In October-November 2020, the phytoplankton and the aquatic environment from 62 sites in the mainstream of the Qinhe River and the largest tributary of the Qinhe River (Danhe River) in the Jincheng region were investigated to clarify the spatial pattern of phytoplankton communities and their driving factors. A total of 7 phyla and 47 species of phytoplankton were identified in the Qinhe River basin and were composed of Cryptophyta, Chlorophyta, Pyrrophyta, Chrysophyta, Bacillariophyta, Cyanophyta, and Crytophyta. Six dominant species in the Qinhe River included:, and . Six dominant species in the Danhe River included: Lemm, and . The Shannon-Wiener diversity index () varied from 0.35 to 3.15, with a mean value 1.40. The Pielou evenness index () varied from 0.24 to 1.00, with a mean value of 0.68. values in the Qinhe River were higher than those in the Danhe River. values were relatively low in the middle reaches of the Qinhe River and middle-low reaches of the Danhe River. The results in the Qinhe River through a canonical correspondence analysis (CCA) showed that the percent of forest land at a 300 m buffer was the driving factor of in Chlorophyta, and nitrate, total phosphorus, and the percent of forest land at the 300 m buffer were the driving factors of . was mainly influenced by the percent of urban land and water temperature, whereas , and were mainly influenced by the percent of farmland and residential land at the 300 m buffer. The results in the Danhe River via CCA showed that and were mainly influenced by pH and sulfate, was mainly influenced by the percent of urban land and grass land, was mainly influenced by chloride and the percent of forest land, was mainly influenced by water temperature and the percent of farmland, and was mainly influenced by ammonia and the percent of farmland.
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http://dx.doi.org/10.13227/j.hjkx.202111307 | DOI Listing |
MethodsX
June 2024
Department of Civil Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.
River bed reconstruction plays an essential part in supporting the hydrodynamic simulation and understanding the morphological processes of a river. The streamlines can be solved using Laplace equations. The equation is first numerically solved in a computational environment and then adapted to the whole considered physical field to solve the resulting streamlines in a physical domain.
View Article and Find Full Text PDFHuan Jing Ke Xue
September 2022
School of Resources and Environment, Henan University of Technology, Jiaozuo 454000, China.
In October-November 2020, the phytoplankton and the aquatic environment from 62 sites in the mainstream of the Qinhe River and the largest tributary of the Qinhe River (Danhe River) in the Jincheng region were investigated to clarify the spatial pattern of phytoplankton communities and their driving factors. A total of 7 phyla and 47 species of phytoplankton were identified in the Qinhe River basin and were composed of Cryptophyta, Chlorophyta, Pyrrophyta, Chrysophyta, Bacillariophyta, Cyanophyta, and Crytophyta. Six dominant species in the Qinhe River included:, and .
View Article and Find Full Text PDFBull Environ Contam Toxicol
May 2021
School of Medicine, Henan Polytechnic University, Jiaozuo, 454000, People's Republic of China.
Gonad development and histopathological changes typically associated with endocrine disruption were evaluated in female Japanese medaka (Oryzias latipes) exposed to river water from four representative cross-sections in the Yellow River (YR), China. Fish were held in the river water treatments from fertilization. Advanced ovarian development was observed in fish exposed to river water from Qinhe cross-section at 20 days post-hatch (dph) and in fish exposed to river water from all four cross-sections at 60 dph.
View Article and Find Full Text PDFHuan Jing Ke Xue
December 2018
Center for Hydrogeology and Environmental Geology, China Geological Survey, Baoding 071051, China.
Environ Sci Pollut Res Int
January 2019
School of Environmental and Chemical Engineering, Shanghai University, No.99, Shangda Road, Baoshan District, Shanghai, 200444, China.
Nitrate pollution in water is a common environmental problem worldwide. The Qinhe Basin (QHB) faces with the risk of eutrophication. To clarify nitrate pollution of river water, water chemical data, water isotope values (δD and δO-HO), and dual nitrate isotope values (δN-NO and δO-NO) were used to discern sources and transformation mechanisms of nitrogen in the QHB.
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