Impact of landscape pattern at multiple spatial scales on water quality: A case study in a typical urbanised watershed in China

2015 ◽  
Vol 48 ◽  
pp. 417-427 ◽  
Author(s):  
Zhenyao Shen ◽  
Xiaoshu Hou ◽  
Wen Li ◽  
Guzhanuer Aini ◽  
Lei Chen ◽  
...  
2018 ◽  
Vol 38 (7) ◽  
Author(s):  
范敏 FAN Min ◽  
彭羽 PENG Yu ◽  
王庆慧 WANG Qinghui ◽  
米凯 MI Kai ◽  
卿凤婷 QING Fengting

2021 ◽  
Author(s):  
Xiao Shu ◽  
Weibo Wang ◽  
Mingyong Zhu ◽  
Jilei Xu ◽  
Xiang Tan ◽  
...  

Abstract The coupling between land use/landscape pattern and water quality in river system varies across different spatial and temporal scales. It is important to understand the association between water quality and land use/landscape pattern across different spatial and temporal scales for the protection of water resources. Here, we measured seasonal water quality at 12 sub-basins in the upper reaches of the Han River (UHR) between 2010 and 2018. We conducted factor analysis and redundancy analysis to determine the links between land use and water quality at multiple spatial scales and to identify the main factors influencing water quality. We found that the concentration of nutrients, including total nitrogen, total phosphorus, nitrate-N, and ammonium-N were higher during the wet season than the dry season. Total nitrogen was identified as the main driver of nutrient pollution of UHR, whereas total phosphorus was identified as another potential nutrient pollutant. We also found that water quality parameters had a stronger related to land use types over the wet season than the dry season. Croplands and urban lands increased phosphorus concentrations of river water, whereas forest and grass lands decreased the nitrogen concentrations of river water at the sub-basins scale. Land use at riparian zone scales better explained variations in water quality than land use at sub-basin scales. The explained variations in landscape metrics were generally higher over the dry season compared to that over the wet season. The largest patch index and Shannon's diversity index were the main predictors of river water quality in UHR.


Ecohydrology ◽  
2021 ◽  
Author(s):  
Xiao Shu ◽  
Weibo Wang ◽  
Mingyong Zhu ◽  
Jilei Xu ◽  
Xiang Tan ◽  
...  

2013 ◽  
Vol 28 (20) ◽  
pp. 5259-5272 ◽  
Author(s):  
Guoqiang Wang ◽  
Yinglan A ◽  
Zongxue Xu ◽  
Shurong Zhang

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