Effects of land use types on dissolved trace metal concentrations in the Le’an River Basin, China

Author(s):  
Yinghui Jiang ◽  
Zhenglei Xie ◽  
Hua Zhang ◽  
Huanqing Xie ◽  
Yun Cao
1993 ◽  
Vol 28 (1) ◽  
pp. 83-110 ◽  
Author(s):  
Richard E. Farrell ◽  
Jae E. Yang ◽  
P. Ming Huang ◽  
Wen K. Liaw

Abstract Porewater samples from the upper Qu’Appelle River basin in Saskatchewan, Canada, were analyzed to obtain metal, inorganic ligand and amino add profiles. These data were used to compute the aqueous speciation of the metals in each porewater using the computer program GEOCHEM-PC. The porewaters were classified as slightly to moderately saline. Metal concentrations reflected both the geology of the drainage basin and the impact of anthropogenic activities. Whereas K and Na were present almost entirely as the free aquo ions, carbonate equilibria dominated the speciation of Ca. Mg and Mn (the predominant metal ligand species were of the type MCO3 (s). MCO30. and MHCO3+). Trace metal concentrations were generally within the ranges reported for non-polluted freshwater systems. Whereas the speciation of the trace metals Cr(III) and Co(II) was dominated by carbonate equilibria, Hg(II)-, Zn(II)- and Fe(II)-speciation was dominated by hydroxy-metal complexes of the type M(OH)+ and M(OH)2°. The speciation of Fe(III) was dominated by Fe(OH)3 (s). In porewaters with high chloride concentrations (> 2 mM), however, significant amounts of Hg(II) were bound as HgCl20 and HgClOH0. The aqueous speciation of Al was dominated by Al(OH)4− and Al2Si2O4(OH)6 (s). Total concentrations of dissolved free amino acids varied from 15.21 to 25.17 umole L−1. The most important metal scavenging amino acids were histidine (due to high stability constants for the metal-histidine complexes) and tryptophan (due to its relatively high concentration in the porewaters. i.e., 5.96 to 7.73 umole L−1). Secondary concentrations of various trace metal-amino add complexes were computed for all the porewaters, but metal-amino acid complexes dominated the speciation of Cu(II) in all the porewaters and Ni(II) in two of the porewaters.


2020 ◽  
Vol 12 (1) ◽  
pp. 1406-1420
Author(s):  
Jianwei Wang ◽  
Kun Wang ◽  
Tianling Qin ◽  
Hanjiang Nie ◽  
Zhenyu Lv ◽  
...  

AbstractLand use/cover change plays an important role in human development and environmental health and stability. Markov chain and a future land use simulation model were used to predict future change and simulate the spatial distribution of land use in the Huang-Huai-Hai river basin. The results show that cultivated land and grassland are the main land-use types in the basin, accounting for about 40% and 30%, respectively. The area of cultivated land decreased and artificial surfaces increased from 1980 to 2010. The degree of dynamic change of land use after the 1990s was greater than that before the 1990s. There is a high probability of exchange among cultivate land, forest and grassland. The area of forest decreased before 2000 and increased after 2000. Under the three emission scenarios (RCP2.6, RCP4.5, and RCP8.5) of IPSL-CM5A-LR climate model, the area of cultivated land will decrease and that of grassland will increase in the upstream area while it will decrease in the downstream area. The above methods and rules will be of great help to future land use planning.


PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9386
Author(s):  
Yanlin Li ◽  
Chunmei Zeng ◽  
Meijun Long

The diversity and community distribution of soil bacteria in different land use types in Yangtze River Basin, Chongqing Municipality were studied by using Illumina MiSeq analysis methods. Soil physical and chemical properties were determined, and correlation analyses were performed to identify the key factors affecting bacterial numbers and α-diversity in these soils. The results showed that the soil physical and chemical properties of different land use types decrease in the order: mixed forest (M2) > pure forest (P1) > grassland (G3) > bare land (B4). There were significant differences in bacterial diversity and communities of different land use types. The diversity of different land use types showed the same sequence with the soil physical and chemical properties. The abundance and diversity of bacterial in M2 and P1 soils was significantly higher than that in G3 and B4 soils. At phylum level, G3 and B4 soils were rich in only Proteobacteria and Actinobacteria, whereas M2 and P1 soils were rich in Proteobacteria, Actinobacteria and Firmicutes. At genus level, Faecalibacterium and Agathobacter were the most abundant populations in M2 soil and were not found in other soils. Pearson correlation analysis showed that soil moisture content, pH, AN, AP, AK and soil enzyme activity were significantly related to bacterial numbers, diversity and community distribution.


2020 ◽  
Vol 20 (3) ◽  
pp. 1046-1058
Author(s):  
Fan Gao ◽  
Bing He ◽  
Songsong Xue ◽  
Yizhen Li

Abstract Based on the Soil and Water Assessment Tool (SWAT) model, the monthly runoff processes of two land-use types in 2000 and 2015 were simulated in this paper. The relationship between runoff and landscape pattern was analyzed, and the spatial correlation between runoff and landscape pattern analyzed using the geographic weighted regression model combined with the change of landscape pattern in the study area from 2000 to 2015. The results show the following. (1) The SWAT model can simulate the monthly runoff processes in the catchment area of the Ulungur River Basin (URB) under different land-use types for 2000 and 2015, but the simulation effect in 2000 was found to be better than that in 2015. (2) From 2000 to 2015, the area of woodland and grassland decreased. Runoff was positively correlated with woodland, grassland, largest patch index, mean patch area (AREA_MN), and contagion index, and negatively correlated with others. This indicates that the landscape fragmentation of URB was aggravated in 2000–2015, the landscape balance was destroyed, and the ability of rainfall interception and water conservation was weakened. (3) Landscape pattern indicators of grassland had a negative spatial impact on URB runoff, and the northern region of URB was more severely affected in 2015 than in 2000. AREA_MN landscape pattern index had a positive impact on runoff in the northern part of URB, and the positive impact in northern URB in 2000 was better than that in 2015.


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