Yin Yingze, Xia Rui, Chen Yan, Jia Ruining, Zhong Nixi, Yan Chao, Hu Qiang, Li Xiang, Zhang Hui
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Northwest University College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China.
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; National Engineering Laboratory for Lake Pollution Control and Ecological Restoration, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Estuarine and Coastal Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
Water Res. 2023 Aug 15;242:120247. doi: 10.1016/j.watres.2023.120247. Epub 2023 Jun 18.
The hydrological regimes and environmental changes in large riverine lakes are known for their complexity and high level of uncertainty. Scientifically uncovering the response mechanisms of water environments under complex hydrological conditions has become a challenging research objective, in the interdisciplinary of environmental science and hydrology. This study delved into the unstable response process between water level and quality of Poyang Lake, the largest freshwater lake as well as one of the most intense hydrological variability water bodies in China. We developed a non-steady state identification approach incorporates Seasonal and Trend decomposition using Loess (STL) and Wavelet Correlation (WTC) methods. The results showed that there were remarkable alterations in the hydrological regime and water quality at both seasonal and long-term scale of Poyang Lake over the past nine years. These alterations were accompanied by significant non-steady state characteristics, reflecting the changes in the response between water level and quality. The employment of the STL-WTC method revealed a significant nonlinear response between the long-term trends of water level and quality, in both the 4-month and 12-month frequency bands. In particular, our findings showed an intriguing shift towards in-phase behavior between water level and quality in the 12-month frequency band, rather than the anti-phase pattern observed previously. This correlation changed more significantly in seasons where the fluctuation pattern of water level varied sharply, such as summer and winter in Poyang Lake. Our study underscored the hydrological conditions and water quality of large lakes connected to rivers do not exhibit a long-term stable unidirectional response state, alterations in hydrological rhythms may induce a transition in the relationship from negative correlation towards nonlinear positive correlation between water level and water quality. Finally, this non-steady state fluctuation of water conditions can further exacerbate long-term and seasonal degradation of water quality.
大型河滨湖泊的水文状况和环境变化以其复杂性和高度不确定性而闻名。在环境科学与水文学的交叉领域，科学地揭示复杂水文条件下的水环境响应机制已成为一项具有挑战性的研究目标。本研究深入探讨了中国最大的淡水湖——鄱阳湖（也是水文变率最剧烈的水体之一）水位与水质之间的不稳定响应过程。我们开发了一种非稳态识别方法，该方法结合了使用黄土（Loess）的季节性和趋势分解（STL）以及小波相关性（WTC）方法。结果表明，在过去九年中，鄱阳湖在季节和长期尺度上的水文状况和水质都发生了显著变化。这些变化伴随着明显的非稳态特征，反映了水位与水质之间响应关系的变化。STL-WTC方法的应用揭示了在4个月和12个月频段内，水位和水质的长期趋势之间存在显著的非线性响应。特别是，我们的研究结果显示，在12个月频段内，水位与水质之间出现了有趣的同相位行为转变，而不是之前观察到的反相位模式。这种相关性在水位波动模式变化剧烈的季节（如鄱阳湖的夏季和冬季）变化更为显著。我们的研究强调，与河流相连的大型湖泊的水文条件和水质不会呈现长期稳定的单向响应状态，水文节律的变化可能导致水位与水质之间的关系从负相关向非线性正相关转变。最后，这种水情的非稳态波动会进一步加剧水质的长期和季节性恶化。
