Affiliations 

  • 1 Xinjiang Institute of Technology, Aksu 843000, China; College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
  • 2 College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China; College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China. Electronic address: zhangfei3s@zjnu.edu.cn
  • 3 Department of Social Sciences, Education University of Hong Kong, Lo Ping Road, Tai Po 999077, Hong Kong
  • 4 Department of Physical and Environmental Sciences, Colorado Mesa University, Grand Junction, CO 81501, USA
  • 5 GeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, USM, Penang 11800, Malaysia
  • 6 Departments of Earth Sciences, the University of Memphis, Memphis, TN 38152, USA
  • 7 College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China
Sci Total Environ, 2023 Mar 29;878:163127.
PMID: 37001663 DOI: 10.1016/j.scitotenv.2023.163127

Abstract

Suspended particulate matter (SPM) in the brackish Ebinur Lake of arid northwest China profoundly affect its water quality and watershed habitat quality. However, the actual driving mechanisms of the Lake's SPM changes remain unclear. Therefore, the purpose of this study is to explore the controlling factors driving the variability of SPM in the Ebinur Lake. This study constructed month-by-month SPM maps of Ebinur Lake based on time-series remote-sensing imageries and SPM inversion model. Thirty-four factors that might influence SPM changes were extracted, and the Partial Least Squares Structural Equation Modeling (PLS-SEM), suitable for complex relationships and factor interactions, was applied to identify the relative influence of each factor quantitatively. The results showed: (1) a clear increasing trend of SPM concentration in Ebinur Lake from 2011 to 2020; (2) that SPM changes were influenced by external and internal factors, explaining 48.2 % and 46.9 % of the changes, respectively; (3) that, to the external factors, meteorological factors exerted the greatest influence on SPM (relative contribution of 38.9 %); that, to the internal factors, water salinity imposed the greatest influence on SPM (relative contribution of 43.3 %); (4) that, among the meteorological factors, the measured variable Alashankou wind speed expressed the most significant positive effect on SPM (weighting coefficient of 0.894), and sulfate generated the strongest positive effect on SPM (weighting coefficient of 0.791) among the water salinity factors. Hence, the quantitative identification of drivers of SPM changes in Ebinur Lake could provide a new perspective to investigate the driving mechanisms of lake water quality in arid areas and inform their sustainable restoration and management.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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