Biomass size spectra of net plankton in the adjacent area near the Yangtze River Estuary in spring

2008 ◽  
Vol 28 (3) ◽  
pp. 1174-1182 ◽  
Author(s):  
Zuo Tao ◽  
Wang Jun ◽  
Jin Xianshi ◽  
Li Zhongyi ◽  
Tang Qisheng
Keyword(s):  
Yangtze River ◽  
River Estuary ◽  
Yangtze River Estuary ◽  
Adjacent Area ◽  
The Yangtze River ◽  
Size Spectra ◽  
The Yangtze River Estuary

Principal Component Analysis of Eutrophication in the Yangtze River Estuary

2012 ◽  
Vol 209-211 ◽  
pp. 1910-1914
Author(s):  
Qiang An ◽  
Lu Lin ◽  
Yuan Yuan Liu ◽  
Ning Qiu Huang ◽  
Bin Zhao
Keyword(s):  
Principal Component Analysis ◽  
Yangtze River ◽  
River Estuary ◽  
Principal Component ◽  
Component Analysis ◽  
Yangtze River Estuary ◽  
Adjacent Area ◽  
The Yangtze River ◽  
Chl A ◽  
The Yangtze River Estuary

The Yangtze River Estuary has become increasingly challenged by various destructive threats to its ecosystem such as the frequent occurrence of harmful algal blooms. Four cruises were carried out in the Yangtze River Estuary and its adjacent area in 2006. Ten variables including CODMn, PO43--P, SiO3-Si, NO3--N, NO2--N, NH4+-N, TN, TP, TOC and chl-a were analyzed by exploratory data analysis. Nitrate was the dominant form of TN throughout the year. Principal component analysis (PCA) was applied to estimate the sources of nutrients contamination in 2006. Two principal components (PCs) were extracted, namely, CODMn, PO43--P, NO3--N and TN for PC1, NO2--N and chl-a for PC2. Influenced by anthropogenic sewage, PC1 near Shidongkou, Bailonggang, Xinhe and Zhuyuan outlets was higher than other stations. The primary influencing factor of PC1 were the contaminants carried by runoff from the Yangtze River. And the dominating factors of eutrophication in 2006 were CODMn, PO43--P, NO3--N, TN and chl-a in the Yangtze River Estuary and its adjacent area.

Integrated evaluation of the marine ecological environment in the Yangtze River Estuary and its adjacent area

2019 ◽  
Vol 39 (13) ◽  
Author(s):  
范海梅 FAN Haimei ◽  
蒋晓山 JIANG Xiaoshan ◽  
纪焕红 JI Huanhong ◽  
刘鹏霞 LIU Pengxia ◽  
胡茂桂 HU Maogui ◽  
...  
Keyword(s):  
Yangtze River ◽  
River Estuary ◽  
Ecological Environment ◽  
Yangtze River Estuary ◽  
Adjacent Area ◽  
The Yangtze River ◽  
The Yangtze River Estuary

scholarly journals Spatial and Temporal Variability of Soil Salinity in the Yangtze River Estuary Using Electromagnetic Induction

2021 ◽  
Vol 13 (10) ◽  
pp. 1875
Author(s):  
Wenping Xie ◽  
Jingsong Yang ◽  
Rongjiang Yao ◽  
Xiangping Wang
Keyword(s):  
Electrical Conductivity ◽  
Spatial Distribution ◽  
Soil Salinity ◽  
Yangtze River ◽  
Laboratory Data ◽  
River Estuary ◽  
Yangtze River Estuary ◽  
Soil Electrical Conductivity ◽  
The Yangtze River ◽  
The Yangtze River Estuary

Soil salt-water dynamics in the Yangtze River Estuary (YRE) is complex and soil salinity is an obstacle to regional agricultural production and the ecological environment in the YRE. Runoff into the sea is reduced during the impoundment period as the result of the water-storing process of the Three Gorges Reservoir (TGR) in the upper reaches of the Yangtze River, which causes serious seawater intrusion. Soil salinity is a problem due to shallow and saline groundwater under serious seawater intrusion in the YRE. In this research, we focused on the temporal variation and spatial distribution characteristics of soil salinity in the YRE using geostatistics combined with proximally sensed information obtained by an electromagnetic induction (EM) survey method in typical years under the impoundment of the TGR. The EM survey with proximal sensing method was applied to perform soil salinity survey in field in the Yangtze River Estuary, allowing quick determination and quantitative assessment of spatial and temporal variation of soil salinity from 2006 to 2017. We developed regional soil salinity survey and mapping by coupling limited laboratory data with proximal sensed data obtained from EM. We interpreted the soil electrical conductivity by constructing a linear model between the apparent electrical conductivity data measured by an EM 38 device and the soil electrical conductivity (EC) of soil samples measured in laboratory. Then, soil electrical conductivity was converted to soil salt content (soil salinity g kg−1) through established linear regression model based on the laboratory data of soil salinity and soil EC. Semivariograms of regional soil salinity in the survey years were fitted and ordinary kriging interpolation was applied in interpolation and mapping of regional soil salinity. The cross-validation results showed that the prediction results were acceptable. The soil salinity distribution under different survey years was presented and the area of salt affected soil was calculated using geostatistics method. The results of spatial distribution of soil salinity showed that soil salinity near the riverbanks and coastlines was higher than that of inland. The spatial distribution of groundwater depth and salinity revealed that shallow groundwater and high groundwater salinity influenced the spatial distribution characteristics of soil salinity. Under long-term impoundment of the Three Gorges Reservoir, the variation of soil salinity in different hydrological years was analyzed. Results showed that the area affected by soil salinity gradually increased in different hydrological year types under the impoundment of the TGR.

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