An index concentration method for suspended load monitoring in large rivers of the Amazonian foreland
<p>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 socioeconomic and environmental impacts. For operational and cost rationali...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-06-01
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| Series: | Earth Surface Dynamics |
| Online Access: | https://www.earth-surf-dynam.net/7/515/2019/esurf-7-515-2019.pdf |
| Summary: | <p>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 socioeconomic 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.</p>
<p>Assuming 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 (<span class="inline-formula"><i>α</i></span>) between the depth-averaged and index concentrations. The 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 Amazonian
foreland. The <span class="inline-formula"><i>α</i></span> prediction requires the estimation of the Rouse
number (<span class="inline-formula"><i>P</i></span>), which summarizes the balance between the suspended particle
settling and the turbulent lift, weighted by the ratio of sediment to eddy
diffusivity (<span class="inline-formula"><i>β</i></span>). Two particle size groups, fine sediments and sand,
were considered to evaluate <span class="inline-formula"><i>P</i></span>. Discrepancies were observed between the
evaluated and measured <span class="inline-formula"><i>P</i></span>, which were attributed to biases related to the
settling and shear velocities estimations, but also to diffusivity ratios
<span class="inline-formula"><i>β</i>≠1</span>. An empirical expression taking these biases into account was
then formulated to predict accurate estimates of <span class="inline-formula"><i>β</i></span>, then <span class="inline-formula"><i>P</i></span>
(<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M10" display="inline" overflow="scroll" dspmath="mathml"><mrow><mi mathvariant="normal">Δ</mi><mi>P</mi><mo>=</mo><mo>±</mo><mn mathvariant="normal">0.03</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="60pt" height="10pt" class="svg-formula" dspmath="mathimg" md5hash="46e0cf6c6e5a2896f12b812199c7323d"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="esurf-7-515-2019-ie00001.svg" width="60pt" height="10pt" src="esurf-7-515-2019-ie00001.png"/></svg:svg></span></span>) and finally <span class="inline-formula"><i>α</i></span>.</p>
<p>The proposed model is a powerful tool for optimizing the concentration
sampling. It allows for detailed uncertainty analysis on the average
concentration derived from an index method. Finally, 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.</p> |
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| ISSN: | 2196-6311 2196-632X |