Assessment of Ship-Generated Underwater Noise in the Shallow Lithuanian Marine Klaipėda Port Through Measurements and Modelling

Abstract Mapping of shipping underwater noise purposed for environmental impact assessments and to forecast noise effects on aquatic life incorporate source spectral models. These models published in scientific literature updated regularly, although these may have limitations and may depend on the variables stored in the ship’s automated identification system data, tied to specific locations i.e., ship speeds and their lengths. Regarding these limitations, it is crucial to assess the possibility of model application in the research area. In this paper the results of evaluation of four different noise models in the shallow Lithuanian marine harbor presented. The results acquired using “ECHO-JOMOPANS” model and the updated “Research Ambient Directionality Model” revealed good correlation with measurement results, although these two models have a different dependency on the ships parameters. The benchmarked “ECHO-JOMOPANS” model incorporates the reference spectrum, having the dependency on the sound frequency, ship’s speed, its length and ships database related reference speeds and ships lengths. In contrast, an updated “Research Ambient Directionality Model” is a modification of an original model, having the dependency only on the sound frequency, ship’s speed, and length.

Authors

Institutions

Publication Details

Journal
Brazilian Archives of Biology and Technology
Published
2025-01-01
DOI
https://doi.org/10.1590/1678-4324-2025230749
Primary Topic
Underwater Acoustics Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessment of Ship-Generated Underwater Noise in the Shallow Lithuanian Marine Klaipėda Port Through Measurements and Modelling

Donatas Bagočius, Aleksas Narščius
Brazilian Archives of Biology and Technology
Underwater Acoustics Research
article

Assessment of Ship-Generated Underwater Noise in the Shallow Lithuanian Marine Klaipėda Port Through Measurements and Modelling

Donatas Bagočius, Aleksas Narščius
article en

Abstract

Abstract Mapping of shipping underwater noise purposed for environmental impact assessments and to forecast noise effects on aquatic life incorporate source spectral models. These models published in scientific literature updated regularly, although these may have limitations and may depend on the variables stored in the ship’s automated identification system data, tied to specific locations i.e., ship speeds and their lengths. Regarding these limitations, it is crucial to assess the possibility of model application in the research area. In this paper the results of evaluation of four different noise models in the shallow Lithuanian marine harbor presented. The results acquired using “ECHO-JOMOPANS” model and the updated “Research Ambient Directionality Model” revealed good correlation with measurement results, although these two models have a different dependency on the ships parameters. The benchmarked “ECHO-JOMOPANS” model incorporates the reference spectrum, having the dependency on the sound frequency, ship’s speed, its length and ships database related reference speeds and ships lengths. In contrast, an updated “Research Ambient Directionality Model” is a modification of an original model, having the dependency only on the sound frequency, ship’s speed, and length.

Brazilian Archives of Biology and TechnologyVol. 68
Klaipėda University (LT), Klaipėdos valstybinė kolegija / Higher Education Institution (LT)
Openalex Percentile: Top 90%
Underwater Acoustics Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.