Arid
DOI10.1007/s11356-017-1041-8
Multi-scale analysis of the relationship between landscape patterns and a water quality index (WQI) based on a stepwise linear regression (SLR) and geographically weighted regression (GWR) in the Ebinur Lake oasis
Wang, Xiaoping1,2; Zhang, Fei1,2
通讯作者Zhang, Fei
来源期刊ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
ISSN0944-1344
EISSN1614-7499
出版年2018
卷号25期号:7页码:7033-7048
英文摘要

Water quality is highly dependent on landscape characteristics. This study explored the relationships between landscape patterns and water quality in the Ebinur Lake oasis in China. The water quality index (WQI) has been used to identify threats to water quality and contribute to better water resource management. This study established the WQI and analyzed the influence of landscapes on the WQI based on a stepwise linear regression (SLR) model and geographically weighted regression (GWR) models. The results showed that the WQI was between 56.61 and 2886.51. The map of the WQI showed poor water quality. Both positive and negative relationships between certain land use and land cover (LULC) types and the WQI were observed for different buffers. This relationship is most significant for the 400-m buffer. There is a significant relationship between the water quality index and landscape index (i.e., PLAND, DIVISION, aggregation index (AI), COHESION, landscape shape index (LSI), and largest patch index (LPI)), demonstrated by using stepwise multiple linear regressions under the 400-m scale, which resulted in an adjusted R-2 between 0.63 and 0.88. The local R-2 between the LPI and LSI for forest grasslands and the WQI are high in the Akeqisu River and the Kuitun rivers and low in the Bortala River, with an R-2 ranging from 0.57 to 1.86. The local R-2 between the LSI for croplands and the WQI is 0.44. The local R-2 values between the LPI for saline lands and the WQI are high in the Jing River and low in the Bo River, Akeqisu River, and Kuitun rivers, ranging from 0.57 to 1.86.


英文关键词Landscape index Water quality parameter Geographically weighted regression Multi-scale WQI
类型Article
语种英语
国家Peoples R China
收录类别SCI-E
WOS记录号WOS:000426571000083
WOS关键词LAND-USE ; SPATIAL SCALES ; EASTERN CHINA ; RIVER ; IMPACTS ; STREAMS ; RESTORATION ; MANAGEMENT ; CATCHMENTS ; RESOURCES
WOS类目Environmental Sciences
WOS研究方向Environmental Sciences & Ecology
来源机构新疆大学
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/209133
作者单位1.Xinjiang Univ, Coll Resources & Environm Sci, Higher Educ Inst, Key Lab Smart City & Environm Modeling, Urumqi 830046, Peoples R China;
2.Xinjiang Univ, Minist Educ, Key Lab Oasis Ecol, Urumqi 830046, Peoples R China
推荐引用方式
GB/T 7714
Wang, Xiaoping,Zhang, Fei. Multi-scale analysis of the relationship between landscape patterns and a water quality index (WQI) based on a stepwise linear regression (SLR) and geographically weighted regression (GWR) in the Ebinur Lake oasis[J]. 新疆大学,2018,25(7):7033-7048.
APA Wang, Xiaoping,&Zhang, Fei.(2018).Multi-scale analysis of the relationship between landscape patterns and a water quality index (WQI) based on a stepwise linear regression (SLR) and geographically weighted regression (GWR) in the Ebinur Lake oasis.ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,25(7),7033-7048.
MLA Wang, Xiaoping,et al."Multi-scale analysis of the relationship between landscape patterns and a water quality index (WQI) based on a stepwise linear regression (SLR) and geographically weighted regression (GWR) in the Ebinur Lake oasis".ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 25.7(2018):7033-7048.
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