QUALITY MONITORING OF SHENZHEN’S COASTAL WATERS BY SATELLITE AND ITS SPATIOTEMPORAL VARIATION

LI Xuxia; WANG Yudong; XIAO Youpeng; XU Xu; WANG Haipeng; CHEN Yimeng; LIN Junchuan; HUANG Guisong; HUANG Zhenguo; SUN Ping; MAI Youquan; YANG Shangbo; XU Wang

doi:10.13205/j.hjgc.202401031

Volume 42 Issue 1

Jan. 2024

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Article Navigation > ENVIRONMENTAL ENGINEERING > 2024 > 42(1): 243-252

LI Xuxia, WANG Yudong, XIAO Youpeng, XU Xu, WANG Haipeng, CHEN Yimeng, LIN Junchuan, HUANG Guisong, HUANG Zhenguo, SUN Ping, MAI Youquan, YANG Shangbo, XU Wang. QUALITY MONITORING OF SHENZHEN’S COASTAL WATERS BY SATELLITE AND ITS SPATIOTEMPORAL VARIATION[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(1): 243-252. doi: 10.13205/j.hjgc.202401031

Citation:

LI Xuxia, WANG Yudong, XIAO Youpeng, XU Xu, WANG Haipeng, CHEN Yimeng, LIN Junchuan, HUANG Guisong, HUANG Zhenguo, SUN Ping, MAI Youquan, YANG Shangbo, XU Wang. QUALITY MONITORING OF SHENZHEN’S COASTAL WATERS BY SATELLITE AND ITS SPATIOTEMPORAL VARIATION[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(1): 243-252. doi: 10.13205/j.hjgc.202401031

Citation:

LI Xuxia, WANG Yudong, XIAO Youpeng, XU Xu, WANG Haipeng, CHEN Yimeng, LIN Junchuan, HUANG Guisong, HUANG Zhenguo, SUN Ping, MAI Youquan, YANG Shangbo, XU Wang. QUALITY MONITORING OF SHENZHEN’S COASTAL WATERS BY SATELLITE AND ITS SPATIOTEMPORAL VARIATION[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(1): 243-252. doi: 10.13205/j.hjgc.202401031

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QUALITY MONITORING OF SHENZHEN’S COASTAL WATERS BY SATELLITE AND ITS SPATIOTEMPORAL VARIATION

doi: 10.13205/j.hjgc.202401031

1. Shenzhen Ecological and Environmental Monitoring Center of Guangdong Province, Shenzhen 518000, China;
2. Southern University of Science and Technology, Shenzhen 518000, China

Received Date: 2023-11-14
Available Online: 2024-04-29

Abstract

Abstract

In recent years, coastal eutrophication and the resulting red tide occurrences have emerged as pressing environmental concerns, posing significant challenges to the sustainable development of Shenzhen, a key city in the China Great Bay Area. Addressing this issue effectively hinges upon a comprehensive understanding of the spatiotemporal dynamics of water quality and red tide outbreaks in Shenzhen's coastal regions. This study utilized the data from the Moderate Resolution Imaging Spectroradiometer(MODIS) to establish models for remote sensing inversion of water quality parameters and automated extraction of red tide occurrences. It has unveiled, for the first time, the spatiotemporal patterns linking key water quality parameters in Shenzhen's coastal waters with red tide outbreaks and analyzed the primary driving factors. Our findings revealed an average annual affected area of red tide occurrence spanning approximately 300.50 km² within Shenzhen's jurisdictional waters, occurring on average 2.38 times annually. Between 2015 and 2022, the annual growth rate of red tide outbreak coverage was approximately 6.7%. Suspended sediment and chlorophyll-a concentrations in the Pearl River Estuary and Shenzhen Bay surpassed those in Dapeng Bay and Daya Bay, exhibiting an increasing trend. Despite the high eutrophication level in the eastern part of the Pearl River Estuary, the frequency of red tide outbreaks remained relatively low, primarily influenced by estuarine suspended sediments. In contrast, regions with superior water quality, such as Dapeng Bay and Daya Bay, experienced higher red tide frequencies that exhibited an annual increasing trend, potentially linking to the variation in nitrogen-phosphorus ratios. The study underscored the imperative need to target nitrogen-phosphorus ratios in the Nan'ao, Kuichong, and Baguang areas and undertook a comprehensive assessment of non-point pollution sources in their terrestrial zones. This information can serve as baseline information crucial for continuously advancing environmental governance, restoration efforts, and management evaluations concerning Shenzhen and its surrounding maritime areas.
- Shenzhen nearshore waters,
- water quality parameter,
- red tide,
- temporal and spatial changes,
- MODIS

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References(21)

References

[1]	马方方,冷科明,周秋伶,等.近40年深圳大鹏湾海域赤潮发生规律及其演变机制分析[J].海洋环境科学,2021,40(2):263-271.
[2]	WANG J,TONG Y,FENG L,et al.Satellite-observed decreases in water turbidity in the pearl river estuary:potential linkage with sea-level rise[J].Journal of Geophysical Research:Oceans,2021,126(4):1-17.
[3]	TONG Y,FENG L,ZHAO D,et al.Remote sensing of chlorophyll-a concentrations in coastal oceans of the Greater Bay Area in China:algorithm development and long-term changes[J].International Journal of Applied Earth Observation and Geoinformation,2022,112:102922.
[4]	但雨生,周忠发,李韶慧,等.基于Sentinel-2的平寨水库叶绿素a浓度反演[J].环境工程,2020,38(3):180-185 ,127.
[5]	HU C M,MULLERKARGER F E,TAYLOR C,et al.Red tide detection and tracing using MODIS fluorescence data:a regional example in SW Florida coastal waters[J].Remote Sensing of Environment,2005,97(3):311-321.
[6]	LIU R J,XIAO Y F,MA Y,et al.Red tide detection based on high spatial resolution broad band optical satellite data[J].ISPRS Journal of Photogrammetry and Remote Sensing,2022,184:131-147.
[7]	WEI J W,LEE Z P,and SHANG S L,A system to measure the data quality of spectral remote sensing reflectance of aquatic environments[J].Journal of Geophysical Research:Oceans,2016,121:8189-8207.
[8]	HU C M.A novel ocean color index to detect floating algae in the global oceans[J].Remote Sensing of Environment,2009,113(10):2118-2129.
[9]	DAI Y H,YANG S B,ZHAO D,et al.Coastal phytoplankton blooms expand and intensify in the 21st century[J].Nature,2023,615(7951):280-284.
[10]	DAI S,ZHOU Y,LI N,et al.Why do red tides occur frequently in some oligotrophic waters?Analysis of red tide evolution history in Mirs Bay,China,and its implications[J].Sci Total Environ,2022,844:157112.
[11]	贾淇文,章桂芳,唐世林,等.2013—2018年珠江河口伶仃洋水域悬浮泥沙季节性变化分析[J].中山大学学报(自然科学版),2021,60(5 ):59-71.
[12]	陈炜婷,姜广甲,邓伟,等.基于GIS的2001—2020年广东近岸海域赤潮时空分布[J].环境工程,2023,41(增刊2):49-53.
[13]	曾丹娜,牛丽霞,陶伟,等.夏季珠江口水域营养盐分布特征及其富营养化评价[J].广东海洋大学学报,2020,40(3):73-82.
[14]	邹伟,朱广伟,蔡永久,等.综合营养状态指数(TLI) 在夏季长江中下游湖库评价中的局限及改进意见[J].湖泊科学,2020,32(1):36-47.
[15]	CHANG N B,XUAN Z M,and YANG Y J,Exploring spatiotemporal patterns of phosphorus concentrations in a coastal bay with MODIS images and machine learning models[J].Remote Sensing of Environment,2013,134:100-110.
[16]	WANG R,WU J J,YIU K F,et al.Long-term variation in phytoplankton assemblages during urbanization:a comparative case study of Deep Bay and Mirs Bay,Hong Kong,China[J].Science of Total Environment,2020,745:140993.
[17]	DAI S L,ZHOU Y Y,LI N,et al.Why do red tides occur frequently in some oligotrophic waters?Analysis of red tide evolution history in Mirs Bay,China and its implications[J].Science of the Total Environment,2022,844:157112.
[18]	张伟,孙健,聂红涛,等.珠江口及毗邻海域营养盐对浮游植物生长的影响[J].生态学报,2015,35(12):4034-4044.
[19]	SHI K,ZHANG Y,SONG K,et al.A semi-analytical approach for remote sensing of trophic state in inland waters:bio-optical mechanism and application[J].Remote Sensing of Environment,2019,232:111349.
[20]	周博天,张雅燕,和施坤.湖泊营养状态遥感评价及其表征参数反演算法研究进展[J].遥感学报,2022,26(1):77-91.
[21]	袁伟皓,王华,曾一川,等.大型通江湖泊藻类增殖驱动要素的时空分异特征[J].环境工程,2021,39(10):64-71 ,128.