Light Attenuation Model for Waters: Linear and Nonlinear Dependencies on Suspended Sediment
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Volume 143, Issue 9
Abstract
Diffuse optical sensors estimate attenuation of natural light (solar irradiance) by measuring its vertical distribution in the water column, and the sensors are useful for estimating both suspended sediment concentration and light availability for organisms in rivers, lakes, and estuaries. However, currently there is a lack of reliable light attenuation models that account for particle size and density, have widely applicable dimensionless form, and show usefulness for coupling with sensors. To overcome these deficiencies, the authors revisit earlier dimensional analysis and relax a number of assumptions to provide a more robust and applicable dimensionless number for light attenuation by sediments. Second, the authors formulate an analytical light attenuation model that is found to be in general agreement with the dimensionless model and provides a theoretical description of the controlling dimensionless number. Third, the authors perform a meta-analysis for a wide range of data sets in diverse waters to test the model across a range of particle sizes and sediment concentrations from 9 to 90 μm and respectively. The dimensionless light attenuation number clearly divides the light attenuation data into two categories: one linear and one with nonlinear dependence on suspended sediment concentration, both of which collapse the respective data sets. About 90% of the data displays linear properties, and the linear empirical coefficient found for the dimensionless model agrees almost exactly with the equation derived with the analytical model. Results that exhibit nonlinearity when scaled with the dimensionless number suggest the influence of secondary processes upon attenuation that most likely arise from the measurement methods for sediment and light properties. The authors recommend ways to avoid nonlinearity, when it can be avoided, that may be followed in future research to enhance the usefulness of sensors and sensor networks.
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Acknowledgments
We would like to thank two anonymous reviewers whose comments and suggested revisions greatly improved the quality of this paper. The authors would also like to thank the Editorial Board at JHE for managing the paper. The authors would like to thank all of the people who worked on this project, including both the graduate and undergraduate students that were part of the NSFVOEIS project. The authors would like to thank Dr. Agouridis for help use of her particle size analyzer. The authors acknowledge National Science Foundation project #0918856 and the University of Kentucky Civil Engineering Department for partial financial support of the students.
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Journal of Hydraulic Engineering
Volume 143 • Issue 9 • September 2017
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©2017 American Society of Civil Engineers.
History
Received: Aug 17, 2016
Accepted: Mar 7, 2017
Published online: Jun 16, 2017
Published in print: Sep 1, 2017
Discussion open until: Nov 16, 2017
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