Investigation of groundwater quality in the Southern Coast of the Black Sea: application of computational health risk assessment in Giresun, Türkiye

Environmental Science and Pollution Research, Год журнала: 2024, Номер 31(39), С. 52306 - 52325

Опубликована: Авг. 15, 2024

Язык: Английский

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Spatiotemporal Variation Assessment and Improved Prediction Of Cyanobacteria Blooms in Lakes Using Improved Machine Learning Model Based on Multivariate Data

Environmental Management, Год журнала: 2025, Номер unknown

Опубликована: Янв. 7, 2025

Язык: Английский

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Delineating the controlling mechanisms of geothermal waters quality and suitability zoning in the Lower Yellow River Basin, China

Environmental Technology & Innovation, Год журнала: 2025, Номер unknown, С. 104126 - 104126

Опубликована: Март 1, 2025

Язык: Английский

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Analysis of the Hydrogeochemical Characteristics and Origins of Groundwater in the Changbai Mountain Region via Inverse Hydrogeochemical Modeling and Unsupervised Machine Learning

Water, Год журнала: 2024, Номер 16(13), С. 1853 - 1853

Опубликована: Июнь 28, 2024

This study employed hydrochemical data, traditional hydrogeochemical methods, inverse modeling, and unsupervised machine learning techniques to explore the traits origins of groundwater in Changbai Mountain region. (1) Findings reveal that predominant types include HCO3−Ca·Mg, HCO3−Ca·Na·Mg, HCO3−Mg·Na, HCO3−Na·Mg. The average metasilicic acid content was found be at 49.13 mg/L. (2) Rock weathering mechanisms, particularly silicate mineral weathering, primarily shape chemistry, followed by carbonate dissolution. (3) Water-rock interactions involve volcanic dissolution cation exchange adsorption. Inverse alongside analysis widespread lithology, underscores complexity reactions, influenced not only water-rock but also evaporation precipitation. (4) Unsupervised learning, integrating SOM, PCA, K-means techniques, elucidates types. SOM component maps a close combination various components. Principal (PCA) identifies first principal (PC1), explaining 48.15% variance. second (PC2) third (PC3) components, explain 13.2% 10.8% variance, respectively. K clustering categorized samples into three main clusters: one less basaltic geological processes, another showing strong igneous rock characteristics, affected other processes or anthropogenic factors.

Язык: Английский

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Evaluation of surface and groundwater quality in Logbadjeck quarrying area: implications for trace metals pollution and health risk assessment

International Journal of Energy and Water Resources, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 26, 2024

Язык: Английский

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Integrating principal component analysis, fuzzy inference systems, and advanced neural networks for enhanced estuarine water quality assessment

Journal of Hydrology Regional Studies, Год журнала: 2025, Номер 57, С. 102182 - 102182

Опубликована: Янв. 15, 2025

Язык: Английский

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Physicochemical and Spatial Distributions of Trace Elements and Organochlorine Compounds in Lake Idku Water, Egypt

Water Air & Soil Pollution, Год журнала: 2025, Номер 236(2)

Опубликована: Янв. 23, 2025

Abstract This study aimed to characterize the water quality of 4 sites in Lake Idku, third largest wetland region Egypt regarding physicochemical indicators, spatial distributions certain trace elements and organochlorine compounds (OCs). Most tested indicators were above permissible limits River Nile except nitrate was lower than limits. The distribution concentrations Fe, Cu, Zn, Mn, Pb, Cd significantly differed (p > 0.05) among sampling sites, where mean these all ranged from 0.0226–0.0392, 0.010–0.098, 0.3570–1.0160, 0.084–0.942, 0.015–0.024, 0.011–0.023 mg/L, respectively. west site lake contained highest contents elements, followed by east, north, then south sites. Water collected had Fe while those Cd, samples east Mn. Mn which exceeded Egyptian regulations, levels that met regulations. Regarding residues OCs, ∑OCs can be grouped descending order as follows: north site, with values 5.632, 5.230, 4.731, 4.650 µg/L, All detected OCs maximum acceptable compared WHO standards 0.1 μg/L, for p,p'-DDT, p,p'-DDD, p,p'-DDE at levels. In conclusion, Idku may risk biota humans, monitoring, management, mitigation strategies are urgently required prevent further pollution restricting discharge industrial agricultural wastewater into Idku.

Язык: Английский

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Water Pollution Reduction for Sustainable Urban Development

Опубликована: Янв. 1, 2025

Язык: Английский

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Water quality evaluation, pollution sources apportionment, and environment management strategies in plain reservoirs: A case study of Tianhe Lake, China

Ecological Indicators, Год журнала: 2025, Номер 175, С. 113491 - 113491

Опубликована: Май 1, 2025

Язык: Английский

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Analysis of Water Quality Using Machine Learning Techniques

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Май 8, 2025

The research aims to analyse water quality using Python determine its potability. In this context, machine learning models: XGBoost and Random Forest, achieving accuracies of up 80% 78%, respectively. process begins by feeding the mod- els a dataset containing various metrics from multiple sources. These models are then trained predict potability, parameters like phys- ical, chemical biological. which is crucial for ensuring safe drinking water. model, most noted great efficiency efficacy in classifying issues, can handle large datasets that include lot varying variables there- fore suitable complicated datasets. On other hand, Forest model robust ensemble technique provide higher accuracy through decision tree aggregation, thus enhancing predictive performance. recognize patterns correlations within data, enabling them with certain level confidence. Both instrumental predicting quality, their deployment sig- nificantly aid monitoring managing resources effectively. language, extensive libraries tools, facilitates implementation optimization these models, scalable reliable analysis framework. success such project could lead improved management practices better health outcomes communities relying on underscores potential environmental protection efforts.

Язык: Английский

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