AIMC Topic: Water Quality

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Tracking the spatiotemporal evolution of groundwater chemistry in the Quaternary aquifer system of Debrecen area, Hungary: integration of classical and unsupervised learning methods.

Environmental science and pollution research international Mar 1, 2025
Monitoring changes in groundwater quality over time helps identify time-dependent factors influencing water safety and supports the development of effective management strategies. This study investigates the spatiotemporal evolution of groundwater ch...
Groundwater Environmental Monitoring Water Pollutants, Chemical Principal Component Analysis Hungary Water Quality Cluster Analysis Unsupervised Machine Learning
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Developing a real-time water quality simulation toolbox using machine learning and application programming interface.

Journal of environmental management Feb 28, 2025
Rivers are vital for sustaining human life as they foster social development, provide drinking water, maintain aquatic ecosystems, and offer recreational spaces. However, most rivers are being increasingly contaminated by pollutants from non-point so...
Algorithms Nitrogen Neural Networks, Computer Phosphorus Environmental Monitoring Rivers Machine Learning Water Quality Water Pollutants, Chemical
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Enhanced water quality prediction model using advanced hybridized resampling alternating tree-based and deep learning algorithms.

Environmental science and pollution research international Feb 24, 2025
Water quality modeling in riverine systems is crucial for effective water resource management and pollution mitigation planning. However, the intricate interplay of anthropogenic activities with hydrological, climatic, and fluvial processes presents ...
Water Quality Rivers Deep Learning Environmental Monitoring Algorithms
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Change analysis of surface water clarity in the Persian Gulf and the Oman Sea by remote sensing data and an interpretable deep learning model.

Environmental science and pollution research international Feb 18, 2025
The health of an ecosystem and the quality of water can be determined by the clarity of the water. The Persian Gulf and Oman Sea have a unique ecosystem, and monitoring their water clarity is necessary for sustainable development. Here, various crite...
Deep Learning Environmental Monitoring Remote Sensing Technology Ecosystem Seawater Salinity Chlorophyll Indian Ocean Water Quality Chlorophyll A Oman
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Emerging applications of fluorescence excitation-emission matrix with machine learning for water quality monitoring: A systematic review.

Water research Feb 13, 2025
Fluorescence excitation-emission matrix (FEEM) spectroscopy is increasingly utilized in water quality monitoring due to its rapid, sensitive, and non-destructive measurement capabilities. The integration of machine learning (ML) techniques with FEEM ...
Water Quality Machine Learning Fluorescence Water Pollutants, Chemical Spectrometry, Fluorescence Environmental Monitoring
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Machine learning-based evolution of water quality prediction model: An integrated robust framework for comparative application on periodic return and jitter data.

Environmental pollution (Barking, Essex : 1987) Feb 9, 2025
Accurate water quality prediction is paramount for the sustainable management of surface water resources. Current deep learning models face challenges in reliably forecasting water quality due to the non-stationarity of environmental conditions and t...
Environmental Monitoring Water Quality Machine Learning Forecasting
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Integrated machine learning-based optimization framework for surface water quality index comparing coastal and non-coastal cases of Guangxi, China.

Marine pollution bulletin Feb 3, 2025
In this study, an optimized comprehensive water quality index (WQI) model framework is developed, which combines advanced machine learning technology to compare different types of surface water quality assessment. The proposed framework enhancement e...
China Water Quality Environmental Monitoring Machine Learning Rivers
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Assessing the impact of rainfall, topography, and human disturbances on nutrient levels using integrated machine learning and GAMs models in the Choctawhatchee River Watershed.

Journal of environmental management Jan 31, 2025
Nutrient pollution caused by excessive total nitrogen (TN) and total phosphorus (TP) is a significant environmental challenge globally, threatening water quality and ecosystem health. This study investigates the interplay between rainfall, topography...
Environmental Monitoring Water Pollutants, Chemical Water Quality Nitrogen Nutrients Humans Rivers Phosphorus Machine Learning Rain
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Integrating machine learning models for optimizing ecosystem health assessments through prediction of nitrate-N concentrations in the lower stretch of Ganga River, India.

Environmental science and pollution research international Jan 30, 2025
Nitrate, a highly reactive form of inorganic nitrogen, is commonly found in aquatic environments. Understanding the dynamics of nitrate-N concentration in rivers and its interactions with other water-quality parameters is crucial for effective freshw...
Water Pollutants, Chemical Nitrogen Water Quality Rivers Nitrates India Machine Learning Ecosystem Environmental Monitoring
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Attention-based deep learning models for predicting anomalous shock of wastewater treatment plants.

Water research Jan 23, 2025
Quickly grasping the time-consuming water quality indicators (WQIs) such as total nitrogen (TN) and total phosphorus (TP) of influent is an essential prerequisite for wastewater treatment plants (WWTPs) to prompt respond to sudden shock loads. Soft d...
Deep Learning Wastewater Neural Networks, Computer Phosphorus Waste Disposal, Fluid Water Purification Machine Learning Water Quality Nitrogen
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