Monitoring Ulva prolifera to prevent cooling water intake blockages at nuclear power plants using remote sensing

In recent decades, coastal nuclear power plants (NPPs) have frequently encountered blockages of their cooling water intake caused by aquatic plants, resulting in significant safety and economic risks. In this study, remote sensing technology is used to dynamically monitor Ulva prolifera in the Yello...

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Main Authors: Haiting Wang, Xueqiang Zhu, Yanyan Cui, Hongtao Ai, Shuai Cai, Mengting Li, Jianying Wang
Format: Article
Language:English
Published: Taylor & Francis Group 2025-08-01
Series:International Journal of Digital Earth
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Online Access:https://www.tandfonline.com/doi/10.1080/17538947.2025.2512593
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Summary:In recent decades, coastal nuclear power plants (NPPs) have frequently encountered blockages of their cooling water intake caused by aquatic plants, resulting in significant safety and economic risks. In this study, remote sensing technology is used to dynamically monitor Ulva prolifera in the Yellow Sea as a case study, and its role in preventing cooling water intake blockages at NPPs is investigated. Data from GF-1 WFV, GF-4 PMI, CB04A, and Landsat 8 OLI satellite imagery from 2021 were analysed via NDVI and FAI algorithms to investigate the spatiotemporal distribution of Ulva prolifera. By tracking the centroids of the extracted areas over time, we mapped their migration routes. Three-tier threshold classification was employed to estimate the harvestable biomass near power plant. Additionally, redundancy analysis was performed to assess the environmental factors influencing Ulva prolifera growth. The results indicate that Ulva prolifera in the Yellow Sea migrates northward due to monsoons and ocean currents, with nitrogen – and phosphate-enriched waters promoting its expansion. Remote sensing can support the provision of early warnings, enabling proactive management to control the spread of biohazards, reduce harvesting frequency, lower labor costs, and mitigate risks to cooling water intake systems.
ISSN:1753-8947
1753-8955