Assessing the Impacts of Marine-Hydrokinetic Energy (MHK) Device Noise on Marine Systems by Using Underwater Acoustic Models as Enabling Tools



This chapter describes the utilization of underwater acoustic models for the evaluation of marine-system noise impacts associated with the installation and operation of marine-hydrokinetic energy (MHK) devices, particularly in coastal oceans. Coastal environments are generally characterized by high spatial and temporal variabilities, which make them very complex acoustic environments. Underwater acoustic models serve as enabling tools for assessing noise impacts on marine systems by generating analytical metrics useful in managing coastal resources. This review is set in the context of an underwater soundscape, which is a combination of sounds that characterize, or arise from, an ocean environment. The study of a soundscape is sometimes referred to as acoustic ecology. Disruption of the natural acoustic environment results in noise pollution : The potential effects of anthropogenic sound sources on marine mammals and fish that could include auditory damage. Changes in the ocean soundscape have also been driven by natural factors arising from climate change, including ocean acidification. The field of underwater acoustics enables us to observe and predict the behavior of this soundscape and the response of the natural acoustic environment to noise pollution. Underwater acoustics entails the development and employment of acoustical methods to image underwater features, to communicate information via the oceanic waveguide, or to measure oceanic properties. Modeling tools traditionally used in underwater acoustics have undergone a necessary transformation to respond to the rapidly changing requirements imposed by this dynamic soundscape. Additional advances have been achieved using energy-flux techniques that can simplify the interpretation of sound-channel models. Nonintrusive measurement approaches include new acoustic-transmission options to minimize impacts on aquatic life. Applied underwater acoustic modeling technologies have further evolved over the past several years in response to new regulatory initiatives that have placed restrictions on the uses of sound in the ocean. The mitigation of marine-mammal endangerment is now an integral consideration in acoustic-system design, installation, and operation. Marine-mammal protection research has focused on simulating anthropogenic sound sources including seismic-exploration activity, merchant shipping traffic , and a new generation of multistatic naval sonar systems. Additional sources derive from ocean-renewable energy resources, including the deployment of wind farms, tidal turbines , and wave-energy devices . Many underwater acoustic models presently used in environmental impact assessments consider only the sound-pressure component of sound, which is the means by which marine mammals hear; however, the primary mechanism by which fish and invertebrate species detect sound is through the particle-motion component of sound. To assist practitioners in the proper usage of acoustic models for assessing the impacts of MHK device noise on marine systems, selection guidance is provided for the current inventory of underwater acoustic propagation and noise models.


Ocean soundscape Acoustic propagation Ambient noise Coastal environments Marine-mammal protection Noise pollution Anthropogenic sound sources Shipping traffic Tidal turbines Wave-energy devices Wind-farm noise Mitigation measures Underwater acoustic networks Temporary threshold shift Permanent threshold shift Auditory evoked potentials 


  1. Andrew, R. K., Howe, B. M., Mercer, J. A., & Dzieciuch, M. A. (2002). Ocean ambient sound: Comparing the 1960s with the 1990s for a receiver off the California coast. Acoustic Research Letters Online, 3(2), 65–70.CrossRefGoogle Scholar
  2. Austin, M., Chorney, N., Ferguson, J., Leary, D., O’Neill, C., & Sneddon, H. (2009). Assessment of underwater noise generated by wave energy devices. Prepared by JASCO Applied Sciences on behalf of Oregon Wave Energy Trust. Technical Report, P001081-001, Version 1.0.Google Scholar
  3. Bass, S. J., & Hay, A. E. (1997). Ambient noise in the natural surf zone: Wave-breaking frequencies. IEEE Journal of Oceanic Engineering, 22, 411–424.CrossRefGoogle Scholar
  4. Carey, W. M., & Evans, R. B. (2011). Ocean ambient noise: Measurement and theory. New York: Springer.CrossRefGoogle Scholar
  5. Copping, A. E., & O’Toole, M. J. (2010). OES-IA annex IV: Environmental effects of marine and hydrokinetic devices. In Experts’ Workshop, September 27th–28th 2010, Clontarf Castle, Dublin, Ireland. Pacific Northwest National Laboratory, PNNL-20034. Prepared for the US Department of Energy under Contract DE-AC05-76RL01830, 64 pp.Google Scholar
  6. Etter, P. C. (2013). Underwater acoustic modeling and simulation (4th ed.). Boca Raton, Florida, USA: CRC Press.CrossRefMATHGoogle Scholar
  7. Farcas, A., Thompson, P. M., & Merchant, N. D. (2016). Underwater noise modelling for environmental impact assessment. Environmental Impact Assessment, 57, 114–122. doi: 10.1016/j.eiar.2015.11.012.CrossRefGoogle Scholar
  8. Felizardo, F. C., & Melville, W. K. (1995). Correlations between ambient noise and the ocean surface wave field. Journal of Physical Oceanography, 25, 513–532.CrossRefGoogle Scholar
  9. Finette, S. (2005). Embedding uncertainty into ocean acoustic propagation models. The Journal of the Acoustical Society of America, 117, 997–1000.CrossRefGoogle Scholar
  10. Finneran, J. J. (2015). Noise-induced hearing loss in marine mammals: A review of temporary threshold shift studies from 1996 to 2015. The Journal of the Acoustical Society of America, 138, 1702–1726.CrossRefGoogle Scholar
  11. Ikpekha, O. W., Soberon, F., Daniels, S. (2014). Modelling the propagation of underwater acoustic signals of a marine energy device using finite element method. In International Conference on Renewable Energies and Power Quality (ICREPQ’14), Cordoba, Spain.Google Scholar
  12. Lawson, J. W. (2009). The use of sound propagation models to determine safe distances from a seismic sound energy source. Department of Fisheries and Oceans, Canadian Science Advisory Secretariat, Res. Doc. 2009/060.Google Scholar
  13. Li, Y., & Ҫalişal, S. M. (2010). Numerical analysis of the characteristics of vertical axis tidal current turbines. Renewable Energy, 35, 435–442. doi: 10.1016/j.renene.2009.05.024.CrossRefGoogle Scholar
  14. Lloyd, T. P., Turnock, S. R., & Humphrey, V. F. (2011). Modelling techniques for underwater noise generated by tidal turbines in shallow waters. In Proceedings of 30th International Conference on Ocean, Offshore and Arctic Engineering (OMAE2011), Rotterdam, The Netherlands (pp. 1–9).Google Scholar
  15. Lurton, X. (1992). The range-averaged intensity model: A tool for underwater acoustic field analysis. IEEE Journal of Oceanic Engineering, 17, 138–149.CrossRefGoogle Scholar
  16. Lurton, X. (2002). An introduction to underwater acoustics: Principles and applications. New York: Springer.Google Scholar
  17. McDonald, M. A., Hildebrand, J. A., & Wiggins, S. M. (2006). Increases in deep ocean ambient noise in the Northeast Pacific west of San Nicolas Island California. The Journal of the Acoustical Society of America, 120, 711–718.CrossRefGoogle Scholar
  18. McDonald, M. A., Hildebrand, J. A., Wiggins, S. M., & Ross, D. (2008). A 50 year comparison of ambient ocean noise near San Clemente Island: A bathymetrically complex coastal region off Southern California. The Journal of the Acoustical Society of America, 124, 1985–1992.CrossRefGoogle Scholar
  19. National Research Council. (2003). Ocean noise and marine mammals. Washington: The National Academies Press.Google Scholar
  20. National Research Council. (2005). Marine mammal populations and ocean noise: Determining when noise causes biologically significant effects. Washington, DC: The National Academies Press.Google Scholar
  21. Orcutt, J. A. (1988). Ultralow- and very-low-frequency seismic and acoustic noise in the Pacific. The Journal of the Acoustical Society of America, 84(1), S194.Google Scholar
  22. Scrimger, J. A., Evans, D. J., McBean, G. A., Farmer, D. M., & Kerman, B. R. (1987). Underwater noise due to rain, hail, and snow. The Journal of the Acoustical Society of America, 81, 79–86.CrossRefGoogle Scholar
  23. Shyu, H.-J., & Hillson, R. (2006). A software workbench for estimating the effects of cumulative sound exposure in marine mammals. IEEE Journal of Oceanic Engineering, 31, 8–21.CrossRefGoogle Scholar
  24. Siderius, M., & Porter, M. B. (2006). Modeling techniques for marine-mammal risk assessment. IEEE Journal of Oceanic Engineering, 31, 49–60.CrossRefGoogle Scholar
  25. Todd, V. L. G., Todd, I. B., Gardiner, J. C., & Morrin, E. C. N. (2015). Marine mammal observer and passive acoustic monitoring handbook. Exeter, UK: Pelagic Publishing.Google Scholar
  26. von Benda-Beckmann, A. M., Wensveen, P. J., Kvadsheim, P. H., Lam, F.-P. A., Miller, P. J. O., Tyack, P. L., et al. (2014). Modeling effectiveness of gradual increases in source level to mitigate effects of sonar on marine mammals. Conservation Biology, 28(1), 119–128. doi: 10.1111/cobi.12162.CrossRefGoogle Scholar
  27. Weston, D. E. (1971). Intensity-range relations in oceanographic acoustics. Journal of Sound and Vibration, 18, 271–287.CrossRefGoogle Scholar
  28. Weston, D. E. (1980a). Acoustic flux formulas for range-dependent ocean ducts. The Journal of the Acoustical Society of America, 68, 269–281.CrossRefMATHGoogle Scholar
  29. Weston, D. E. (1980b). Acoustic flux methods for oceanic guided waves. The Journal of the Acoustical Society of America, 68, 287–296.CrossRefMATHGoogle Scholar
  30. Zykov, M. (2013). Underwater sound modeling of low energy geophysical equipment operations. JASCO Document 00600, Version 2.0. Prepared by JASCO Applied Sciences for CSA Ocean Sciences Inc.Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Northrop Grumman CorporationBaltimoreUSA

Personalised recommendations