Temporal-Spatial Distribution of Chlorophyll-a and Impacts of Environmental Factors in the Bohai Sea and Yellow Sea
| Autor: | Jiahua Zhang, Guanlan Zhang, Sha Zhang, Shahazad Ali, Na Zhao, Yun Bai |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Chlorophyll a
General Computer Science Discharge Generalized additive model General Engineering Mode (statistics) the Bohai sea and Yellow sea generalized additive model Wind direction Spatial distribution Atmospheric sciences Wind speed Sea surface temperature chemistry.chemical_compound chemistry environmental factors Environmental science self-organizing mapping neural network General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering Chl-a lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 7, Pp 160947-160960 (2019) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2019.2950833 |
| Popis: | Better understanding of the temporal-spatial distribution of chlorophyll-a concentration (Chl-a) is crucial in controlling harmful water blooms. In this study, the dynamical change of Chl-a over the Bohai Sea and Yellow Sea from 2003-2017 were analyzed by using the MODIS/Aqua satellite data, and the effects of sea surface temperature (SST), wind and wave were investigated. The typical distribution modes of long-term surface Chl-a were extracted by using the Self-organizing Mapping (SOM), neural network model. The results showed distinct seasonal variations of the Chl-a along with a gradual increase in the study period. The total Chl-a of the whole area reached the lowest value of 2.41mg/m3 in July, and the highest value 3.43mg/m3 in April; though in Laizhou Bay, the Chl-a concentration was significantly higher than other regions and the value reached at the peak in September. The spatial distribution showed that Chl-a decreased from inshore to offshore. Meanwhile, from clear mode to low, medium, and high concentration modes, the Chl-a gradually increased in coverage and concentration, and modes extracted by the SOM neural network have effectively elucidated the trend of Chl-a in spatial, seasonal, and interannual variability. The Generalized Additive Model (GAM) was used to evaluate the effect of SST, wind, and wave on the changing patterns of Chl-a. It was found that there is a significant nonlinear correlation between Chl-a and SST, wind speed, mean wave direction and significant height of the wave. These influencing factors accounted for 47.9% of the change of Chl-a, which had significant effects on Chl-a change. Compared with wind speed, mean wave direction and significant height of wave, SST can better explain the change of Chl-a. Besides, wind direction and increased human activity (e.g., river discharge) played a significant role in changing the Chl-a distribution in the Bohai Sea and Yellow Sea. |
| Databáze: | OpenAIRE |
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