Shetland Tidal Array Monitoring Report April 2022 to July 2023

TY - RPRT
TI - Shetland Tidal Array Monitoring Report April 2022 to July 2023
AU - Nova Innovation
AB - This report is provided in support of discharge of conditions attached to the following licences for Nova Innovation’s Shetland Tidal Array in Bluemull Sound:Marine Licence MS-00009110, issued by Marine Scotland Licensing Operations Team on behalf of the Scottish Ministers, under the Marine (Scotland) Act 2020.Shetland Islands Council (SIC) Works Licence 2022/015/WL, issued by Shetland Islands Council under the Zetland County Council Act 1974.In the reporting period covered by this report (April 2022 to July 2023), the programme of environmental monitoring for the Shetland Tidal Array comprised the following two key activities:Land-based diving bird and marine mammal observation surveys in Bluemull Sound.Subsea monitoring using turbine-mounted optical video cameras.Combined, these methods gather data to understand the likely nature and consequences of any nearfield interactions between turbines in the array and marine wildlife, with a focus on mammals and diving birds, due to their protected status.This report builds on previous monitoring reports produced by Nova for the Shetland Tidal Array (Nova Innovation, 2017; 2021a; 2021b; 2022b; 2022c). It presents the results from analysis of environmental monitoring data gathered between April 2022 and July 2023 (the ‘reporting period’). This includes analysis of data gathered during 108 hours of land-based surveys and around 40 GB of subsea video footage from subsea monitoring using turbine-mounted cameras.A key focus of effort during this reporting period has been exploring the development of tools to automate processing and analysis of subsea video, which to date has required resource intensive and time-consuming manual review. A study to develop a model based on machine learning for processing and analysing the subsea video data is presented in this report, as well as ongoing work to refine the model and apply it to Nova’s subsea video data.
DA - 2023/07//
PY - 2023
SP - 57
SN - STA-002
UR - https://marine.gov.scot/sites/default/files/231031_nova_sta_monitoring_report_final_md-lot_sic.pdf
LA - English
KW - Marine Energy
KW - Tidal
KW - Attraction
KW - Collision
KW - Habitat Change
KW - Birds
KW - Seabirds
KW - Waterfowl
KW - Fish
KW - Pelagic Fish
KW - Marine Mammals
KW - Cetaceans
KW - Pinnipeds
ER -

Export Citation to RIS

Abstract

This report is provided in support of discharge of conditions attached to the following licences for Nova Innovation’s Shetland Tidal Array in Bluemull Sound:

Marine Licence MS-00009110, issued by Marine Scotland Licensing Operations Team on behalf of the Scottish Ministers, under the Marine (Scotland) Act 2020.
Shetland Islands Council (SIC) Works Licence 2022/015/WL, issued by Shetland Islands Council under the Zetland County Council Act 1974.

In the reporting period covered by this report (April 2022 to July 2023), the programme of environmental monitoring for the Shetland Tidal Array comprised the following two key activities:

Land-based diving bird and marine mammal observation surveys in Bluemull Sound.
Subsea monitoring using turbine-mounted optical video cameras.

Combined, these methods gather data to understand the likely nature and consequences of any nearfield interactions between turbines in the array and marine wildlife, with a focus on mammals and diving birds, due to their protected status.

This report builds on previous monitoring reports produced by Nova for the Shetland Tidal Array (Nova Innovation, 2017; 2021a; 2021b; 2022b; 2022c). It presents the results from analysis of environmental monitoring data gathered between April 2022 and July 2023 (the ‘reporting period’). This includes analysis of data gathered during 108 hours of land-based surveys and around 40 GB of subsea video footage from subsea monitoring using turbine-mounted cameras.

A key focus of effort during this reporting period has been exploring the development of tools to automate processing and analysis of subsea video, which to date has required resource intensive and time-consuming manual review. A study to develop a model based on machine learning for processing and analysing the subsea video data is presented in this report, as well as ongoing work to refine the model and apply it to Nova’s subsea video data.