Xinjiang Institute of Technology, Aksu 843000, China; College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China.
College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China; College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China.
Sci Total Environ. 2023 Jun 20;878:163127. doi: 10.1016/j.scitotenv.2023.163127. Epub 2023 Mar 29.
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.
中国干旱西北的艾比湖悬浮颗粒物（SPM）对其水质和流域生境质量有深远影响。然而，该湖 SPM 变化的实际驱动机制仍不清楚。因此，本研究旨在探讨驱动艾比湖 SPM 变化的控制因素。本研究基于多时相遥感影像和 SPM 反演模型，构建了艾比湖逐月 SPM 分布图。提取了可能影响 SPM 变化的 34 个因素，并应用偏最小二乘结构方程模型（PLS-SEM）来定量识别每个因素的相对影响，该模型适合复杂关系和因素交互。结果表明：（1）艾比湖 SPM 浓度自 2011 年至 2020 年呈明显上升趋势；（2）SPM 变化受外部和内部因素影响，分别解释了 48.2%和 46.9%的变化；（3）外部因素中，气象因素对 SPM 的影响最大（相对贡献为 38.9%），内部因素中，水盐度对 SPM 的影响最大（相对贡献为 43.3%）；（4）在气象因素中，实测的阿拉山口风速对 SPM 表现出最显著的正效应（权重系数为 0.894），而硫酸盐对 SPM 产生了最强的正效应（权重系数为 0.791）。因此，定量识别艾比湖 SPM 变化的驱动因素可以为研究干旱地区湖泊水质的驱动机制提供新视角，并为其可持续恢复和管理提供信息。
