Identifying the spatio-temporal variations of Ulva prolifera disasters in all life cycle
Since 2007, Ulva prolifera disasters have occurred every year in the South Yellow Sea of China, the largest green tide disaster in the world. The inter-annual differences make monitoring and early warning for such disasters difficult. This study used remote sensing data (2015–2019) to determine its...
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| Format: | Article |
| Language: | English |
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IWA Publishing
2022-02-01
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| Series: | Journal of Water and Climate Change |
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| Online Access: | http://jwcc.iwaponline.com/content/13/2/629 |
| _version_ | 1828879976972156928 |
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| author | Baowei Zhang Jianzhong Guo Ziwei Li Yi Cheng Yao Zhao Muhammad Waseem Boota Yaonan Zhang Liqiang Feng |
| author_facet | Baowei Zhang Jianzhong Guo Ziwei Li Yi Cheng Yao Zhao Muhammad Waseem Boota Yaonan Zhang Liqiang Feng |
| author_sort | Baowei Zhang |
| collection | DOAJ |
| description | Since 2007, Ulva prolifera disasters have occurred every year in the South Yellow Sea of China, the largest green tide disaster in the world. The inter-annual differences make monitoring and early warning for such disasters difficult. This study used remote sensing data (2015–2019) to determine its spatio-temporal variations in all life cycles. The results showed a lay effect between the NDVI-mean and the coverage area of U. prolifera. The spatio-temporal distribution of U. prolifera showed stages and regional differences. From late April to early May, U. prolifera first emerged near the Subei Shoal. After development in the middle of the Yellow Sea, U. prolifera broke out in the eastern sea area of Shandong and Jiangsu, declined in the Shandong sea area, and disappeared near Qingdao. The cycle lasted for approximately 90 days. The sea surface temperature was the necessary condition for the disaster, and the sea wind field was the main driving force for its horizontal drift. This study overcomes the poor timing and continuity of remote sensing data in the monitoring of U. prolifera. It provides a theoretical reference for forecasting the outbreak period of U. prolifera and can aid policy-makers to avert such disasters in advance. HIGHLIGHTS
There is a significant hysteresis effect between NDVIM and the U. prolifera coverage area.;
U. prolifera disasters at different growth stages are geographically regional.;
Sea surface temperature and sea wind field are the main influencing factors of U. prolifera disaster.;
NDVIM can provide a scientific theoretical reference for predicting the future outbreak period of U. prolifera.; |
| first_indexed | 2024-12-13T09:38:29Z |
| format | Article |
| id | doaj.art-6f01ebd301d74710be553b0222f2d91f |
| institution | Directory Open Access Journal |
| issn | 2040-2244 2408-9354 |
| language | English |
| last_indexed | 2024-12-13T09:38:29Z |
| publishDate | 2022-02-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Journal of Water and Climate Change |
| spelling | doaj.art-6f01ebd301d74710be553b0222f2d91f2022-12-21T23:52:15ZengIWA PublishingJournal of Water and Climate Change2040-22442408-93542022-02-0113262964410.2166/wcc.2021.424424Identifying the spatio-temporal variations of Ulva prolifera disasters in all life cycleBaowei Zhang0Jianzhong Guo1Ziwei Li2Yi Cheng3Yao Zhao4Muhammad Waseem Boota5Yaonan Zhang6Liqiang Feng7 PLA Strategic Support Force Information Engineering University, No. 62, Science Avenue, Zhengzhou, Henan Province 450001, China College of Environment and Planning, Henan University, North Section of Jinming Avenue, Longting District, Kaifeng, Henan Province 475004, China School of Water Conservancy Science and Engineering, Zhengzhou University, No. 100, Science Avenue, Zhengzhou, Henan Province 450001, China PLA Strategic Support Force Information Engineering University, No. 62, Science Avenue, Zhengzhou, Henan Province 450001, China PLA Strategic Support Force Information Engineering University, No. 62, Science Avenue, Zhengzhou, Henan Province 450001, China School of Water Conservancy Science and Engineering, Zhengzhou University, No. 100, Science Avenue, Zhengzhou, Henan Province 450001, China Northwest Institute of Eco-Environment and Resources, CAS, No. 320, Donggang West Road, Lanzhou, Gansu Province 730000, China Center for Ocean Mega-Science, Chinese Academy of Sciences, No. 7, Nanhai Road, Qingdao, Shandong Province 266071, China Since 2007, Ulva prolifera disasters have occurred every year in the South Yellow Sea of China, the largest green tide disaster in the world. The inter-annual differences make monitoring and early warning for such disasters difficult. This study used remote sensing data (2015–2019) to determine its spatio-temporal variations in all life cycles. The results showed a lay effect between the NDVI-mean and the coverage area of U. prolifera. The spatio-temporal distribution of U. prolifera showed stages and regional differences. From late April to early May, U. prolifera first emerged near the Subei Shoal. After development in the middle of the Yellow Sea, U. prolifera broke out in the eastern sea area of Shandong and Jiangsu, declined in the Shandong sea area, and disappeared near Qingdao. The cycle lasted for approximately 90 days. The sea surface temperature was the necessary condition for the disaster, and the sea wind field was the main driving force for its horizontal drift. This study overcomes the poor timing and continuity of remote sensing data in the monitoring of U. prolifera. It provides a theoretical reference for forecasting the outbreak period of U. prolifera and can aid policy-makers to avert such disasters in advance. HIGHLIGHTS There is a significant hysteresis effect between NDVIM and the U. prolifera coverage area.; U. prolifera disasters at different growth stages are geographically regional.; Sea surface temperature and sea wind field are the main influencing factors of U. prolifera disaster.; NDVIM can provide a scientific theoretical reference for predicting the future outbreak period of U. prolifera.;http://jwcc.iwaponline.com/content/13/2/629life cyclendvispatio-temporal variationsulva prolifera |
| spellingShingle | Baowei Zhang Jianzhong Guo Ziwei Li Yi Cheng Yao Zhao Muhammad Waseem Boota Yaonan Zhang Liqiang Feng Identifying the spatio-temporal variations of Ulva prolifera disasters in all life cycle Journal of Water and Climate Change life cycle ndvi spatio-temporal variations ulva prolifera |
| title | Identifying the spatio-temporal variations of Ulva prolifera disasters in all life cycle |
| title_full | Identifying the spatio-temporal variations of Ulva prolifera disasters in all life cycle |
| title_fullStr | Identifying the spatio-temporal variations of Ulva prolifera disasters in all life cycle |
| title_full_unstemmed | Identifying the spatio-temporal variations of Ulva prolifera disasters in all life cycle |
| title_short | Identifying the spatio-temporal variations of Ulva prolifera disasters in all life cycle |
| title_sort | identifying the spatio temporal variations of ulva prolifera disasters in all life cycle |
| topic | life cycle ndvi spatio-temporal variations ulva prolifera |
| url | http://jwcc.iwaponline.com/content/13/2/629 |
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