AIMC Topic: Water Pollution

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Adversarial susceptibility analysis for water quality prediction models.

Scientific reports
Water quality is a critical factor for human health and environmental sustainability. Rapid urbanization and industrialization have led to significant water contamination, increasing the prevalence of waterborne diseases. This study investigates the ...

Prediction of water quality parameters and pollution exceedance analysis in typical rivers of semi-arid regions based on interpretable deep learning models.

Environmental pollution (Barking, Essex : 1987)
Deep learning models that integrate environmental characteristics provide a powerful means for high-precision water quality prediction; however, their black-box nature can limit interpretability and reliability. We proposed an interpretable Attention...

Making waves: Is water quality trading a false promise for balancing ecology and economy?

Water research
Agriculture is a major contributor to water pollution through nutrient runoff and excessive water use, exacerbating global water scarcity and ecosystem degradation. Water Quality Trading (WQT) has emerged as a market-based mechanism to address this i...

Identifying and addressing challenges in gross pollutant trap maintenance: perspectives from the Australian stormwater industry.

Marine pollution bulletin
A common approach to removing pollution from stormwater is through the installation of gross pollutant traps (GPTs). However, GPTs are often not maintained effectively, leading to pollution accumulation and additional pollution bypassing into natural...

A novel deep learning-based floating garbage detection approach and its effectiveness evaluation in environmentally sustainable development.

Journal of environmental management
Floating garbage removal is an essential environmental strategy to reduce water pollution and achieve environmental sustainability, and it is a pressing issue for global ecological restoration. Under the interference of complex environments, floating...

Joint identification of hydraulic conductivity and groundwater pollution sources using unscented Kalman smoother with multiple data assimilation and deep learning.

Ecotoxicology and environmental safety
Identification of groundwater pollution sources (IGPSs) is a prerequisite for pollution remediation and pollution risk prediction. Data assimilation approaches have been used extensively in IGPSs field in recent years. A data assimilation approach-un...

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 surface water pollution using wavelet transform and 1D-CNN.

Water science and technology : a journal of the International Association on Water Pollution Research
Permanganate index (COD), total nitrogen, and ammonia nitrogen are important indicators that represent the degree of pollution of surface water. This study combined ultraviolet-visible (UV-vis) spectroscopy with a one-dimensional convolutional neural...

Measuring water pollution effects on antimicrobial resistance through explainable artificial intelligence.

Environmental pollution (Barking, Essex : 1987)
Antimicrobial resistance refers to the ability of pathogens to develop resistance to drugs designed to eliminate them, making the infections they cause more difficult to treat and increasing the likelihood of disease diffusion and mortality. As such,...

Identifying human activities causing water pollution based on microbial community sequencing and source classifier machine learning.

Environment international
Identifying and differentiating human activities is crucial for effectively preventing the threats posed by environmental pollution to aquatic ecosystems and human health. Machine learning (ML) is a powerful analytical tool for tracking human impacts...