Assessment of Drinking Water Quality and Identifying Pollution Sources in a Chromite Mining Region

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 480, P. 136050 - 136050

Published: Oct. 4, 2024

Language: Английский

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Daily River flow Simulation Using Ensemble Disjoint Aggregating M5-Prime Model

Heliyon, Journal Year: 2024, Volume and Issue: 10(20), P. e37965 - e37965

Published: Sept. 30, 2024

Accurate prediction of daily river flow (Q t ) remains a challenging yet essential task in hydrological modeling, particularly crucial for flood mitigation and water resource management. This study introduces an advanced M5 Prime (M5P) predictive model designed to estimate Q as well one- two-day-ahead forecasts (i.e. t+1 t+2 ). The performance M5P ensembles incorporating Bootstrap Aggregation (BA), Disjoint Aggregating (DA), Additive Regression (AR), Vote (V), Iterative classifier optimizer (ICO), Random Subspace (RS), Rotation Forest (ROF) were comprehensively evaluated. proposed models applied case data Tuolumne County, US, using dataset comprising measured precipitation (P ), evaporation (E t), . A wide range input scenarios explored predicting , t+1, t+2. Results indicate that P significantly influence accuracy. Notably, relying solely on the most correlated variable (e.g., t-1) does not guarantee robust However, extending forecast horizon mitigates low-correlation variables Performance metrics DA-M5P achieves superior results, with Nash-Sutcliff Efficiency 0.916 root mean square error 23 m3/s, followed by ROF-M5P, BA-M5P, AR-M5P, RS-M5P, V-M5P, ICO-M5P, standalone model. ensemble modeling framework enhanced capability stand-alone algorithm 1.2 %-22.6 %, underscoring its efficacy potential advancing forecasting.

Language: Английский

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Groundwater for drinking and sustainable agriculture and public health hazards of nitrate: developmental and sustainability implications for an arid aquifer system

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

Published: Jan. 1, 2025

Language: Английский

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Advanced streamflow forecasting for Central European Rivers: The Cutting-Edge Kolmogorov-Arnold networks compared to Transformers

Journal of Hydrology, Journal Year: 2024, Volume and Issue: unknown, P. 132175 - 132175

Published: Oct. 1, 2024

Language: Английский

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Optimising miniaturised hydrocyclones for enhanced separation of microplastics

Chemical Engineering Journal, Journal Year: 2024, Volume and Issue: 496, P. 153718 - 153718

Published: July 6, 2024

Microplastics, particularly those in the 5–20 µm range, pose substantial risks aquatic environments, yet effective removal techniques are limited. This study assesses two critical geometric parameters of a 10 mm mini-hydrocyclone: inlet radius and insertion angle. Along with velocity, they optimised collectively to enhance MPs' removal. Computational Fluid Dynamics (CFD) simulations using Mixture model Reynolds stress were employed track particle–water–air interactions, revealing flow dynamics absence an air core. The Response Surface Methodology (RSM) Box-Behnken design experiments was adopted assess impact operational determine optimal design. Recovery efficiency, concentration split rate recorded during compared CFD results, showing good agreement between simulations. resulting novel achieved 88.53% MPs recovery efficiency 1.83, which represents obvious improvement over commercial design's 79.97% 1.68. Simulations reveal that shortens path for through forced turbulence region modifies velocity fields, enhancing gradient within mini-hydrocyclone's chamber. Moreover, exhibits more robust response variations, crucial advantage its application arrays. Experiments further confirm matrix composed mini-hydrocyclones achieves percentage points higher than mini-hydrocyclones. These findings mark significant step towards MP removal, addressing environmental issue.

Language: Английский

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Advancing railway sustainability: strategic integration of circular economy principles in ballasted track systems

Journal of Cleaner Production, Journal Year: 2025, Volume and Issue: unknown, P. 144713 - 144713

Published: Jan. 1, 2025

Language: Английский

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Enhancing prediction of dissolved oxygen over Santa Margarita River: Long short-term memory incorporated with multi-objective observer-teacher-learner optimization

Journal of Water Process Engineering, Journal Year: 2025, Volume and Issue: 70, P. 106969 - 106969

Published: Jan. 11, 2025

Language: Английский

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Investigation of microplastic pollution index in the urban surface water: A case study in west Godavari district, Andhra Pradesh, India

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 374, P. 124098 - 124098

Published: Jan. 11, 2025

Language: Английский

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Persistent Effects of Naturally Aged Polyethylene Terephthalate Microplastics on Physalaemus cuvieri Tadpoles: The Toxic Legacy Beyond Exposure

Water Air & Soil Pollution, Journal Year: 2025, Volume and Issue: 236(2)

Published: Jan. 22, 2025

Language: Английский

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Modeling future sediment retention service in the Bagh-e-Shadi Forest protected area using InVEST and the ACCESS-ESM1-5 climate model

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

Published: Jan. 27, 2025

Assessing the impact of climate change on water-related ecosystem services (ES) in Protected Areas (PAs) is essential for developing soil and water conservation strategies that promote sustainability restore ES. However, application ES research Area (PA) management remains ambiguous has notable shortcomings. This study primarily aimed to assess SDR-InVEST (Sediment Delivery Ratio-Integrated Valuation Ecosystem Services Tradeoffs) model estimating ES, including loss, sediment export, retention, under various scenarios from 1997 2100 data-scarce region Bagh-e-Shadi Forest PA. PA, a forest zone Yazd Province, Iran, highest incidence fire occurrences, leading accelerated erosion degradation. Our pioneering employing InVEST model, particularly SDR investigate effects load, retention. Additionally, this focused sensitivity analysis individually parameter uncertainties highlighted calibration process. By incorporating latest IPCC emission scenarios, it addresses critical gap area. Sensitivity analyses identified Borselli IC0, cover factor, k (Kb) as most influential parameters export. IC0 kb are factors shape sigmoid function SDR–IC relationship. From 2021, our findings indicated area experienced an average annual loss 77.1 t ha−1 year−1. export was 0.08 year−1, while retention averaged 2.2 The results increasing due change, driven by projected increases precipitation. showed yield increase SSP585 scenario during period 2041–2060, with rise 148.02% compared baseline conditions. Sediment expected 25,436.25 year−1 63,128.63 same period. minimum be 40.6% SSP126 2021–2040. quantified changes provisioning will enhance future land use planning, especially managing Forest.

Language: Английский

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