands are responsible for vertical concentration gradients, this index method can induce large uncertainties in the matter fluxes. 20Assuming that physical laws describing the suspension of grains in turbulent flow are valid for large rivers, a simple formulation is derived to model the ratio ( ) between index and average concentrations. The model is validated using an exceptional dataset (1330 water samples, 249 concentration profiles, 88 particle size distributions (PSDs) and 494 discharge measurements) that was collected between 2010 and 2017 in the Amazonian foreland. The prediction requires the estimation of the Rouse number ( ), which summarizes the balance between the suspended particle settling and the turbulent lift, weighted 25 by the ratio of sediment to eddy diffusivity ( ). Two particle size groups, washload and sand, were considered to evaluate .Discrepancies were observed between the evaluated and measured , that were attributed to biases related to the settling and shear velocities estimations, but also to diffusivity ratios ≠ 1. An empirical expression taking into account these biases was then formulated to predict accurate estimates of , then (∆ = ±0.03) and finally .The proposed model is a powerful tool for optimizing the concentration sampling. It allows for detailed uncertainty analysis 30 on the average concentration derived from an index method. Finally, this model can be coupled with remote sensing and hydrological modeling to serve as a step toward the development of an integrated approach for assessing sediment fluxes in poorly monitored basins.Earth Surf. Dynam. Discuss., https://doi.

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“…In cases for which it is relevant to assume an equilibrium state between the sediment supply to the river and the transport capacity of the flow, the bed-load and graded suspension fluxes can also be evaluated from semi empirical formulae taking into account local hydraulic conditions. An important interest of rating curves using such physically-based model is that one can compute yearly sediment fluxes and long term sediment budgets based on statistical discharges and/or discharge time series [4]. Comparatively, the part of solid fluxes corresponding to washload appears relatively easier to measure in the field because the concentration in fine sediments across the flow section is rather uniform.…”

Section: Solid Fluxes Measurementsmentioning

confidence: 99%

Toward an operational approach for the characterization and modelling of fine sediments dynamics in reservoirs

Peteuil¹,

Jodeau

Linares

et al. 2018

E3S Web Conf.

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Achieving a sustainable management of sediment fluxes in existing or proposed reservoirs is a challenging but essential requirement for dam operators. Such objective is of utmost importance to avoid sedimentation-related consequences. Numerical modelling is of great interest to understand the flow and sediment dynamics in a reservoir, to simulate the long-term evolution of sediment deposits and to evaluate the efficiency of various management strategies. This paper presents recent case studies, which validate the feasibility and relevancy of such technical option. The progresses obtained on essential stages of the numerical modelling of sediments dynamics in reservoirs are particularly emphasized. Concerning the distribution of deposits, a promising field method based on an optimum combination of direct samplings with acoustic measurements and video auscultations is detailed. Feedbacks are then provided concerning an innovative device deployed in the field for a direct measurement of the settling velocity. Issues about the assessment of calibration parameters are also addressed in this communication. Lab experiments performed on deposits sampled in several reservoirs provide practical guidance to evaluate the erosion parameters of sediments. Finally, several examples of sediment dynamics modelling in reservoirs including both cohesive and non-cohesive sediment are presented.

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A simple physically-based model for predicting sand transport dynamics in the Lower Mekong River

Cited by 8 publications

References 4 publications

Rainfall control on Amazon sediment flux: synthesis from 20 years of monitoring

Rainfall control on Amazon sediment flux: synthesis from 20 years of monitoring

An index concentration method for suspended load monitoring in large rivers of the Amazonian foreland

Toward an operational approach for the characterization and modelling of fine sediments dynamics in reservoirs

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