AIMC Topic: Rivers

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Assessing climate change and human impacts on runoff and hydrological droughts in the Yellow River Basin using a machine learning-enhanced hydrological modeling approach.

Journal of environmental management Mar 26, 2025
Analyzing the impacts of climate change (CC) and human activities (HA) on hydrological events is important for water resource management. This study quantifies the impacts of CC and HA on runoff and hydrological drought characteristics (HDC) in the Y...
Droughts Humans Hydrology Machine Learning Rivers Models, Theoretical Climate Change Environmental Monitoring China
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Advancing flood risk assessment: Multitemporal SAR-based flood inventory generation using transfer learning and hybrid fuzzy-AHP-machine learning for flood susceptibility mapping in the Mahananda River Basin.

Journal of environmental management Mar 22, 2025
The Mahananda River basin, located in Eastern India, faces escalating flood risks due to its complex hydrology and geomorphology, threatening socioeconomic and environmental stability. This study presents a novel approach to flood susceptibility (FS)...
Machine Learning Risk Assessment Fuzzy Logic India Rivers Floods
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Sentinel-2 imagery coupled with machine learning to modelling water turbidity in the Doce River Basin, Brazil.

Environmental monitoring and assessment Mar 22, 2025
Remote sensing and machine learning are techniques that can be used to monitor water quality properties, surpassing the limitations of the conventional techniques. Turbidity is an important water quality property directly influenced by the Fundão dam...
Water Pollutants, Chemical Remote Sensing Technology Rivers Water Quality Brazil Environmental Monitoring Machine Learning
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Artificial intelligence based detection and control strategies for river water pollution: A comprehensive review.

Journal of contaminant hydrology Mar 17, 2025
Water quality (WQ) is a metric for assessing the overall health and safety of water bodies like a river. Owing to the habitation of anthropogenic habitation around its basin, the rivers can become one of the most contaminated water sources globally. ...
Neural Networks, Computer Water Quality Rivers Water Pollutants, Chemical Water Pollution Artificial Intelligence Environmental Monitoring
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Prediction of suspended sediment load in Sungai Semenyih using extreme learning machines and metaheuristic optimization approach.

Journal of environmental management Mar 17, 2025
Suspended sediment load (SSL) refers to sediment particles, such as silt and clay, that are suspended in water. It plays a critical role in hydrology and water quality management, influencing factors such as water quality, river erosion, sedimentatio...
Machine Learning Environmental Monitoring Water Quality Extreme Learning Machines Rivers Geologic Sediments
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Integrated machine learning based groundwater quality prediction through groundwater quality index for drinking purposes in a semi-arid river basin of south India.

Environmental geochemistry and health Mar 14, 2025
The main objective of this study is to predict and monitor groundwater quality through the use of modern Machine Learning (ML) techniques. By employing ML techniques, the research effectively evaluates groundwater quality to forecast its future trend...
Machine Learning India Groundwater Water Quality Rivers Drinking Water Environmental Monitoring Water Pollutants, Chemical
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AI-aided chronic mixture risk assessment along a small European river reveals multiple sites at risk and pharmaceuticals being the main risk drivers.

Environment international Mar 13, 2025
The vast amount of registered chemicals leads to a high diversity of substances occurring in the environment and the creation of new substances outpaces chemical risk assessment as well as monitoring strategies. Hence, risk assessment strategies need...
Animals Risk Assessment Water Pollutants, Chemical Artificial Intelligence Pharmaceutical Preparations Environmental Monitoring Rivers Germany
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Prediction of river dissolved oxygen (DO) based on multi-source data and various machine learning coupling models.

PloS one Mar 4, 2025
Too low a concentration of dissolved oxygen (DO) in a river can disrupt the ecological balance, while too high a concentration may lead to eutrophication of the water body and threaten the health of the aquatic environment. Therefore, accurate predic...
Principal Component Analysis Oxygen Rivers Water Quality Models, Theoretical Machine Learning Algorithms Environmental Monitoring
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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...
Environmental Monitoring Water Pollutants, Chemical Machine Learning Algorithms Water Quality Rivers Nitrogen Phosphorus Neural Networks, Computer
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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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