AIMC Topic: Rivers

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Spatiotemporal variations in Pearl River plume dispersion over the last decade based on VIIRS-derived sea surface salinity.

Marine pollution bulletin May 22, 2025
A river plume indicates the dispersion and transport path of pollutants from runoff, monitoring the spatiotemporal variation of river plume distribution from space is crucial for marine environmental governance. This study focuses on the Pearl River ...
Seawater Salinity Water Movements Satellite Imagery Environmental Monitoring Rivers Spatio-Temporal Analysis China Machine Learning
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Synergistic effects of environmental factors on benthic diversity: Machine learning analysis.

Water research May 6, 2025
This study examines the water environmental factors of the Cangshan stream and benthic animal communities by using random forest, gradient boosting decision tree, and support vector machine models to analyze the complex response mechanisms of benthic...
Rivers Invertebrates Biodiversity Phosphorus Machine Learning Temperature Oxygen Nitrogen Animals
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Bayesian-optimized recursive machine learning for predicting human-induced changes in suspended sediment transport.

Environmental monitoring and assessment Apr 26, 2025
The suspended sediment load (SSL) of a river is a key indicator of water resource management, river morphology, and ecosystem health. This study analyzes historical changes in SSL and evaluates machine learning (ML) models for SSL prediction in the G...
Rivers Environmental Monitoring Bayes Theorem Geologic Sediments Humans Machine Learning
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Efficient urban flood control and drainage management framework based on digital twin technology and optimization scheduling algorithm.

Water research Apr 22, 2025
Urban flood control and drainage systems often face significant challenges in coordinating municipal drainage with river-lake flood prevention during flood seasons. Rising river levels can create backwater effects, which substantially increase urban ...
Cities Rivers Floods Algorithms Lakes
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Assessing the impacts of cascade reservoirs on Pearl River environmental status using machine learning and satellite-derived chlorophyll-a concentrations.

Journal of environmental management Apr 18, 2025
Rivers play a crucial role in in global matter cycling and energy flow, contributing significantly to biogeochemical cycles and the development of human civilization. Reservoirs, as prevalent artificial water bodies, modify river flow and impact ener...
Rivers Machine Learning Chlorophyll A China Ecosystem Environmental Monitoring
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Statistical analysis and prediction via neural networks of water quality in the Middle Paraíba do Sul (Rio de Janeiro State, Brazil) region in the period (2012-2022).

Environmental science and pollution research international Apr 3, 2025
The aim of this study is to accurately predict the water quality at these points over a decade through the combined use of statistical tools and artificial intelligence. This study brings the innovative use of neural networks implemented with the GRN...
Environmental Monitoring Water Quality Rivers Neural Networks, Computer Brazil
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Feasibility study of real-time virtual sensing for water quality parameters in river systems using synthetic data and deep learning models.

Journal of environmental management Apr 2, 2025
With water quality management crucial for environmental sustainability, multiple techniques for real-time monitoring and estimation of water quality parameters have been developed. However, certain data types, such as airborne images, are only access...
Feasibility Studies Nitrogen Water Quality Rivers Phosphorus Water Pollutants, Chemical Carbon Deep Learning Environmental Monitoring
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Water quality parameters-based prediction of dissolved oxygen in estuaries using advanced explainable ensemble machine learning.

Journal of environmental management Apr 1, 2025
The dissolved oxygen (DO) is crucial for the ecological health of estuaries and bays. However, human activities, land-sea interactions, and the unclear impact mechanisms of water quality parameters (WQPs) pose challenges to DO prediction. Water quali...
Nitrogen Water Quality Estuaries Rivers Environmental Monitoring Machine Learning Oxygen China
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Are we underestimating the driving factors and potential risks of freshwater microplastics from in situ and in silico perspective?

Water research Mar 28, 2025
The high loads of heterogeneous microplastics (MPs) in water system sparked the exploration of MPs source and impact in the environment. However, the contributions of driving factors to MPs contamination and the potential risks posed by multidimensio...
Machine Learning Computer Simulation Environmental Monitoring Microplastics Water Pollutants, Chemical Rivers Fresh Water
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Temporal and spatial feature extraction using graph neural networks for multi-point water quality prediction in river network areas.

Water research Mar 26, 2025
Deep learning methods have demonstrated strong capabilities in capturing nonlinear relationships for water quality prediction, yet existing studies predominantly focus on individual monitoring sites while neglecting pollutant spatial dynamics. To add...
Nitrogen Water Quality Environmental Monitoring Oxygen Rivers Graph Neural Networks Neural Networks, Computer
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