Multi-purpose offshore wind: A case study on integrating passive acoustic surveillance into infrastructure in the North Sea

This study investigates the feasibility and effectiveness of integrating acoustic sensors into offshore renewable energy infrastructure for multi-purpose underwater monitoring, with a focus on detecting illegal fishing activity. Two North Sea sites (Dogger Bank and Buchan Deep) were analysed to assess acoustic detection capabilities over a frequency bandwidth from $100\mathrm{Hz}$ to $10\mathrm{kHz}$. The main uncertainties in the modelling stem from limited knowledge of the sediment properties, and from the range of possible source levels. The work could therefore be expanded by considering a stochastic approach to these uncertainties if a specific site was taken forward for trials of the monitoring method. The results indicate that a single hydrophone attached to the turbine substructure can detect the activity of a fishing vessel within a range of 300 to $400m$ under average conditions, extending up to 2 to $4\mathrm{km}$ under favourable conditions. Optimal detection frequencies were typically in the range of $500\mathrm{Hz}$ to $5\mathrm{kHz}$. Detection performance is strongly influenced by ambient noise levels and sediment composition, while water depth has minimal impact. Seasonal variations significantly affect sound propagation, with a downward-refracting sound speed profile in the summer and attenuating sediments increasing propagation loss. This increased loss is offset by reduced ambient noise due to calmer sea states, resulting in longer detection ranges during the summer. The optimistic detection ranges align with or exceed typical turbine spacing, suggesting that a hydrophone-equipped wind farm could effectively monitor fishing activity across its footprint. Coverage would not extend beyond its boundaries into adjacent Marine Protected Areas.