AIMC Topic: Lakes

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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...
Lakes Environmental Monitoring Neural Networks, Computer Water Quality Metals, Heavy Water Pollution, Chemical Water Pollutants, Chemical Turkey
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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 Phosphorus Water Quality Lakes Biological Oxygen Demand Analysis Machine Learning Environmental Monitoring Finland Ecosystem
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Hybrid WT-CNN-GRU-based model for the estimation of reservoir water quality variables considering spatio-temporal features.

Journal of environmental management Apr 9, 2024
Water quality indicators (WQIs), such as chlorophyll-a (Chl-a) and dissolved oxygen (DO), are crucial for understanding and assessing the health of aquatic ecosystems. Precise prediction of these indicators is fundamental for the efficient administra...
Machine Learning Algorithms Neural Networks, Computer Water Quality Wavelet Analysis Chlorophyll A Lakes Environmental Monitoring
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Spatiotemporal variation reconstruction of total phosphorus in the Great Lakes since 2002 using remote sensing and deep neural network.

Water research Mar 19, 2024
Total phosphorus (TP) is non-optically active, thus TP concentration (CTP) estimation using remote sensing still exists grand challenge. This study developed a deep neural network model (DNN) for CTP estimation with synchronous in-situ measurements a...
Seasons Neural Networks, Computer Remote Sensing Technology Environmental Monitoring Lakes Phosphorus
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Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States.

Environmental science & technology Mar 6, 2024
Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dyna...
Lakes Machine Learning United States
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An Intelligent Early Warning System for Harmful Algal Blooms: Harnessing the Power of Big Data and Deep Learning.

Environmental science & technology Mar 4, 2024
Harmful algal blooms (HABs) pose a significant ecological threat and economic detriment to freshwater environments. In order to develop an intelligent early warning system for HABs, big data and deep learning models were harnessed in this study. Data...
Harmful Algal Bloom Lakes Deep Learning Big Data Environmental Monitoring
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Employing hybrid deep learning for near-real-time forecasts of sensor-based algal parameters in a Microcystis bloom-dominated lake.

The Science of the total environment Feb 24, 2024
Harmful cyanobacterial blooms (CyanoHABs) are increasingly impacting the ecosystem of lakes, reservoirs and estuaries globally. The integration of real-time monitoring and deep learning technology has opened up new horizons for early warnings of Cyan...
Artificial Intelligence Ecosystem Cyanobacteria Harmful Algal Bloom Lakes Microcystis Deep Learning
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An optical mechanism-based deep learning approach for deriving water trophic state of China's lakes from Landsat images.

Water research Jan 24, 2024
Widespread eutrophication has been considered as the most serious environment problems in the world. Given the critical roles of lakes in human society and serious negative effects of water eutrophication on lake ecosystems, it is thus fundamentally ...
Environmental Monitoring China Water Humans Lakes Ecosystem Deep Learning Eutrophication
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Optimisation and interpretation of machine and deep learning models for improved water quality management in Lake Loktak.

Journal of environmental management Dec 25, 2023
Loktak Lake, one of the largest freshwater lakes in Manipur, India, is critical for the eco-hydrology and economy of the region, but faces deteriorating water quality due to urbanisation, anthropogenic activities, and domestic sewage. Addressing the ...
Environmental Monitoring Deep Learning Water Quality Ecosystem India Lakes
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Deep learning-based efficient drone-borne sensing of cyanobacterial blooms using a clique-based feature extraction approach.

The Science of the total environment Dec 23, 2023
Recent advances in remote sensing techniques provide a new horizon for monitoring the spatiotemporal variations of harmful algal blooms (HABs) using hyperspectral data in inland water. In this study, a hierarchical concatenated variational autoencode...
Plants Harmful Algal Bloom Cyanobacteria Chlorophyll A Deep Learning Lakes Unmanned Aerial Devices Environmental Monitoring
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