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Environmental Science and Pollution Research

, Volume 26, Issue 1, pp 959–974 | Cite as

Using Shannon entropy to model turbulence-induced flocculation of cohesive sediment in water

  • Zhongfan Zhu
  • Dingzhi PengEmail author
Research Article
  • 60 Downloads

Abstract

Turbulence-induced flocculation of cohesive fine-grained sediment plays an important role in the transport characteristics of pollutants and nutrients absorbed on the surface of sediment in estuarine and coastal waters via the complex processes of sediment transport, deposition, resuspension and consolidation. In this study, the concept of Shannon entropy based on probability is applied to modelling turbulence-induced flocculation of cohesive sediment in water. Using the hypothesis regarding the cumulative distribution function, the function of floc size with flocculation time is derived by assuming a characteristic floc size as a random variable and maximizing the Shannon entropy, subject to certain constraints. The Shannon entropy-based model is capable of modelling the variation in floc size as the flocculation time progresses from zero to infinity. The model is tested against some existing experimental data from the literature and against a few deterministic mathematical models. The model yields good agreement with the observed data and yields better prediction accuracy than the other models. The parameter that has been incorporated into the model exhibits an empirical power-law relationship with the flow shear rate. An empirical model formulation is proposed, and it exhibits high prediction accuracy when applied to existing experimental data.

Keywords

Shannon entropy Probability distribution Flocculation model Cohesive sediment 

Notes

Funding information

This work is supported by the National Natural Science Foundation of China (51509004). This study is also supported by the Open Research Foundation of Key Laboratory of the Pearl River Estuarine Dynamics and Associated Process Regulation, Ministry of Water Resources, China ([2018]KJ01).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Water SciencesBeijing Normal UniversityBeijingChina

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