Wang Lizhi, Meng Fanli, Song Hongli, An Juan, Wang Yun
Shandong Provincial Key Laboratory of Water and Soil Conservation and Environmental Protection, College of Resources and Environment, Linyi University, Linyi, 276005, China.
Guizhou Academy of Environmental Science Research and Design, Guiyang, China.
Sci Rep. 2024 Oct 23;14(1):25112. doi: 10.1038/s41598-024-75812-4.
Traditional linear correlation analysis may not fully capture the true relationship between these variables. Therefore, multi-scale running correlation analysis, such as time-dependent intrinsic correlation (TDIC) and continuous wavelet transform based on Hilbert-Huang transform (HHT), provides valuable insights into local correlations and the evolving relationship between nutrients and environmental factors over time. In this study, we investigated seven environmental factors and four water quality nutrient indicators in deep lakes on the Yungui Plateau in southwestern China. The results revealed that there may be strong correlations between environmental factors and nutrient levels during certain periods, while opposite trends may emerge at other times. These variations in correlation could be attributed to uncertain physical processes, spatial heterogeneity, or the impact of different climatic factors on local hydrological processes. Wavelet analysis indicated that changes in environmental factors lag behind those in nutrient levels, particularly on a cycle of about 12 months. This suggests that changes in environmental factors align with natural patterns after the water body has been polluted. These conclusions underscore the complexity and dynamic nature of the relationship between environmental factors and nutrient levels in water bodies, highlighting the importance of employing advanced analysis techniques to capture this complexity.
传统的线性相关分析可能无法完全捕捉这些变量之间的真实关系。因此，多尺度运行相关分析，如时间相关内在相关性（TDIC）和基于希尔伯特-黄变换（HHT）的连续小波变换，为局部相关性以及营养物质与环境因子随时间的演变关系提供了有价值的见解。在本研究中，我们调查了中国西南部云贵高原深水湖泊中的七个环境因子和四个水质营养指标。结果表明，在某些时期环境因子与营养水平之间可能存在强相关性，而在其他时期可能出现相反的趋势。相关性的这些变化可能归因于不确定的物理过程、空间异质性或不同气候因子对当地水文过程的影响。小波分析表明，环境因子的变化滞后于营养水平的变化，特别是在大约12个月的周期上。这表明在水体受到污染后，环境因子的变化与自然模式相符。这些结论强调了水体中环境因子与营养水平关系的复杂性和动态性，突出了采用先进分析技术来捕捉这种复杂性的重要性。
