AIMC Topic: Lakes

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

Scientific reports Nov 21, 2024
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...
Body Size Machine Learning Animals Ecosystem Lakes Coleoptera
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Leveraging explainable machine learning for enhanced management of lake water quality.

Journal of environmental management Oct 13, 2024
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...
Algorithms Eutrophication Lakes Machine Learning Phosphorus Water Quality Florida Environmental Monitoring Nitrogen
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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 Sep 24, 2024
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...
Machine Learning Lakes Environmental Monitoring Neural Networks, Computer Sustainable Development Ice Cover Support Vector Machine Pakistan
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Long-term trend forecast of chlorophyll-a concentration over eutrophic lakes based on time series decomposition and deep learning algorithm.

The Science of the total environment Aug 10, 2024
Long-term trend forecast of chlorophyll-a concentration (Chla) holds significant implications for eutrophication management and pollution control planning on lakes, especially under the background of climate change. However, it is a challenging task ...
Chlorophyll Chlorophyll A Seasons Climate Change China Environmental Monitoring Forecasting Lakes Deep Learning Eutrophication
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Machine learning-based analysis of heavy metal contamination in Chinese lake basin sediments: Assessing influencing factors and policy implications.

Ecotoxicology and environmental safety Aug 1, 2024
Sediments are important heavy metal sinks in lakes, crucial for ensuring water environment safety. Existing studies mainly focused on well-studied lakes, leaving gaps in understanding pollution patterns in specific basins and influencing factors.We c...
Rivers Metals, Heavy Geologic Sediments Environmental Monitoring Water Pollutants, Chemical Environmental Policy Lakes China Machine Learning
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Predicting abrupt depletion of dissolved oxygen in Chaohu lake using CNN-BiLSTM with improved attention mechanism.

Water research Jul 3, 2024
Depletion of dissolved oxygen (DO) is a significant incentive for biological catastrophic events in freshwater lakes. Although predicting the DO concentrations in lakes with high-frequency real-time data to prevent hypoxic events is effective, few re...
Water Quality China Neural Networks, Computer Environmental Monitoring Lakes Oxygen
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Analyzing variation of water inflow to inland lakes under climate change: Integrating deep learning and time series data mining.

Environmental research Jun 23, 2024
The alarming depletion of global inland lakes in recent decades makes it essential to predict water inflow from rivers to lakes (WIRL) trend and unveil the dominant influencing driver, particularly in the context of climate change. The raw time serie...
Lakes Deep Learning Climate Change Environmental Monitoring Data Mining
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Exploring spatiotemporal patterns of algal cell density in lake Dianchi with explainable machine learning.

Environmental pollution (Barking, Essex : 1987) Jun 18, 2024
The escalating global occurrence of algal blooms poses a growing threat to ecosystem services. In this study, the spatiotemporal heterogeneity of water quality parameters was leveraged to partition Lake Dianchi into three clusters. Considering water ...
Ecosystem Eutrophication Environmental Monitoring Water Quality Lakes Machine Learning
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A case study of using artificial neural networks to predict heavy metal pollution in Lake Iznik.

Environmental monitoring and assessment May 29, 2024
Artificial neural networks offer a viable route in assessing and understanding the presence and concentration of heavy metals that can cause dangerous complications in the wider context of water quality prediction for the sustainability of the ecosys...
Environmental Monitoring Water Pollutants, Chemical Turkey Neural Networks, Computer Lakes Water Pollution, Chemical Water Quality Metals, Heavy
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Incorporation of water quality index models with machine learning-based techniques for real-time assessment of aquatic ecosystems.

Environmental pollution (Barking, Essex : 1987) May 27, 2024
Water quality index (WQI) is a well-established tool for assessing the overall quality of fresh inland-waters. However, the effectiveness of real-time assessment of aquatic ecosystems using the WQI is usually impacted by the absence of some water qua...
Water Pollutants, Chemical Lakes Phosphorus Machine Learning Biological Oxygen Demand Analysis Water Quality Environmental Monitoring Ecosystem Finland
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