Name: Nathan Merchant
Address: Centre for Environment Fisheries and Aquaculture Science,
Pakefield Road, Lowestoft, NR33 0HT, UK
Assessment of underwater noise is increasingly required by regulators of development projects in marine and freshwater habitats, and noise pollution can be a constraining factor in the consenting process. Noise levels arising from the proposed activity are modelled and the potential impact on species of interest within the affected area is then evaluated. Although there is considerable uncertainty in the relationship between noise levels and impacts on aquatic species, the science underlying noise modelling is well understood. Nevertheless, many environmental impact assessments (EIAs) do not reflect best practice, and stakeholders and decision makers in the EIA process are often unfamiliar with the concepts and terminology that are integral to interpreting noise exposure predictions. In this paper, we review the process of underwater noise modelling and explore the factors affecting predictions of noise exposure. Finally, we illustrate the consequences of errors and uncertainties in noise modelling, and discuss future research needs to reduce uncertainty in noise assessments.
Collection and analysis of data from the Cromarty Firth were funded through the DECC SEA Programme using equipment purchased with the support of Moray Offshore Renewables Ltd.
Cromarty Firth, Scotland
- To raise awareness of issues in model predictions of noise
- To promote best practices in noise impact assessments
- To enable more informed EIA processes for noise-generating developments
Errors and uncertainties in noise modelling can lead to significant pitfalls in the EIA process. Underestimates of noise exposure lead to an underestimation of the risk of injury and disturbance to marine life. This is of particular concern in the vicinity of the noise source, where these impacts are most likely to be acute. On the other hand, if noise exposure is overestimated over a wide area, otherwise acceptable operations could be denied regulatory consent on the basis of inaccurate predictions. This paper has reviewed and assessed the many factors that affect predictions of noise exposure in an EIA context, with the aim of clarifying and summarising the science underlying noise modelling for the benefit of regulators, stakeholders, and practitioners. To allow an informed appraisal of the risk of noise-related impact, it is then critical that EIAs clearly state the underlying assumptions and scientific basis for noise exposure predictions. This applies particularly to the characterisation of the noise source, to the modelling of propagation loss, and to uncertainties in the input data relied upon in the model.
Farcas, A.; Thompson, P.; Merchant, N. (2016). Underwater Noise Modelling for Environmental Impact Assessment. Environmental Impact Assessment Review, 57, 114-122. https://tethys.pnnl.gov/publications/underwater-noise-modelling-environmental-impact-assessment