Environmental Earth Sciences, Journal Year: 2024, Volume and Issue: 83(23)
Published: Nov. 22, 2024
Language: Английский
Environmental Science and Pollution Research, Journal Year: 2025, Volume and Issue: unknown
Published: March 1, 2025
Abstract Monitoring changes in groundwater quality over time helps identify time-dependent factors influencing water safety and supports the development of effective management strategies. This study investigates spatiotemporal evolution chemistry Debrecen area, Hungary, from 2019 to 2024, using indexing, machine learning, multivariate statistical techniques. These techniques include self-organizing maps (SOM), hierarchical cluster analysis (HCA), principal component (PCA), indexing (GWQI). The hydrochemical revealed that Ca-Mg-HCO₃ is dominant type, with a temporal shift toward Na-HCO₃, reflecting increased salinity driven by ongoing rock-water interactions. SOM showed transition heterogeneous more uniform time, suggesting greater stability aquifer system. Elevated zones shifted spatially due recharge flow patterns, while hardness intensified expanded, indicating continued carbonate dissolution. HCA highlighted shifts composition, six clusters identified five gradual homogenization quality. PCA further confirmed this trend, linking it underlying processes, such as water–rock interactions, limited contributions anthropogenic influences. GWQI indicated general improvement most regions meeting drinking standards. However, specific areas exhibited signs localized contamination, requiring targeted management. findings underscore importance continuous monitoring detect emerging trends guide resource highlights need for sustainable practices safeguard resources ensure long-term security area.
Language: Английский
Citations
2
Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)
Published: March 27, 2024
Abstract This research presents an unsupervised learning approach for interpreting well-log data to characterize the hydrostratigraphical units within Quaternary aquifer system in Debrecen area, Eastern Hungary. The study applied factor analysis (FA) extract logs from spontaneous potential (SP), natural gamma ray (NGR), and resistivity (RS) correlate it petrophysical hydrogeological parameters of shale volume hydraulic conductivity. indicated a significant exponential relationship between scaled first derived through analysis. As result, universal FA-based equation estimation is that shows close agreement with deterministic estimation. Furthermore, correlated decimal logarithm conductivity estimated Csókás method. method modified Kozeny-Carman continuously estimates FA method-based estimations showed high similarity correlation coefficient 0.84. use provided new strategy geophysical well-logs interpretation bridges gap traditional data-driven machine techniques. beneficial characterizing heterogeneous systems successful groundwater resource development.
Language: Английский
Citations
8
Modeling Earth Systems and Environment, Journal Year: 2024, Volume and Issue: 10(3), P. 3693 - 3709
Published: March 22, 2024
Abstract In this research, a multi-step modeling approach is followed using unsupervised and deep learning algorithms to interpret the geophysical well-logging data for improved characterization of Quaternary aquifer system in Debrecen area, Hungary. The Most Frequent Value-Assisted Cluster Analysis (MFV-CA) used map lithological variations within system. Additionally, Csókás method discern both vertical horizontal fluctuations hydraulic conductivity. MFV-CA introduced cope with limitation conventional Euclidean distance-based k-means clustering known its low resistance outlying values, resulting deformed cluster formation. However, computational time demands are evident, making them costly time-consuming. As result, Deep Learning (DL) methods suggested provide fast groundwater aquifers. These include Multi-Layer Perceptron Neural Networks (MLPNN), Convolutional (CNN), Recurrent (RNN), Long Short-Term Memory (LSTM), which implemented classification regression. categorized inputs into three distinct lithologies trained initially by results MFV-CA. At same time, regression model offered continuous estimations conductivity model. demonstrated significant compatibility between outcomes derived from approaches DL algorithms. Accordingly, lithofacies across main hydrostratigraphical units mapped. This integration enhanced understanding system, offering promising development management.
Language: Английский
Citations
7
Sustainable Water Resources Management, Journal Year: 2024, Volume and Issue: 10(2)
Published: March 2, 2024
Abstract The recent study followed a multi-methodological approach integrating gravity, magnetotelluric (MT), and electrical resistivity tomography (ERT) to investigate the geometry hydrological characteristics of main hydrostratigraphical units in Western Debrecen area, Eastern Hungary. integration these methods aims delineate potential zones for groundwater development guide effective extraction strategies. In gravity investigation, Bouguer anomaly map undergoes spectral analysis separation shallow deep features, offering preliminary indication basement rock depth. Subsequently, data inversion is employed variations topography, revealing basin structure, with sediment thicknesses extending up 2 km. On other hand, MT are modeled using 1D Occam algorithm validate results analysis. This inversion, constrained lithological logs further utilized area. Accordingly, four identified, including Nagyalföld Aquifer, Algyő Endrődi Aquitards, Badenian Pre-Neogene Aquitard. Consequently, Dar Zarrouk parameters based transmissivity hydraulic conductivity aquifer measured. showed that ranged between 7.9 11.9 m/day, while an average 13.1 m/day. ERT spatial distribution depth water table. table observed regions characterized by elevated thickness sedimentary rocks, attributed their high specific capacity. Integrating hydrogeophysical provided comprehensive understanding subsurface hydrology enabled better-informed decision-making development.
Language: Английский
Citations
4
Modeling Earth Systems and Environment, Journal Year: 2025, Volume and Issue: 11(2)
Published: Jan. 20, 2025
Language: Английский
Citations
0
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: Feb. 10, 2025
Groundwater aquifers are complex systems that require accurate lithological and hydrogeological characterization for effective development management. Traditional methods, such as core analysis pumping tests provide precise results but expensive, time-consuming, impractical large-scale investigations. Geophysical well logging data offers an efficient continuous alternative, though manual interpretation of logs can be challenging may result in ambiguous outcomes. This research introduces automated approach using machine learning signal processing techniques to enhance the aquifer characterization, focusing on Quaternary system Debrecen area, Eastern Hungary. The proposed methodology is initiated with imputation missing deep resistivity from spontaneous potential, natural gamma ray, medium utilizing a gated recurrent unit (GRU) neural network. preprocessing step significantly improved quality subsequent analyses. Self-organizing maps (SOMs) then applied preprocessed map distribution units across groundwater system. Considering mathematical geological aspects, SOMs delineated three primary units: shale, shaly sand, sand gravel which aligned closely drilling data. Continuous wavelet transform further refined mapping hydrostratigraphical boundaries. integrated methods effectively mapped subsurface generating 3D model simplifies into four major zones. lithology deterministically estimated shale volume permeability, revealing higher permeability lower sandy gravelly layers. provides robust foundation flow contaminant transport modeling extended other regions management development.
Language: Английский
Citations
0
Deleted Journal, Journal Year: 2024, Volume and Issue: 6(3)
Published: March 11, 2024
Abstract Groundwater plays a crucial role in Hungary sustaining ecosystems and meeting the growing demand for freshwater to fulfill domestic agricultural needs. This study employs analytical hierarchy process (AHP) methodology delineate groundwater potential zones Debrecen area, Hungary. To ensure robustness reliability of zoning, geophysical data are utilized validation purposes. In AHP modeling seven conditioning factors integrated, including geology, topography, slope, land use/land cover, precipitation, drainage density, lineament density. The integration normalized weights each factor identified three (GWPZs) assigned as moderate, high, very high potential. result model is further validated with gravity wireline logging. Gravity subjected spectral analysis forward map lineaments detect thickness sedimentary sequences. indicated that these sequences varies between 1.25 2.7 km, deep local basin delimited by normal faults situated eastern part area. Additionally, well-logging using Csókás method provided continuous estimation petrophysical hydrogeological parameters along main hydrostratigraphical units. Accordingly, uniform distribution hydraulic conductivity observed area due presence coarse-grained incised valley deposits. results showed close agreement models. interdisciplinary approach advanced mapping valuable insights into characteristics aquifers
Language: Английский
Citations
3
Water, Journal Year: 2024, Volume and Issue: 16(15), P. 2204 - 2204
Published: Aug. 3, 2024
The evaluation of saturated hydraulic conductivity (Ks) constitutes an invaluable tool for the management and protection groundwater resources. This study attempted to estimate Ks in shallow aquifer Kabul City, Afghanistan, response occurring crisis caused by overexploitation a lack appropriate monitoring system on pumping wells, based datasets from well drilling logs, various analytical methods test analyses, laboratory-based methodologies. selection estimation was influenced data availability established equations, including Theis, developed Cooper–Jacob, Kruger, Zamarin, Zunker, Sauerbrei, Chapuis, pre-determined values dedicated log segments exhibited highest correlation coefficients, ranging between 60% 75%, with real conditions phreatic respect drawdown rate map. results successfully obtained local-specific quantitative value ranges gravel, sand, silt, clay, conglomerate. fall within high range classification, 30.0 139.8 m per day (m/d) average across calculation methods. proved that combination results, predetermined derived empirical laboratory approaches, geological description, classified soil materials analyses reliable through cost-effective accessible compared conducting expensive tests arid semi-arid areas.
Language: Английский
Citations
2
Groundwater for Sustainable Development, Journal Year: 2024, Volume and Issue: 27, P. 101348 - 101348
Published: Sept. 21, 2024
Language: Английский
Citations
2
Environmental Earth Sciences, Journal Year: 2024, Volume and Issue: 83(23)
Published: Nov. 22, 2024
Language: Английский
Citations
0