2025_programme: A STATISTICAL MODEL FOR ASSESSING UNDERWATER RADIATED NOISE FROM SMALL VESSELS

• Day: June 19, Thursday
    Location / Time: A. TERPSIHORI at 18:20-18:40
• Last minutes changes: Cancelled
• Session: 27. Radiated noise from Ships and Surface Platforms
  Organiser(s): N/A
  Chairperson(s): Andreas Grech La Rosa
• Lecture: A STATISTICAL MODEL FOR ASSESSING UNDERWATER RADIATED NOISE FROM SMALL VESSELS
  Paper ID: 2324
  Author(s): Mark Shipton
  Presenter: Mark Shipton
  Abstract: Underwater Radiated Noise (URN) from vessels has become a significant area of focus due to its potentially adverse effects on marine life. In order to assess the impact of URN from vessels on marine habitats, acoustic monitoring sensors are deployed; however, such an approach is costly, time-consuming, and can be done only in reachable areas. Statistical modeling of URN from vessels based on the operational characteristics of the vessel (e.g., type, speed, size, draft) is an alternative for assessing the expected URN intensity of vessels in areas not monitored by acoustic sensors.In this paper, we model the distribution of vessels’ URN to evaluate the likelihood of the noise intensity extending beyond the level considered harmful to marine life. We use the general Gaussian distribution function to robustly match the legacy data of vessels’ URN. We demonstrate the model over a database of small vessels (motorboats, yachts, fishing vessels, and ferries), which we collected in Šibenik, Croatia. Based on a testing set, not used for the distribution analysis, the model shows accuracy in predicting the URN level. This shows a potential for creating underwater noise maps based on probabilistic evaluation.
• Corresponding author: Mr Mark Shipton
  Affiliation: University of Haifa, School of Marine Sciences
  Country: Israel