Comparing Above and Underwater Visibility of Fluorescent Quinine-Based Liquid and Solid Tracers to Estimate Suspended Sediment Concentrations Under Low Luminosity Conditions

Soheil Zehsaz*, João L.M.P.de Lima, M. Isabel P.de Lima, Thayná A.B. Almeida, Rui L.Pedroso de Lima, Abelardo A.de A. Montenegro

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

While exploring the use and visibility of fluorescent tracers for estimating flow velocities under varying water turbidity, this study introduces a technique for estimating suspended sediment concentration (SSC) in water. Laboratory and field experiments were conducted using a dual above/underwater optical camera monitoring system to measure and compare the visibility (brightness intensity) of fluorescent tracers applied into water under varying SSC loads. Based on the fluorescent properties of quinine under low luminosity conditions, a quinine solution, in both liquid and solid (ice cube) states, was applied to the water surface. Its visibility was recorded using the monitoring system, and brightness intensity was quantified using image processing techniques such as grayscale conversion, object segmentation, and pixel intensity extraction. Results indicate that the tracer brightness intensity decreases as SSC loads increase, with the underwater camera recording lower visibility than the above-water camera, particularly at higher SSC loads. Empirical regression equations were developed to describe the relationship between the tracer brightness intensity recorded by the underwater camera and the SSC loads. These findings suggest the ability of the presented monitoring system, using quinine solution in both liquid and solid states, along with an underwater camera, to estimate a relevant range of SSC loads under low luminosity conditions.

Original languageEnglish
Article number10
JournalSensing and Imaging
Volume26
Issue number1
DOIs
Publication statusPublished - 2025

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

Keywords

  • Aquatic environment
  • Environmental monitoring
  • Hydrological monitoring
  • Image processing
  • Visualization techniques

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