AIMC Topic: Groundwater

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Geochemical evolution, geostatistical mapping and machine learning predictive modeling of groundwater fluoride: a case study of western Balochistan, Quetta.

Environmental geochemistry and health
Around 2.6 billion people are at risk of tooth carries and fluorosis worldwide. Quetta is the worst affected district in Balochistan plateau. Endemic abnormal groundwater fluoride ( ) lacks spatiotemporal studies. This research integrates geospatial...

Recent advances in groundwater pollution research using machine learning from 2000 to 2023: A bibliometric analysis.

Environmental research
Groundwater pollution has become a global challenge, posing significant threats to human health and ecological environments. Machine learning, with its superior ability to capture non-linear relationships in data, has shown significant potential in a...

Enhancing groundwater quality prediction through ensemble machine learning techniques.

Environmental monitoring and assessment
Groundwater quality is assessed by conducting water sampling and laboratory analysis. Field-based measurements are costly and time-consuming. This study introduces a machine learning (ML)-based framework and innovative application of stacking ensembl...

Simulation and prediction of sulfamethazine migration, transformation and risk diffusion during cross-media infiltration from surface water to groundwater driven by dynamic water level: Machine learning coupled HYDRUS-GMS model.

Journal of environmental management
Seasonal water level fluctuations in rivers significantly influenced the cross-media migration, transformation, and risk diffusion of antibiotics from the vadose zone into groundwater. This study developed a coupled model integrating machine learning...

Prioritization of monitoring compounds from SNTS identified organic micropollutants in contaminated groundwater using a machine learning optimized ToxPi model.

Water research
Advanced suspect and non-target screening (SNTS) approach can identify a large number of potential hazardous micropollutants in groundwater, underscoring the need for pinpointing priority pollutants among detected chemicals. This present study theref...

Fuzzy multi-objective optimization for sustainable agricultural water management of irrigation networks.

Journal of environmental management
Sustainable water resource management in arid and water deficit regions requires optimal use of water resources due to competition among different water sectors. The purpose of this study is to model uncertainties in economic and hydro-climatic varia...

Unravelling integrated groundwater management in pollution-prone agricultural cities: A synergistic approach combining probabilistic risk, source apportionment and artificial intelligence.

Journal of hazardous materials
Groundwater is vital for agricultural cities, but intensive farming and fertilizer use have increased contamination risks, particularly for non-carcinogenic health hazards. This study reveals the sources of contaminants in groundwater, their health i...

Assessment of groundwater quality variation characteristics and influencing factors in an intensified agricultural area: An integrated hydrochemical and machine learning approach.

Journal of environmental management
The decline in groundwater quality in intensive agricultural areas in recent years, driven by environmental change and intensified human activity, poses a significant threat to agricultural production and public health, requiring attention and effect...

An integrated framework of deep learning and entropy theory for enhanced high-dimensional permeability field identification in heterogeneous aquifers.

Water research
Accurately estimating high-dimensional permeability (k) fields through data assimilation is critical for minimizing uncertainties in groundwater flow and solute transport simulations. However, designing an effective monitoring network to obtain diver...

Enhancing local-scale groundwater quality predictions using advanced machine learning approaches.

Journal of environmental management
Assessing groundwater quality typically involves labor-intensive, time-consuming, and costly laboratory tests, making real-time monitoring impractical, especially at the local level. Groundwater quality projections at the local scale using broad spat...