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Lakes

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Integrating multisource data and machine learning for supraglacial lake detection: Implications for environmental management and sustainable development goals in high mountainous regions.

Journal of environmental management
The accurate detection and monitoring of supraglacial lakes in high mountainous regions are crucial for understanding their dynamic nature and implications for environmental management and sustainable development goals. In this study, we propose a no...

Projected response of algal blooms in global lakes to future climatic and land use changes: Machine learning approaches.

Water research
The eutrophication of lakes and the subsequent algal blooms have become significant environmental issues of global concern in recent years. With ongoing global warming and intensifying human activities, water quality trends in lakes worldwide varied ...

Habitat selection ecology of the aquatic beetle community using explainable machine learning.

Scientific reports
The aim of our work is to determine the importance of habitat features for the selection of the aquatic beetle community. Insects are represented by their general ecological traits such as body size, ecological element and trophic type, which are cat...

Leveraging explainable machine learning for enhanced management of lake water quality.

Journal of environmental management
Freshwater lakes worldwide suffer from eutrophication caused by excessive nutrient loads, particularly nitrogen (N) and phosphorus (P) from wastewater and runoff, affecting aquatic life and public health. Using a large (1800 km) subtropical lake as a...

Accurate prediction of pollution and health risks of iodinated X-ray contrast media in Taihu Lake with machine learning and revealing key environmental factors.

Water research
Iodinated X-ray contrast media (ICM) are commonly detected at considerable concentrations in aquatic environments. The long-term pollution trends in ICM at the whole lake/river scale have not yet been investigated; therefore, the risks associated wit...

Integrating machine learning and remote sensing for long-term monitoring of chlorophyll-a in Chilika Lagoon, India.

Environmental monitoring and assessment
Chlorophyll-a (Chla) is recognized as a key indicator of water quality and ecological health in aquatic ecosystems, offering valuable insights into ecosystem dynamics and changes over time. This study aimed to to develop and validate a robust ML mode...

Balanced hydropower and ecological benefits in reservoir-river-lake system: An integrated framework with machine learning and game theory.

Journal of environmental management
The negative impacts of large hydroelectric reservoirs on downstream ecosystems have attracted worldwide attention. Few attempts have been made to dynamically predict ecological benefits and rationally negotiation in the reservoir-river-lake (RRL) sy...

Dongting Lake algal bloom forecasting: Robustness and accuracy analysis of deep learning models.

Journal of hazardous materials
Harmful algal blooms (HABs) pose a significant threat to aquatic ecosystems, prompting efforts to predict their occurrence for swift action by water management agencies. Despite the potential for high-precision forecasting through machine learning, t...

Unsupervised learning for lake underwater vegetation classification: Constructing high-precision, large-scale aquatic ecological datasets.

The Science of the total environment
Monitoring underwater vegetation is vital for evaluating lake ecosystem health. Automated data collection and analysis play key roles in achieving large-scale, high-precision, and high-frequency monitoring. While technologies such as unmanned vessels...

Are more data always better? - Machine learning forecasting of algae based on long-term observations.

Journal of environmental management
Bloom-forming algae present a unique challenge to water managers as they can significantly impair provision of important ecosystem services and cause health risks to humans and animals. Consequently, effective short-term algae forecasts are important...