AIMC Topic: Lakes
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Global dominance of seasonality in shaping lake-surface-extent dynamics.
Nature
May 28, 2025
Lakes are crucial for ecosystems, greenhouse gas emissions and water resources, yet their surface-extent dynamics, particularly seasonality, remain poorly understood at continental to global scales owing to limitations in satellite observations. Alth...
Optimizing Watershed Land Use to Achieve the Benefits of Lake Carbon Sinks while Maintaining Water Quality.
Environmental science & technology
May 6, 2025
Greenhouse gas emissions and water quality decline are two major issues currently affecting lakes worldwide. Determining how to control both greenhouse gas emissions and water quality decline is a long-term challenge. We compiled data on the annual a...
Inversion of lake transparency using remote sensing and deep hybrid recurrent models.
Ecotoxicology and environmental safety
Apr 26, 2025
Utilizing computer technology and remote sensing data, the extraction of water-related features of lakes has become a hot topic in lake ecological research. Addressing challenges like the high optical complexity of lake water bodies, the inadequacy o...
Water quality parameters retrieval and nutrient status evaluation based on machine learning methods and Sentinel- 2 imagery: a case study of the Hongjiannao Lake.
Environmental monitoring and assessment
Apr 15, 2025
A timely and accurate understanding of lake water quality is significant for maintaining ecological balance, ensuring water resource security, and promoting regional sustainable development. However, due to the varying numerical ranges and characteri...
U-shaped deep learning networks for algal bloom detection using Sentinel-2 imagery: Exploring model performance and transferability.
Journal of environmental management
Apr 3, 2025
Inland water sources, such as lakes, support diverse ecosystems and provide essential services to human societies. However, these valuable resources are under increasing pressure from rapid climate changes and pollution resulting from human activitie...
Identification of key feature variables and prediction of harmful algal blooms in a water diversion lake based on interpretable machine learning.
Environmental research
Mar 28, 2025
Harmful algal blooms (HABs) as an increasing environmental problem in lakes, and water diversion has become a common and effective strategy for mitigating HABs. Early and accurate identification of the occurrence of HABs in lakes is essential for sci...
Comparing the performance of 10 machine learning models in predicting Chlorophyll a in western Lake Erie.
Journal of environmental management
Mar 17, 2025
Algal blooms, which have substantial adverse effects, are increasingly occurring worldwide in the context of global warming and eutrophication. Machine learning models (MLMs) are emerging as efficient and promising tools for predicting algal blooms. ...
Integrating partial least square structural equation modelling and machine learning for causal exploration of environmental phenomena.
Environmental research
Mar 11, 2025
Understanding the causes of environmental phenomena is crucial for promoting positive outcomes and mitigating negative ones. Partial least squares structural equation modelling (PLS-SEM) is becoming a valuable tool for evaluating causal relationships...
Interconnections, trend analysis and forecasting of water-air temperature with water level dynamics in Blue Moon Lake Valley: A statistical and machine learning approach.
Journal of environmental management
Mar 8, 2025
Glacier-fed lakes serve as vital indicators of climate change, yet their temperature and water level dynamics are insufficiently studied, particularly in high-altitude basins. Examining these interactions is fundamental for the effective management o...
Dissolved organic carbon estimation in lakes: Improving machine learning with data augmentation on fusion of multi-sensor remote sensing observations.
Water research
Feb 21, 2025
This paper presents a novel approach for estimating Dissolved Organic Carbon (DOC) concentrations in lakes considering both carbon sources and sink operators. Despite the critical role of DOC, the combined application of machine learning, as a robust...
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