AIMC Topic: Water Quality

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Using machine learning models to estimate Escherichia coli concentration in an irrigation pond from water quality and drone-based RGB imagery data.

Water research
The rapid and efficient quantification of Escherichia coli concentrations is crucial for monitoring water quality. Remote sensing techniques and machine learning algorithms have been used to detect E. coli in water and estimate its concentrations. Th...

Groundwater suitability assessment for irrigation and drinking purposes by integrating spatial analysis, machine learning, water quality index, and health risk model.

Environmental science and pollution research international
An in-depth understanding of nitrate-contaminated surface water and groundwater quality and associated risks is important for groundwater management. Hydrochemical characteristics and driving forces of groundwater quality and non-carcinogenic risks o...

A case study of using artificial neural networks to predict heavy metal pollution in Lake Iznik.

Environmental monitoring and assessment
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...

Forecasting fish mortality from water and air quality data using deep learning models.

Journal of environmental quality
The high rate of aquatic mortality incidents recorded in Taiwan and worldwide is creating an urgent demand for more accurate fish mortality prediction. Present study innovatively integrated air and water quality data to measure water quality degradat...

Incorporation of water quality index models with machine learning-based techniques for real-time assessment of aquatic ecosystems.

Environmental pollution (Barking, Essex : 1987)
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...

Machine learning-driven prediction of phosphorus removal performance of metal-modified biochar and optimization of preparation processes considering water quality management objectives.

Bioresource technology
Developing an optimized and targeted design approach for metal-modified biochar based on water quality conditions and management is achievable through machine learning. This study leveraged machine learning to analyze experimental data on phosphate a...

Integrating machine learning models with cross-validation and bootstrapping for evaluating groundwater quality in Kanchanaburi province, Thailand.

Environmental research
Exploring the potential of new models for mapping groundwater quality presents a major challenge in water resource management, particularly in Kanchanaburi Province, Thailand, where groundwater faces contamination risks. This study aimed to explore t...

Enhancing water quality prediction for fluctuating missing data scenarios: A dynamic Bayesian network-based processing system to monitor cyanobacteria proliferation.

The Science of the total environment
Tackling the impact of missing data in water management is crucial to ensure the reliability of scientific research that informs decision-making processes in public health. The goal of this study is to ascertain the root causes associated with cyanob...

Hybrid WT-CNN-GRU-based model for the estimation of reservoir water quality variables considering spatio-temporal features.

Journal of environmental management
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...

Graph neural network-based anomaly detection for river network systems.

F1000Research
BACKGROUND: Water is the lifeblood of river networks, and its quality plays a crucial role in sustaining both aquatic ecosystems and human societies. Real-time monitoring of water quality is increasingly reliant on in-situ sensor technology.Anomaly d...