Recent advances in groundwater pollution research using machine learning from 2000 to 2023: a bibliometric analysis DOI
Xuan Li, Guohua Liang, Bin He

et al.

Environmental Research, Journal Year: 2024, Volume and Issue: 267, P. 120683 - 120683

Published: Dec. 20, 2024

Language: Английский

Comparative Assessment of Machine Learning Models for Groundwater Quality Prediction Using Various Parameters DOI
Majid Niazkar, Reza Piraei, Mohammad Reza Goodarzi

et al.

Environmental Processes, Journal Year: 2025, Volume and Issue: 12(1)

Published: Feb. 11, 2025

Language: Английский

Citations

4
Machine learning-enhanced GALDIT modeling for the Nile Delta aquifer vulnerability assessment in the Mediterranean region DOI
Zenhom E. Salem,

Nesma A. Arafa,

Abdelaziz Abdeldayem

et al.

Groundwater for Sustainable Development, Journal Year: 2025, Volume and Issue: 28, P. 101403 - 101403

Published: Jan. 7, 2025

Language: Английский

Citations

2
Predictive modeling of fractional plankton-assisted cholera propagation dynamics using Bayesian regularized deep cascaded exogenous neural networks DOI

A. V. Sultan,

Muhammad Junaid Ali Asif Raja,

Chuan‐Yu Chang

et al.

Process Safety and Environmental Protection, Journal Year: 2025, Volume and Issue: unknown, P. 106819 - 106819

Published: Feb. 1, 2025

Language: Английский

Citations

1
Geochemical and isotopic studies of the Douda-Damerjogue aquifer (Republic of Djibouti): Origin of high nitrate and fluoride, spatial distribution, associated health risk assessment and prediction of water quality using machine learning DOI
M.O. Awaleh, Tiziano Boschetti,

Christelle Marlin

et al.

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 967, P. 178789 - 178789

Published: Feb. 14, 2025

Language: Английский

Citations

1
Assessing groundwater quality and suitability in Qatar: Strategic insights for sustainable water management and environmental protection DOI Creative Commons
Sarra Aloui, Adel Zghibi, Annamaria Mazzoni

et al.

Environmental and Sustainability Indicators, Journal Year: 2025, Volume and Issue: unknown, P. 100582 - 100582

Published: Jan. 1, 2025

Language: Английский

Citations

0
A Novel Method to Forecast Nitrate Concentration Levels in Irrigation Areas for Sustainable Agriculture DOI Creative Commons
Halil Karahan, Müge Erkan Can

Agriculture, Journal Year: 2025, Volume and Issue: 15(2), P. 161 - 161

Published: Jan. 13, 2025

This study developed an ANN-based model to predict nitrate concentrations in drainage waters using parameters that are simpler and more cost-effective measure within the Lower Seyhan Basin, a key agricultural region Turkey. For this purpose, daily water samples were collected from measurement station during 2022 2023 years, determined laboratory. In addition concentrations, other parameters, such as flow rate, EC, pH, precipitation, also measured simultaneously. The complex relationship between values which easier less costly measure, was used two different scenarios training phase of ANN-Nitrate model. After trained, estimated for only parameters. Scenario I, random dataset predicted, while II, predictions made time series, results compared with both scenarios. proposed reliably fills gaps (Scenario I) predicts series II). model, although based on artificial neural network (ANN), has potential be adapted methods machine learning intelligence, Support Vector Machines, Decision Trees, Random Forests, Ensemble Learning Methods.

Language: Английский

Citations

0
Research on the Features and Driving Factors of Shallow Groundwater Quality in Arid Areas, Northwest China DOI Open Access
Long Wang, Nan Yang, Yang Zhao

et al.

Water, Journal Year: 2025, Volume and Issue: 17(7), P. 934 - 934

Published: March 22, 2025

Given the increasing threat of groundwater pollution, comprehending trends and influencing factors quality variation is essential for effective mitigation strategies. This study addresses variations in Beichuan River, a critical area China’s arid region. Using hydrochemical analysis multivariate statistics, we identified key quality. Groundwater mildly alkaline, with HCO3−-Ca as dominant type. The concentrations major ions increase during high-flow period due to rainfall effects. dissolution rock salt primarily contributes presence Na+ Cl− ions. Meanwhile, weathering silicate carbonate rocks main origin Ca2+, Mg2+, HCO3− Additionally, evaporite principal source SO42−. Human activities, particularly sewage discharge fertilization, significantly contribute nitrate contamination. Principal component revealed that industrial activities are controlling season, while hydrochemistry low-flow season mainly influenced by rocks, salt. Our findings provide scientific basis preventing deterioration ecological environmental protection regions.

Language: Английский

Citations

0
Irrigation Water Quality Prognostication: An Innovative Ensemble Architecture Leveraging Deep Learning and Machine Learning for Enhanced SAR and ESP Estimation in the East Coast of India DOI
Alok Kumar Pati, Alok Ranjan Tripathy, Debabrata Nandi

et al.

Journal of environmental chemical engineering, Journal Year: 2025, Volume and Issue: unknown, P. 116433 - 116433

Published: April 1, 2025

Language: Английский

Citations

0
"Integrating AHP and geospatial data analysis for mapping groundwater potential in tropical coastal villages of Thiruvananthapuram, Southern India" DOI
Stephen Pitchaimani,

Jerin Joe R. J,

Richard Abishek S

et al.

Journal of Coastal Conservation, Journal Year: 2024, Volume and Issue: 29(1)

Published: Dec. 16, 2024

Language: Английский

Citations

0
Recent advances in groundwater pollution research using machine learning from 2000 to 2023: a bibliometric analysis DOI
Xuan Li, Guohua Liang, Bin He

et al.

Environmental Research, Journal Year: 2024, Volume and Issue: 267, P. 120683 - 120683

Published: Dec. 20, 2024

Language: Английский

Citations

0