@article{fdi:010076072,
  title = {{A}n index concentration method for suspended load monitoring in large rivers of the {A}mazonian foreland},
  author = {{S}antini, {W}illiam and {C}amenen, {B}. and {L}e {C}oz, {J}. and {V}auchel, {P}hilippe and {G}uyot, {J}ean-{L}oup and {L}avado, {W}. and {C}arranza, {J}. and {P}aredes, {M}. {A}. and {A}revalo, {J}. {J}. {P}. and {A}revalo, {N}. and {V}illar, {R}. {E}. and {J}ulien, {F}. and {M}artinez, {J}ean-{M}ichel},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ecause 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 socioeconomic and environmental impacts. {F}or operational and cost rationalization purposes, index concentrations are often sampled in the flow and used as a surrogate of the cross-sectional average concentration. {H}owever, in large rivers where suspended sands are responsible for vertical concentration gradients, this index method can induce large uncertainties in the matter fluxes. {A}ssuming 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 (alpha) between the depth-averaged and index concentrations. {T}he model is validated using an exceptional dataset (1330 water samples, 249 concentration profiles, 88 particle size distributions and 494 discharge measurements) that was collected between 2010 and 2017 in the {A}mazonian foreland. {T}he alpha prediction requires the estimation of the {R}ouse number ({P}), which summarizes the balance between the suspended particle settling and the turbulent lift, weighted by the ratio of sediment to eddy diffusivity (beta). {T}wo particle size groups, fine sediments and sand, were considered to evaluate {P}. {D}iscrepancies were observed between the evaluated and measured {P}, which were attributed to biases related to the settling and shear velocities estimations, but also to diffusivity ratios beta not equal 1. {A}n empirical expression taking these biases into account was then formulated to predict accurate estimates of beta, then {P} ({D}elta {P} = +/- 0.03) and finally alpha. {T}he proposed model is a powerful tool for optimizing the concentration sampling. {I}t allows for detailed uncertainty analysis on the average concentration derived from an index method. {F}inally, this model could likely 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.},
  keywords = {{AMAZONE}},
  booktitle = {},
  journal = {{E}arth {S}urface {D}ynamics},
  volume = {7},
  numero = {2},
  pages = {515--536},
  ISSN = {2196-6311},
  year = {2019},
  DOI = {10.5194/esurf-7-515-2019},
  URL = {https://www.documentation.ird.fr/hor/fdi:010076072},
}