AIMC Topic: Groundwater

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Impact of long-term mining activity on groundwater dynamics in a mining district in Xinjiang coal Mine Base, Northwest China: insight from geochemical fingerprint and machine learning.

Environmental science and pollution research international
Long-term coal mining could lead to a serious of geo-environmental problems. However, less comprehensive identification of factors controlling the groundwater dynamics were involved in previous studies. This study focused on 68 groundwater samples co...

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...

Statistical and machine learning analysis for the application of microbially induced carbonate precipitation as a physical barrier to control seawater intrusion.

Journal of contaminant hydrology
Seawater intrusion in coastal aquifers is a significant problem that can be addressed through the construction of subsurface dams or physical cut-off barriers. An alternative method is the use of microbially induced carbonate precipitation (MICP) to ...

A fuzzy interval dynamic optimization model for surface and groundwater resources allocation under water shortage conditions, the case of West Azerbaijan Province, Iran.

Environmental science and pollution research international
The allocation of water in areas which face shortage of water especially during hot dry seasons is of utmost importance. This is normally affected by various factors, the management of which takes a lot of time and energy with efforts falling inferti...

A new strategy for groundwater level prediction using a hybrid deep learning model under Ecological Water Replenishment.

Environmental science and pollution research international
Accurate prediction of the groundwater level (GWL) is crucial for sustainable groundwater resource management. Ecological water replenishment (EWR) involves artificially diverting water to replenish the ecological flow and water resources of both sur...

Comparative study for coastal aquifer vulnerability assessment using deep learning and metaheuristic algorithms.

Environmental science and pollution research international
Coastal aquifer vulnerability assessment (CAVA) studies are essential for mitigating the effects of seawater intrusion (SWI) worldwide. In this research, the vulnerability of the coastal aquifer in the Lahijan region of northwest Iran was investigate...

Spatiotemporal assessment of groundwater quality and quantity using geostatistical and ensemble artificial intelligence tools.

Journal of environmental management
The study investigated the spatiotemporal relationship between surface hydrological variables and groundwater quality/quantity using geostatistical and AI tools. AI models were developed to estimate groundwater quality from ground-based measurements ...

Groundwater quality index development using the ANN model of Delhi Metropolitan City, India.

Environmental science and pollution research international
Groundwater is widely recognized as a vital source of fresh drinking water worldwide. However, the rapid, unregulated population growth and increased industrialization, coupled with a rise in human activities, have significantly harmed the quality of...

A fuzzy logic-based approach for groundwater vulnerability assessment.

Environmental science and pollution research international
Groundwater vulnerability assessment systems have been developed to protect groundwater resources. The DRASTIC model calculates the vulnerability index of the aquifer based on seven effective parameters. The application of expert opinion in rating an...

Identification of light nonaqueous phase liquid groundwater contamination source based on empirical mode decomposition and deep learning.

Environmental science and pollution research international
The simulation optimization method was used to the identification of light nonaqueous phase liquid (LNAPL) groundwater contamination source (GCS) with the help of a hypothetical case in this study. When applying the simulation optimization method to ...