Modelling clogging dynamics in groundwater systems using multiscale homogenized physics informed neural network (MHPINN) DOI Creative Commons
Alvin Wei Ze Chew,

Renfei He,

Limao Zhang

et al.

Engineering Science and Technology an International Journal, Journal Year: 2024, Volume and Issue: 49, P. 101605 - 101605

Published: Jan. 1, 2024

Groundwater systems, or also commonly known as large-scale closed and saturated porous media systems in general, are important sources of potable water, especially arid countries. However, maintenance groundwater is operationally expensive time-consuming, hence requiring field engineers to optimally predict the system's breakthrough phase. To address this engineering challenge, study developed an alternative physics informed machine learning model, termed multiscale homogenized neural network (MHPINN), model effluent discharge concentrations from when removing different contaminants. The proposed MHPINN mainly exploits homogenization theory, coupled with perturbation analysis, for hydrodynamic modelling extract input features pertaining pore-scale clogging behavior media. Together available experimental data, extracted then set layer training concentration emulated systems. At same time, performed modified mean square error (MSE) cost function, based upon mathematical representations derived a series rigorous constructs formulations, better facilitate model's learning, under sparse data constraint. verify methodology, MPINN trained (and validated) obtained five historical studies, which remove ammonium ions fine-scaled colloids, each study. Overall, outperformed other conventional models (random forest, support vector machines, etc.) by obtaining higher predictive accuracy around 4% on average validation step across studies. Therefore, analysis underscored effectiveness combine both physics-based complex constraints, demonstrating potential methodology extend physical

Language: Английский

Modeling of Distributed Control System for Network of Mineral Water Wells DOI Open Access
Ivan M. Pershin,

E. G. Papush,

Tatyana V. Kukharova

et al.

Water, Journal Year: 2023, Volume and Issue: 15(12), P. 2289 - 2289

Published: June 19, 2023

The article is devoted to solving the problem of designing a distributed control system for network production wells on example mineral water deposits in Caucasus Mineral Waters region, Russia. purpose was determine set parameters ensure technologically effective and safe operating modes deposits. A mathematical model deposit developed taking into account given configuration rate wells. detailed algorithm presented under consideration based frequency concept analysis synthesis systems. experimental tests validation were performed at facility “Narzan”, Kislovodsk, results modeling field experiments confirmed adequacy effectiveness proposed algorithm. authors came conclusion that adapted can be used create regional automated cluster management monitoring, operational forecasting nature real hydrogeological processes ensuring their stability.

Language: Английский

Citations

55
Water Quality Evaluation and Prediction Using Irrigation Indices, Artificial Neural Networks, and Partial Least Square Regression Models for the Nile River, Egypt DOI Open Access
Mohamed Gad, Ali Saleh, Hend Hussein

et al.

Water, Journal Year: 2023, Volume and Issue: 15(12), P. 2244 - 2244

Published: June 15, 2023

Water quality is identically important as quantity in terms of meeting basic human needs. Therefore, evaluating the surface-water and associated hydrochemical characteristics essential for managing water resources arid semi-arid environments. present research was conducted to evaluate predict agricultural purposes across Nile River, Egypt. For that, several irrigation indices (IWQIs) were used, along with an artificial neural network (ANN), partial least square regression (PLSR) models, geographic information system (GIS) tools. The physicochemical parameters, such T °C, pH, EC, TDS, K+, Na+, Mg2+, Ca2+, Cl−, SO42−, HCO3−, CO32−, NO3−, measured at 51 locations. As a result, ions contents following: Ca2+ > Na+ Mg2+ K+ HCO3− Cl− SO42− NO3− reflecting Ca-HCO3 mixed Ca-Mg-Cl-SO4 types. index (IWQI), sodium adsorption ratio (SAR), percentage (Na%), soluble (SSP), permeability (PI), magnesium hazard (MH) had mean values 92.30, 1.01, 35.85, 31.75, 72.30, 43.95, respectively. instance, IWQI readings revealed that approximately 98% samples inside no restriction category, while 2% fell within low area irrigation. ANN-IWQI-6 model’s six indices, R2 0.999 calibration (Cal.) 0.945 validation (Val.) datasets, are crucial predicting IWQI. rest models behaved admirably SAR, Na%, SSP, PI, MR Cal. Val. 0.999. findings ANN PLSR effective methods assist decision plans. To summarize, integrating features, WQIs, ANN, PLSR, GIS tools suitability offers complete image sustainable development.

Language: Английский

Citations

47
New approach into human health risk assessment associated with heavy metals in surface water and groundwater using Monte Carlo Method DOI Creative Commons
Mohamed Hamdy Eid, Mustafa Eissa, Essam A. Mohamed

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Jan. 10, 2024

Abstract This study assessed the environmental and health risks associated with heavy metals in water resources of Egypt's northwestern desert. The current approaches included Spearman correlation matrix, principal component analysis, cluster analysis to identify pollution sources quality-controlling factors. Various indices (HPI, MI, HQ, HI, CR) were applied evaluate human risks. Additionally, Monte Carlo method was employed for probabilistic carcinogenic non-carcinogenic risk assessment via oral dermal exposure routes adults children. Notably, all exhibited high HPI MI values exceeding permissible limits (HPI > 100 6), respectively. Furthermore, HI indicated significant both children, while contact posed a 19.4% samples 77.6% children (HI 1). Most CR 1 × 10 –4 Cd, Cr, Pb, suggesting vulnerability effects age groups. simulations reinforced these findings, indicating impact on adults. Consequently, comprehensive treatment measures are urgently needed mitigate Siwa Oasis.

Language: Английский

Citations

47
Assessment of groundwater quality in arid regions utilizing principal component analysis, GIS, and machine learning techniques DOI
Mustafa El-Rawy, Mohamed Wahba, Heba Fathi

et al.

Marine Pollution Bulletin, Journal Year: 2024, Volume and Issue: 205, P. 116645 - 116645

Published: June 25, 2024

Language: Английский

Citations

22
Artificial Neural Network Modeling for the Prediction, Estimation, and Treatment of Diverse Wastewaters: A Comprehensive Review and Future Perspective DOI
Muhammad Ibrahim, Adnan Haider, Jun Wei Lim

et al.

Chemosphere, Journal Year: 2024, Volume and Issue: 362, P. 142860 - 142860

Published: July 15, 2024

Language: Английский

Citations

18
Groundwater for drinking and sustainable agriculture and public health hazards of nitrate: developmental and sustainability implications for an arid aquifer system DOI Creative Commons
Boualem Bouselsal,

Adel Satouh,

Johnbosco C. Egbueri

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104160 - 104160

Published: Jan. 1, 2025

Language: Английский

Citations

6
Health risk assessment of groundwater use for drinking in West Nile Delta, Egypt DOI Creative Commons
Zenhom E. Salem,

Samia S. Hasan,

Ahmed Sefelnasr

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 3, 2025

Abstract Human health is at risk from drinking water contamination, which causes a number of problems in many parts the world. The geochemistry groundwater, its quality, origins groundwater pollution, and associated risks have all been subject substantial research recent decades. In this study, west Rosetta Nile branch Delta Aquifer examined for potential. Numerous quality indices were applied, such as index (WQI), synthetic pollution (SPI) models, assessment (HRA) method. limits measured parameters are used to test validity on basis WHO recommendations. TDS southern regions within desirable allowable with percent 25.3% 29.33%, respectively. Nearly study area has value HCO 3 , Al Ba. Ca Mg values center south portion investigated area, whereas north unsuitable. Na, Cl SO 4 fall desired level but become unsuitable towards north. Mn NO inappropriate except northwestern part. Fe suitable range southwestern regions. Pb, Zn, Cu, Cd undetected collected samples. Regarding WQI classified into classes good, poor, very poor unfit According SPI model, 20%, 18.7%, 8% 34.6% samples suitable, slightly, moderately, highly polluted unfit, respectively Based HRA, Children most category endangered 14.7% overall obtained, followed by females males 12% 8%, This offers insights conservation management coastal aquifers’ supplies. These findings significant implications developing strategies executing preventative actions reduce resource vulnerability related hazards West Delta, Egypt.

Language: Английский

Citations

2
Integration of Geochemical Modeling, Multivariate Analysis, and Irrigation Indices for Assessing Groundwater Quality in the Al-Jawf Basin, Yemen DOI Open Access

Mohammed Hezam Al-Mashreki,

Mohamed Hamdy Eid, Omar Saeed

et al.

Water, Journal Year: 2023, Volume and Issue: 15(8), P. 1496 - 1496

Published: April 11, 2023

Water quality monitoring is crucial in managing water resources and ensuring their safety for human use environmental health. In the Al-Jawf Basin, we conducted a study on Quaternary aquifer, where various techniques were utilized to evaluate, simulate, predict groundwater (GWQ) irrigation. These include indices (IWQIs), geochemical modeling, multivariate statistical analysis, geographic information systems (GIS), adaptive neuro-fuzzy inference (ANFIS). Physicochemical analysis was collected samples determine composition. The results showed that order of abundance ions Ca2+ > Mg2+ Na+ K+ SO42− Cl− HCO3− NO3−. assessment irrigation based such as Irrigation index (IWQI), sodium adsorption ratio(SAR), percent (Na%), soluble percentage (SSP), potential salinity (PS), residual carbonate RSC, which revealed moderate-to-severe restrictions some samples. Adaptive Neuro-Fuzzy Inference System (ANFIS) model then used IWQIs with high accuracy during both training testing phases. Overall, these findings provide valuable decision-makers management can aid sustainable development resources.

Language: Английский

Citations

40
Groundwater vulnerability assessment in central Iran: Integration of GIS-based DRASTIC model and a machine learning approach DOI Creative Commons
Zeynab Karimzadeh Motlagh, Reza Derakhshani, Mohammad Hossein Sayadi

et al.

Groundwater for Sustainable Development, Journal Year: 2023, Volume and Issue: 23, P. 101037 - 101037

Published: Nov. 1, 2023

The study try to evaluate the susceptibility of groundwater. DRASTIC model was implemented through GIS. Various input variables, such as water table depth, net recharge, aquifer and soil media, topography, vadose zone impact, hydraulic conductivity, were evaluated within generate a groundwater vulnerability map. Subsequently, machine-learning algorithms (SVM, RF, GLM) employed using SDM package in R software optimize method. To assess performance pollution risk models, training validation datasets ROC curve. results revealed that approximately 40% area fell high range, while around 30% exhibited moderate risk. Evaluation machine learning models indicated their effectiveness development. RF demonstrated highest predictive power, achieving an AUC 0.98. Additionally, GLM SVM achieved values 76%. These can serve efficient techniques for evaluating managing resources. findings underscored relatively poor quality area, with excessive exploitation by agricultural sector infiltration urban sewage industrial waste identified primary causes pollution. implications these are crucial devising strategies implementing preventive measures mitigate resource associated health risks central Iran.

Language: Английский

Citations

28
Optimisation and interpretation of machine and deep learning models for improved water quality management in Lake Loktak DOI

Swapan Talukdar,

Shahfahad,

Somnath Bera

et al.

Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 351, P. 119866 - 119866

Published: Dec. 25, 2023

Language: Английский

Citations

27