Impacts of land use and landscape pattern on water quality at multiple spatial scales in a subtropical large river

The coupling between land use/landscape pattern and water quality in river systems 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 o...

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Bibliographic Details
Published inEcohydrology Vol. 15; no. 3
Main Authors Shu, Xiao, Wang, Weibo, Zhu, Mingyong, Xu, Jilei, Tan, Xiang, Zhang, Quanfa
Format Journal Article
LanguageEnglish
Published Oxford Wiley Subscription Services, Inc 01.04.2022
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Summary:The coupling between land use/landscape pattern and water quality in river systems 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, was higher during the wet season than the dry season. Total nitrogen was the main driver of nutrient pollution in the UHR, whereas total phosphorus was identified as another potential nutrient pollutant. We also found that water quality parameters were more strongly related to land use types during the wet season than the dry season. Croplands and urban lands increased phosphorus concentrations of river water, whereas forest and grasslands decreased the nitrogen concentrations of river water at the sub‐basin scale. Land use at the 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 during the dry season than the wet season. The largest patch index and Shannon's diversity index were the main predictors of river water quality in the UHR.
Bibliography:Funding information
Ordinary University Characteristic Innovation Project of Guangdong Province, China, Grant/Award Number: 2020KTSCX140; Open Funding Project of the Key Laboratory of Aquatic Botany and Watershed Ecology, Chinese Academy of Science; National Natural Science Foundation of China, Grant/Award Numbers: 31922060, 31720103905, 32030069
ISSN:1936-0584
1936-0592
DOI:10.1002/eco.2398