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Estimation of mud and sand fractions and total concentration from coupled optical-acoustic sensors
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  • Duc Anh Tran,
  • Mathias Jacquet,
  • Stuart Grant Pearson,
  • B. C. van Prooijen,
  • Romaric Verney
Duc Anh Tran
Royal Belgian Institute of Natural Sciences

Corresponding Author:[email protected]

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Mathias Jacquet
Ifremer
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Stuart Grant Pearson
Delft University of Technology
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B. C. van Prooijen
Delft University of Technology
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Romaric Verney
IFREMER
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Abstract

Optical and acoustic sensors have been widely used in laboratory experiments and field studies to investigate suspended particulate matter concentration and particle size over the last four decades. Both methods face a serious challenge as laboratory and in-situ calibrations are usually required. Furthermore, in coastal and estuarine environments, the coexistence of mud and sand often results in multimodal particle size distributions, amplifying erroneous measurements. This paper proposes a new approach of combining a pair of optical-acoustic signals to estimate the total concentration and sediment composition of a mud/sand mixture in an efficient way without an extensive calibration. More specifically, we first carried out a set of 54 bimodal size regime experiments to derive empirical functions of optical-acoustic signals, concentrations, and mud/sand fractions. The functionalities of these relationships were then tested and validated using more complex multimodal size regime experiments over 30 optical-acoustic pairs of 5 wavelengths (420, 532, 620, 700, 852 nm) and 6 frequencies (0.5, 1, 2, 4, 6, 8 MHz). In the range of our data, without prior knowledge of particle size distribution, combinations between optical wavelengths 620-700 nm and acoustic frequencies 4-6 MHz predict mud/sand fraction and total concentration with the variation < 10% for the former and < 15% for the later. This approach therefore enables the robust estimation of suspended sediment concentration and composition, which is particularly useful in cases where calibration data is insufficient.
22 Nov 2023Submitted to ESS Open Archive
22 Nov 2023Published in ESS Open Archive