Aquifer characterization using geophysical borehole-logging and hydrochemical techniques—a case study from Lahore, Pakistan DOI
Muhammad Farooq Ahmed, Sadia Ismail, Muhammad Umer Khan

et al.

Environmental Earth Sciences, Journal Year: 2024, Volume and Issue: 84(1)

Published: Dec. 28, 2024

Language: Английский

Prediction of Nitrate Concentration and the Impact of Land Use Types on Groundwater in the Nansi Lake Basin DOI
Javed Iqbal, Chunli Su, Hasnain Abbas

et al.

Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: 487, P. 137185 - 137185

Published: Jan. 14, 2025

Language: Английский

Citations

4
Risk assessment of potentially toxic elements and mapping of groundwater pollution indices using soft computer models in an agricultural area, Northeast Algeria DOI
Azzeddine Reghais, Abdelmalek Drouiche, Faouzi Zahi

et al.

Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: unknown, P. 137991 - 137991

Published: March 1, 2025

Language: Английский

Citations

1
Unraveling the impact of high arsenic, fluoride and microbial population in community Tubewell water around coal mines in a semiarid region: Insight from health hazards, and geographic information systems DOI
Abdur Rashid, Muhammad Ayub, Xubo Gao

et al.

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 480, P. 136064 - 136064

Published: Oct. 5, 2024

Language: Английский

Citations

3
Machine Learning-based Model for Groundwater Quality Prediction: A Comprehensive Review and Future Time–Cost Effective Modelling Vision DOI

Farhan ‘Ammar Fardush Sham,

Ahmed El‐Shafie,

Wan Zurina Binti Jaafar

et al.

Archives of Computational Methods in Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 19, 2025

Language: Английский

Citations

0
Identifying the spatial pattern and driving factors of nitrate in groundwater using a novel framework of interpretable stacking ensemble learning DOI Creative Commons
Xuan Li, Guohua Liang, Lei Wang

et al.

Environmental Geochemistry and Health, Journal Year: 2024, Volume and Issue: 46(11)

Published: Oct. 29, 2024

Groundwater nitrate contamination poses a potential threat to human health and environmental safety globally. This study proposes an interpretable stacking ensemble learning (SEL) framework for enhancing interpreting groundwater spatial predictions by integrating the two-level heterogeneous SEL model SHapley Additive exPlanations (SHAP). In model, five commonly used machine models were utilized as base (gradient boosting decision tree, extreme gradient boosting, random forest, extremely randomized trees, k-nearest neighbor), whose outputs taken input data meta-model. When applied agricultural intensive area, Eden Valley in UK, outperformed individual predictive performance generalization ability. It reveals mean level of 2.22 mg/L-N, with 2.46% sandstone aquifers exceeding drinking standard 11.3 mg/L-N. Alarmingly, 8.74% areas high remain outside designated vulnerable zones. Moreover, SHAP identified that transmissivity, baseflow index, hydraulic conductivity, percentage arable land, C:N ratio soil top key driving factors nitrate. With threatening globally, this presents high-accuracy, interpretable, flexible modeling enhances our understanding mechanisms behind contamination. implies has great promise providing valuable evidence management, water resource protection, sustainable development, particularly data-scarce area.

Language: Английский

Citations

2
Groundwater salinity modeling and mapping using machine learning approaches: a case study in Sidi Okba region, Algeria DOI
Samir Boudibi, Haroun Fadlaoui,

Fatima Hiouani

et al.

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(36), P. 48955 - 48971

Published: July 23, 2024

Language: Английский

Citations

0
Aquifer characterization using geophysical borehole-logging and hydrochemical techniques—a case study from Lahore, Pakistan DOI
Muhammad Farooq Ahmed, Sadia Ismail, Muhammad Umer Khan

et al.

Environmental Earth Sciences, Journal Year: 2024, Volume and Issue: 84(1)

Published: Dec. 28, 2024

Language: Английский

Citations

0