AIMC Topic: Rivers

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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
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...

Artificial intelligence based detection and control strategies for river water pollution: A comprehensive review.

Journal of contaminant hydrology
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. ...

Prediction of suspended sediment load in Sungai Semenyih using extreme learning machines and metaheuristic optimization approach.

Journal of environmental management
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...

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
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...

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
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...

Prediction of river dissolved oxygen (DO) based on multi-source data and various machine learning coupling models.

PloS one
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...

Developing a real-time water quality simulation toolbox using machine learning and application programming interface.

Journal of environmental management
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...

Enhanced water quality prediction model using advanced hybridized resampling alternating tree-based and deep learning algorithms.

Environmental science and pollution research international
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 ...

Integration of remote sensing and machine learning algorithm for agricultural drought early warning over Genale Dawa river basin, Ethiopia.

Environmental monitoring and assessment
Drought remains a menace in the Horn of Africa; as a result, the Ethiopia's Genale Dawa River Basin is one of the most vulnerable to agricultural drought. Hence, this study integrates remote sensing and machine learning algorithm for early warning id...

Integrated machine learning-based optimization framework for surface water quality index comparing coastal and non-coastal cases of Guangxi, China.

Marine pollution bulletin
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...