AIMC Topic: Water Quality

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Prediction of trihalomethane occurrence and cancer risk using interpretable machine learning and virtual data augmentation.

Journal of hazardous materials
Trihalomethanes (THMs) in drinking water are regulated for carcinogenic health risks. However, frequent water quality monitoring imposes significant resource burdens. This study proposes a framework integrating interpretable machine learning (ML) wit...

Advancing wetland groundwater pollution zoning: A novel integration of Monte Carlo health risk modeling and machine learning.

Journal of hazardous materials
Wetlands serve as crucial water reservoirs, providing essential water resources for the surrounding regions. However, elevated ion concentrations in wetland groundwater may pose health risks to local populations. This study focused on Judian Lake and...

Review on sea water quality (SWQ) monitoring using satellite remote sensing techniques (SRST).

Marine pollution bulletin
Due to extensive anthropogenic activities in coastal areas and rivers connected to the seas, effective and timely monitoring the sea water quality (SWQ) is crucial for maintaining ecosystem health. SWQ monitoring involves examining the chemical, phys...

Integrating Regression and Boosting Techniques for Enhanced River Water Quality Monitoring in the Cauvery Basin: A Seasonal and Sustainable Approach.

Water environment research : a research publication of the Water Environment Federation
This study addresses a critical research gap in water quality monitoring, specifically within the Cauvery River basin, where substantial contamination poses significant risks to both human health and aquatic ecosystems. The paper introduces an effect...

Long-term water quality simulation and driving factors identification within the watershed scale using machine learning.

Journal of contaminant hydrology
Understanding long-term trends and analyzing their driving factors are essential to effectively enhance water quality in watersheds. In China, although the overall quality of surface water continues to improve, significant issues remain in certain re...

Federated Machine Learning Enables Risk Management and Privacy Protection in Water Quality.

Environmental science & technology
Real-time water quality risk management in wastewater treatment plants (WWTPs) requires extensive data, and data sharing is still just a slogan due to data privacy issues. Here we show an adaptive water system federated averaging (AWSFA) framework ba...

A Comprehensive Exploration of Groundwater Quality of Ambagarh Chowki Region, Chhattisgarh, India: Water Quality Index, Health Risk, and ANN Predictive Modeling.

Water environment research : a research publication of the Water Environment Federation
Access to safe and clean drinking water remains a critical global challenge, with groundwater as a primary source for billions of people. Further, toxic contaminants increasingly threaten groundwater quality, posing significant health risks. This stu...

Improving real-time forecasting of bay water quality by integrating in-situ monitoring, machining learning, and process-based modeling.

Journal of environmental management
Frequent occurrences of disasters such as red tides significantly threaten bay ecosystems, making near real-time water quality forecasting crucial for disaster warning and decision-making. Conventional techniques, such as process-based modeling and i...

Prediction of enhanced coagulation with varied pre-oxidations for seasonal variations of cyanobacteria-dominated algae-laden water quality.

Journal of environmental management
Enhanced coagulation with pre-oxidation is a cost-effective approach for managing seasonal water quality pollution caused by algal outbreaks and deaths. The synergistic application of pre-oxidants and coagulants, coupled with intelligent and precise ...

Enhancing drinking water safety: Real-time prediction of trihalomethanes in a water distribution system using machine learning and multisensory technology.

Ecotoxicology and environmental safety
Prolonged exposure to high concentrations of trihalomethanes (THMs) may generate human health risks due to their carcinogenic and mutagenic properties. Therefore, monitoring THMs in drinking water distribution systems (DWDS) is essential. This study ...