AIMC Topic: Groundwater

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Assessing current and future available resources to supply urban water demands using a high-resolution SWAT model coupled with recurrent neural networks and validated through the SIMPA model in karstic Mediterranean environments.

Environmental science and pollution research international Jul 24, 2024
Hydrological simulation in karstic areas is a hard task due to the intrinsic intricacy of these environments and the common lack of data related to their geometry. Hydrological dynamics of karstic sites in Mediterranean semiarid regions are difficult...
Environmental Monitoring Spain Models, Theoretical Groundwater Water Supply Hydrology Neural Networks, Computer
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Groundwater salinity modeling and mapping using machine learning approaches: a case study in Sidi Okba region, Algeria.

Environmental science and pollution research international Jul 23, 2024
The groundwater salinization process complexity and the lack of data on its controlling factors are the main challenges for accurate predictions and mapping of aquifer salinity. For this purpose, effective machine learning (ML) methodologies are empl...
Salinity Algeria Environmental Monitoring Support Vector Machine Machine Learning Models, Theoretical Groundwater
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Solving water scarcity challenges in arid regions: A novel approach employing human-based meta-heuristics and machine learning algorithm for groundwater potential mapping.

Chemosphere Jul 20, 2024
Addressing water scarcity challenges in arid regions is a pressing concern and demands innovative solutions for accurate groundwater potential mapping (GPM). This study presents a comprehensive evaluation of advanced modeling techniques to enhance th...
Water Supply Computer Heuristics Humans Machine Learning Groundwater Algorithms Iran
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A machine learning approach to investigate the impact of land use land cover (LULC) changes on groundwater quality, health risks and ecological risks through GIS and response surface methodology (RSM).

Journal of environmental management Jul 19, 2024
Groundwater resources are enormously affected by land use land cover (LULC) dynamics caused by increasing urbanisation, agricultural and household discharge as a result of global population growth. This study investigates the impact of decadal LULC c...
Humans Machine Learning India Agriculture Geographic Information Systems Bayes Theorem Water Quality Groundwater Environmental Monitoring
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Groundwater health risk assessment and its temporal and spatial evolution based on trapezoidal fuzzy number-Monte Carlo stochastic simulation: A case study in western Jilin province.

Ecotoxicology and environmental safety Jul 17, 2024
The United States Environmental Protection Agency (USEPA) Four-step-Method (FSM) is a straightforward and extensively utilized tool for evaluating regional health risks, However, the complex and heterogeneous groundwater environment system causes gre...
Monte Carlo Method Stochastic Processes Fuzzy Logic Water Quality Uncertainty Spatio-Temporal Analysis China Environmental Monitoring Water Pollutants, Chemical Groundwater Humans Risk Assessment
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Bee-inspired insights: Unleashing the potential of artificial bee colony optimized hybrid neural networks for enhanced groundwater level time series prediction.

Environmental monitoring and assessment Jul 11, 2024
Analysis of the change in groundwater used as a drinking and irrigation water source is of critical importance in terms of monitoring aquifers, planning water resources, energy production, combating climate change, and agricultural production. Theref...
Environmental Monitoring Bees Animals Neural Networks, Computer Algorithms Groundwater
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Integrating deep learning and regression models for accurate prediction of groundwater fluoride contamination in old city in Bitlis province, Eastern Anatolia Region, Türkiye.

Environmental science and pollution research international Jul 11, 2024
Groundwater resources in Bitlis province and its surroundings in Türkiye's Eastern Anatolia Region are pivotal for drinking water, yet they face a significant threat from fluoride contamination, compounded by the region's volcanic rock structure. To ...
Fluorides Cities Turkey Environmental Monitoring Groundwater Water Pollutants, Chemical Deep Learning
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Prediction of arsenic concentration in groundwater of Chapainawabganj, Bangladesh: machine learning-based approach to spatial modeling.

Environmental science and pollution research international Jul 9, 2024
Groundwater in northwestern parts of Bangladesh, mainly in the Chapainawabganj District, has been contaminated by arsenic. This research documents the geographical distribution of arsenic concentrations utilizing machine learning techniques. The stud...
Machine Learning Water Pollutants, Chemical Arsenic Bangladesh Groundwater Environmental Monitoring
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The weighted multi-scale connections networks for macrodispersivity estimation.

Journal of contaminant hydrology Jul 5, 2024
Macrodispersivity is critical for predicting solute behaviors with dispersive transport models. Conventional methods of estimating macrodispersivity usually need to solve flow equations and are time-consuming. Convolutional neural networks (CNN) have...
Models, Theoretical Groundwater Water Movements Neural Networks, Computer
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Assessment of groundwater quality in arid regions utilizing principal component analysis, GIS, and machine learning techniques.

Marine pollution bulletin Jun 25, 2024
Assessing water quality in arid regions is vital due to scarce resources, impacting health and sustainable management.This study examines groundwater quality in Assuit Governorate, Egypt, using Principal Component Analysis, GIS, and Machine Learning ...
Water Pollutants, Chemical Groundwater Principal Component Analysis Environmental Monitoring Machine Learning Water Quality Egypt Geographic Information Systems
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