Zhou Wang , Fei Xiao , Miaomiao Chen , Jiahuan Luo , Shuhui Cao , Qi Feng
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引用次数: 0
Abstract
In the past few decades, freshwater lakes in the middle and lower reaches of the Yangtze River have experienced significant ecological degradation, with many lakes transitioning from oligotrophic to eutrophic states. In response to this issue, China has implemented some ecological restoration measures in the Yangtze River basin to improve water quality, but the results of those measures on water transparency are unsure. This study integrates long-term Landsat satellite imagery with a machine learning model to estimate Secchi disk depth (Zsd), a critical indicator of lake transparency and ecological health. The model achieved an average absolute error of 13.4 cm, a root mean square error of 17.9 cm, and a coefficient of determination (R2) of 0.712.From 2013 to 2023, Zsd maps revealed significant seasonal fluctuations in transparency. Among the 24 monitored lakes, one exhibited an upward trend, while 11 showed declining trends. The analysis also identified a positive correlation between Zsd and water levels in Poyang and Dongting Lakes, suggesting that higher water levels contribute to higher transparency. However, short-term ecological measures, such as returning embankments to lakes, did not result in measurable improvements in Zsd. This study highlights the importance of systematic monitoring of lake transparency to assess ecosystem health. It demonstrates the potential of integrating remote sensing and machine learning for effective water management and provides a foundation for evaluating the long-term outcomes of ecological restoration policies.
期刊介绍:
The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published.
• All aspects of ecological and environmental indicators and indices.
• New indicators, and new approaches and methods for indicator development, testing and use.
• Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources.
• Analysis and research of resource, system- and scale-specific indicators.
• Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs.
• How research indicators can be transformed into direct application for management purposes.
• Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators.
• Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.