A deep learning interpretable model for river dissolved oxygen multi-step and interval prediction based on multi-source data fusion

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 629, P. 130637 - 130637

Published: Jan. 14, 2024

Language: Английский

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Developing a novel tool for assessing the groundwater incorporating water quality index and machine learning approach

Groundwater for Sustainable Development, Journal Year: 2023, Volume and Issue: 23, P. 101049 - 101049

Published: Nov. 1, 2023

Groundwater plays a pivotal role as global source of drinking water. To meet sustainable development goals, it is crucial to consistently monitor and manage groundwater quality. Despite its significance, there are currently no specific tools available for assessing trace/heavy metal contamination in groundwater. Addressing this gap, our research introduces an innovative approach: the Quality Index (GWQI) model, developed tested Savar sub-district Bangladesh. The GWQI model integrates ten water quality indicators, including six heavy metals, collected from 38 sampling sites study area. enhance precision assessment, employed established machine learning (ML) techniques, evaluating model's performance based on factors such uncertainty, sensitivity, reliability. A major advancement incorporation metals into framework index model. best authors knowledge, marks first initiative develop encompassing heavy/trace elements. Findings assessment revealed that area ranged 'good' 'fair,' indicating most indicators met standard limits set by Bangladesh government World Health Organization. In predicting scores, artificial neural networks (ANN) outperformed other ML models. Performance metrics, root mean square error (RMSE), (MSE), absolute (MAE) training (RMSE = 0.361; MSE 0.131; MAE 0.262), testing 0.001; 0.00; 0.001), prediction evaluation statistics (PBIAS 0.000), demonstrated superior effectiveness ANN. Moreover, exhibited high sensitivity (R2 1.0) low uncertainty (less than 2%) rating These results affirm reliability novel monitoring management, especially regarding metals.

Language: Английский

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Heavy metal contamination assessment and potential human health risk of water quality of lakes situated in the protected area of Tisa, Romania

Heliyon, Journal Year: 2024, Volume and Issue: 10(7), P. e28860 - e28860

Published: March 29, 2024

Protected areas are significant due to the high value of natural resources they shelter. This study's primary objective is assess quality status water (13 lakes and Tisa River) localized in protected area River on territory Romania. A number 13 surface (Tisa situated through Natura 2000 ecological network studied. The chemistry potential pollution were analyzed by measuring analyzing a set twenty elements sixteen physico-chemical parameters. impact anthropogenic activities was settled applied analysis obtained results. human health risk noticed. Results indicated that waters rich Ni Fe probably interaction with groundwater Ni. Waters characterized contamination, which if directly or food chain consumed could negatively influence health. Piper Gibbs plots studied divided into three categories based water-rock interactions: mixed Ca2+-Na+-HCO3-, CaCO3-, Na+-HCO3-. Likewise, indices (Heavy metal Pollution Index, HPI Heavy Evaluation HEI) correlated As, amounts. findings this research imply influenced geogenic origin emergence activities. significance related understanding mechanisms quality, improving conserving resources, correspondingly any risks be identified.

Language: Английский

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Research on the Features and Driving Factors of Shallow Groundwater Quality in Arid Areas, Northwest China

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

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Harmonizing water quality: Integrating indices and chemo-metrics for sustainable management in the Ramganga river watershed

Analytical Chemistry Letters, Journal Year: 2024, Volume and Issue: 14(1), P. 29 - 47

Published: Jan. 2, 2024

AbstractRiver systems are vital for both civilization and biodiversity. The rising threats to it is due the rapid industrialization urbanization, resulting in heightened wastewater discharge. This study delves into Ramganga River watershed India, conducting a comprehensive assessment of its water quality drinking irrigation purposes. A total 84 samples were collected from three streams, further categorized two clusters, involving evaluation 30 characteristics. To measure suitability, CCME-WQI was computed, revealing distinct categorizations during Dry Season (DS) Wet (WS) year 2019-20. Cluster 1, comprising Sampling Sites-1 (S-1), Sites-3 (S-3), Sites-5 (S-5), fell within fair category DS, shifting marginal WS. 2, encompassing S-2, S-4, S-6, S-7, remained poor transitioning IWQI employed assess irrigation. Notably, S-1 S-3 consistently under high suitability category, while S-2 exhibited DS medium S-4 seasons. In contrast, S-5, S-7 demonstrated Cations anions unveiled an alkaline dominance Calcium (Ca2+) Magnesium (Mg2+) exceeding alkalis Sodium (Na+) Potassium (K+), depicted weak acid Bicarbonates (HCO3-) Carbonates (CO3-) surpassing strong Sulphate (SO42-) Chloride (Cl2-), with exception at DS. USSL diagram indicated medium-high salinity low sodium levels, signifying potential suitability. extends heavy metal concentrations, indicating adherence standard limits, except elevated iron levels. These findings furnish invaluable insights policymakers stakeholders resource management, providing nuanced understanding challenges opportunities sustaining watershed.Display full sizeKeywords: Surface waterRamgangaPhysiyo-chemicalPollution, Piper

Language: Английский

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Determination of high-risk factors and related spatially influencing variables of heavy metals in groundwater

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 358, P. 120853 - 120853

Published: April 11, 2024

Language: Английский

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Modelling Euphrates river water quality index based on field measured data in Al-Diwaniyah City, Iraq

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

Published: Jan. 2, 2025

Pollution monitoring in surface water using field observational procedure is a challenging matter as it time consuming, and needs lot of efforts. This study addresses the challenge efficiently predicting pollution GIS-based artificial neural network (ANN) to detect heavy metal (HM) effect wastewater required discharge on Euphrates River Al-Diwaniyah City, Iraq. The established 40 sampling stations incorporates Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-OES) assess HM levels. An ANN model suggested estimate Heavy Metal Index (HPI) considering physiological chemical factors. It formulates six scenarios enhance HPI prediction accuracy, utilizing MATLAB for modeling GIS statistical tools with inverse distance weighted (IDW) methods comprehensive assessment. developed approach predicted HP concentration basin an actual case study. validation predictive maps between theoretical practical part performed by 16 conducting laboratory analyses, resulting acceptable coefficients determination (R2), observations standard deviation ratio (RSR), Nash–Sutcliffe efficiency 0.999, 1, 0.99, respectively indicates that reliable forecast results closely match observed data from stations. identifies nickel, iron, cadmium concentrations exceeded Iraqi World Health Organization (WHO) standards, leading index peak 150.38 branch. In this study, used identify areas high levels, validate accuracy prediction, generate map visualize

Language: Английский

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Effects of urban stormwater pollution on watershed diffuse loads under extreme precipitation conditions

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 132802 - 132802

Published: Feb. 1, 2025

Language: Английский

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Deep learning for river water quality monitoring: a CNN-BiLSTM approach along the Kaveri River

Sustainable Water Resources Management, Journal Year: 2024, Volume and Issue: 10(3)

Published: May 17, 2024

Language: Английский

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Investigation of self-purification and water quality index during dry and rainy seasons in the Khurumela Stream (Botswana)

Journal of Ecohydraulics, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 18

Published: June 20, 2024

This study investigated the self-purification and predicted water quality index of a stream in Botswana, fed by natural spring. The is tributary Lotsane River which turn drains into Limpopo River. was conducted through sampling measuring variables (14) along at different points during dry rainy seasons year. There were statistical significances observed between for temperature, electrical conductivity, salinity, total dissolved solids, oxygen (DO), biochemical demand (BOD) with P values less than 0.05. No turbidity, suspended potential hydrogen (pH). indices mostly excellent season unacceptable season. BOD to increase, whereas DO concentrations decreasing distance. deoxygenation rates 1.007 0.886 day−1 respectively. improving distance constant Negative correlation positive correlations leverages advanced predictive algorithms offer real-time insights future projections. methodology will be valuable monitoring main watercourse downstream, River, season, allow better knowledge define adequate strategies safeguard resources ecosystems.

Language: Английский

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