Development of an inland waterway traffic noise prediction model considering water surface adsorption and embankment shielding influences

  • B. L. Dai
  • N. Sheng
  • Y. L. He
  • F. H. Mu
  • J. M. Xu
  • A. F. Zhu
Original Paper


This paper proposed an improved prediction method of inland waterway vessel noise considering the effects of water surface adsorption and embankment shielding. The method was established on the basis of the UK Calculation of Road Traffic Noise (CoRTN) method, and the effects of water surface adsorption and embankment shielding were integrated into the governing equations. The developed method was validated using the data measured at the 40 monitoring points along Da Yunhe Channel in China. The results showed that the improved method had a higher accuracy and precision than that of the unmodified CoRTN method. The predicted noise exposure level by the unmodified CoRTN method correlated with the measured values with an R2 of 0.74569, which was enhanced to 0.86457 by the improved method. The current research is the prime to forecast river vessel noise level on the basis of the CoRTN method considering water surface adsorption and embankment shielding influences in China. It is expected that the modified method could be a new tool for estimating vessel noise effect on the inhabitant around the urban inland waterways.


Vessel noise Water surface Embankment Inland waterway 



This research was supported by the Natural Science Foundation of Jiangsu Province of China (BK20160430), the Project Funded by China Postdoctoral Science Foundation (2016M591757), the Jiangsu Planned Projects for Postdoctoral Research Funds of China (1601179C), and Huaian Key Research and Development (Social Development) Program of China (HAS201601).

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest.


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Copyright information

© Islamic Azad University (IAU) 2019

Authors and Affiliations

  1. 1.Jiangsu Engineering Laboratory for Environment Functional Materials, Jiangsu Collaborative Innovation Center of Regional Modern Agriculture and Environmental Protection, School of Chemistry and Chemical EngineeringHuaiyin Normal UniversityHuaianPeople’s Republic of China
  2. 2.Department of Decision SciencesMacau University of Science and TechnologyTaipaPeople’s Republic of China
  3. 3.Faculty of Geosciences and Environmental EngineeringSouthwest Jiaotong UniversityChengduPeople’s Republic of China

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