Evaluating Tools and Technologies for Monitoring Baleen Whales During Offshore Wind Foundation Installation

Szesciorka, A.; Severy, M.; Ampela, K.; Hein, C.; Richlen, M.; Haxel, J.; Clerc, J. (2025). Evaluating Tools and Technologies for Monitoring Baleen Whales During Offshore Wind Foundation Installation. Report by Pacific Northwest National Laboratory and National Renewable Energy Laboratory for the U.S. Department of Energy.

@techreport{Szesciorka-2025-2080470,
author = {Szesciorka, A and Severy, M and Ampela, K and Hein, C and Richlen, M and Haxel, J and Clerc, J},
title = {Evaluating Tools and Technologies for Monitoring Baleen Whales During Offshore Wind Foundation Installation},
institution = {California Ocean Alliance},
year = {2025},
month = {jan},
number = {PNNL-37249 NREL/TP-5000-92549},
keywords = {Wind Energy, Fixed Offshore Wind, Noise, Marine Mammals, Cetaceans},
}

TY - RPRT
TI - Evaluating Tools and Technologies for Monitoring Baleen Whales During Offshore Wind Foundation Installation
AU - Szesciorka, A
AU - Severy, M
AU - Ampela, K
AU - Hein, C
AU - Richlen, M
AU - Haxel, J
AU - Clerc, J
AB - Offshore wind energy facilities are being planned and installed in United States waters in accordance with regulations and processes designed to avoid negative effects on federally-protected baleen whales and other marine mammals. Potential impacts to baleen whales associated with offshore wind farm construction are of particular concern because of their conservation status, the overlap of their habitat with existing and planned offshore wind energy facilities, and their expected sensitivity to low-frequency sounds, such as those produced during pile driving. Therefore, this report focuses on monitoring technologies capable of detecting this species group. The ability to install offshore wind turbine foundations in low- to no-visibility conditions is of interest to developers because it increases construction flexibility and reduces the duration of in-water foundation installation activities. Several available monitoring technologies have the potential to detect whales in low- and no-light conditions (e.g., passive acoustic monitoring systems, infrared camera systems), but no standardized approach exists to characterize the functional performance of these technologies. The Pacific Northwest National Laboratory and the National Renewable Energy Laboratory, with support from the U.S. Department of Energy and input from the Bureau of Ocean Energy Management and the National Oceanic and Atmospheric Administration, assessed the current state of technologies and methods for monitoring baleen whales in low- and no-light conditions during installation of fixed-bottom turbine foundations. In developing the report, the labs engaged with stakeholders during public workshops, organized by the Regional Wildlife Science Collaborative, and recruited subject matter experts for interviews and peer review. Based on this feedback, the labs then developed technology-specific reviews and a standardized framework to help guide offshore wind energy project developers and technology designers as they navigate these technological challenges. The report provides documentation about key performance metrics, a synthesis of the state of monitoring technology performance, a potential framework to standardize technology characterization, and recommendations for research, development, and deployment. Although this report is specific to baleen whale monitoring technologies during installation of fixed-bottom wind turbine foundations, the monitoring technologies and the proposed framework could be applicable to other marine mammal species and aspects of offshore wind energy development, with the caveat that other marine mammal species have behaviors (e.g., surfacing and calling rates) that differ from baleen whales and may require a modified approach.ReferencesThe table below contains the relevant literature to this report.TitleAuthorDateContent TypeTechnologyStressorReceptorMarine mammal census using space satellite imageryAbileah, R.2002Journal Article Marine MammalA Convolutional Neural Network for Automated Detection of Humpback Whale Song in a Diverse, Long-Term Passive Acoustic DatasetAllen, A. N.; Harvey, M.; Harrell, L.; et al.2021Journal Article Marine Mammals, CetaceansBest Practices Guidelines for Cetacean TaggingAndrews, R. D.; Baird, R. 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DA - 2025/01//
PY - 2025
SP - 105
PB - California Ocean Alliance
SN - PNNL-37249 NREL/TP-5000-92549
LA - English
KW - Wind Energy
KW - Fixed Offshore Wind
KW - Noise
KW - Marine Mammals
KW - Cetaceans
ER -