Phosphorus release from the sediment of a drinking water reservoir under the influence of seasonal hypoxia

The Science of The Total Environment, Год журнала: 2024, Номер 917, С. 170490 - 170490

Опубликована: Фев. 1, 2024

Язык: Английский

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Geostatistical and multivariate analysis of phosphate evolution and its relationship with heavy metals in shallow groundwater in a Semi-Arid Basin

Earth Science Informatics, Год журнала: 2025, Номер 18(3)

Опубликована: Фев. 18, 2025

Язык: Английский

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Exploring internal phosphorus loads and management interventions through Bayesian reservoir modeling

Journal of Environmental Management, Год журнала: 2025, Номер 384, С. 125538 - 125538

Опубликована: Май 1, 2025

Phosphorus is a limiting nutrient for eutrophication in many lakes and reservoirs across the world. While most management strategies aim at reducing external (watershed) phosphorus sources, internal loading (IPL) often receives less attention, as it challenging to measure or estimate through modeling. Here, we present novel approach characterize dynamics, leveraging multi-decadal monitoring data mass-balance model developed within Bayesian inference framework. The performs well (R2 = 57 % RMSE 0.032 mg/L total phosphorus) when applied Jordan Lake, segmented eutrophic reservoir North Carolina, USA. Results highlight dominant increasing role of summers (0.53 g/m2/month), contributing nearly twice loading. We also explore long-term lake warming scenarios that intensify fluxes both into out sediment layer, but have little effect on water-column concentrations. Additionally, investigate dynamics under different interventions. Our simulations demonstrate potential IPL mitigation (e.g., capping, dredging) accelerate sustain water quality improvements, particularly paired with reductions. modeling transferable similar waterbodies, especially where there need based largely data. It provides computationally efficient framework making long-term, probabilistic forecasts accounting future climate, anthropogenic impacts, gradual accumulation (or depletion) layer.

Язык: Английский

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Impact of Dense Networks of Reservoirs on Streamflows at Dryland Catchments

Sustainability, Год журнала: 2022, Номер 14(21), С. 14117 - 14117

Опубликована: Окт. 29, 2022

Small reservoirs play an important role in providing water to rural communities. Increased construction of small mitigate the effects droughts leads a High-density Reservoirs Network (HdRN) reservoirs, which can potentially modify streamflows both dry and wet periods. However, there is lack understanding interannual behavior flow retention impact future increases number mainly for HdRN dryland catchments. This research aims determine possible increase on hydrological networks, evaluating annual flows generated at outlet watershed scenarios with different densities (number per area). The study area was Conceição river catchment (3347 km2) semiarid Brazil. model developed SWAT. obtained appropriate results daily streamflows, values 0.63, 0.81, 0.53% NSE, KGE, PBIAS, respectively. current density region estimated 0.068 square kilometer (res/km2). Eight expansion were defined between 0.1 res/km2 3.0 res/km2. showed that influence runoff reduction mostly occurs probability exceedance 1% 10% month very months high peaks flow. due stronger during years (up 30%) than 8%), it tended consecutive rain (from about 7% first year 20% last worst scenario), may intensify period extended droughts. provides insights variability retention, help resources agencies better prepare hydrologic extremes (droughts floods).

Язык: Английский

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Understanding the Water Quality Dynamics in a Large Tropical Reservoir Under Hydrological Drought Conditions

Water Air & Soil Pollution, Год журнала: 2024, Номер 235(1)

Опубликована: Янв. 1, 2024

Язык: Английский

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Chlorophyll-a Estimation in 149 Tropical Semi-Arid Reservoirs Using Remote Sensing Data and Six Machine Learning Methods

Remote Sensing, Год журнала: 2024, Номер 16(11), С. 1870 - 1870

Опубликована: Май 24, 2024

It is crucial to monitor algal blooms in freshwater reservoirs through an examination of chlorophyll-a (Chla) concentrations, as they indicate the trophic condition these waterbodies. Traditional monitoring methods, however, are expensive and time-consuming. Addressing this hindrance, we conducted a comprehensive investigation using several machine learning models for Chla modeling. To end, used situ collected water sample data remote sensing from Sentinel-2 satellite, including spectral bands indices, large-scale coverage. This approach allowed us conduct analysis characterization concentrations across 149 Ceará, semi-arid region Brazil. The implemented included k-nearest neighbors, random forest, extreme gradient boosting, least absolute shrinkage, group method handling (GMDH); particular, GMDH has not been previously explored context. forward stepwise was determine best subset input parameters. Using 70/30 split training testing datasets, best-performing model model, achieving R2 0.91, MAPE 102.34%, RMSE 20.4 μg/L, which were values consistent with ones found literature. Nevertheless, predicted concentration most sensitive red, green, near-infrared bands.

Язык: Английский

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Chlorophyll-a prediction in tropical reservoirs as a function of hydroclimatic variability and water quality

Environmental Science and Pollution Research, Год журнала: 2023, Номер 30(39), С. 91028 - 91045

Опубликована: Июль 19, 2023

Язык: Английский

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Uncovering the influence of hydrological and climate variables in chlorophyll-A concentration in tropical reservoirs with machine learning

Environmental Science and Pollution Research, Год журнала: 2022, Номер 29(49), С. 74967 - 74982

Опубликована: Июнь 1, 2022

Язык: Английский

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Chlorophyll-a Estimation in 149 Tropical Semi-Arid Reservoirs Using Remote Sensing and Machine Learning

Опубликована: Фев. 20, 2024

Eutrophication, a global concern, impacts water quality, ecosystems, and human health. It’s crucial to monitor algal blooms in freshwater reservoirs, as they indicate the trophic condition of waterbody through Chlorophyll-a (Chla) concentration. Traditional monitoring methods, however, are expen-sive time-consuming. Addressing this hindrance, we developed models using remotely sensed data from Sentinel-2 satellite for large-scale coverage, including its bands spectral indexes, estimate Chla concentration on 149 reservoirs Ceará, Brazil. Several machine learning were trained tested, k-nearest neighbours, random forests, extreme gradient boosting, least absolute shrinkage, group method handling (GMDH), sup-port vector models. A stepwise approach determined best subset input parameters. Using 70/30 split training testing datasets, best-performing model was GMDH, achieving an R2 0.91, MAPE 102.34%, RMSE 20.38 g/L, which values consistent with ones found literature. Nevertheless, predicted most sensitive red, green, near infra-red bands.

Язык: Английский

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Water environmental capacity analysis and eutrophication assessment of water-supplied reservoirs

Desalination and Water Treatment, Год журнала: 2024, Номер 317, С. 100200 - 100200

Опубликована: Янв. 1, 2024

The protection of water quality in reservoirs, particularly those designated for supply, has garnered increasing attention environmental management purposes. In this paper, the Shuangxikou Reservoir Yuyao was chosen as a case study. pollutant load at various points within reservoir analyzed and its eutrophication level evaluated through combination site surveys regular monitoring. Additionally, model trial algorithm utilized to investigate environment capacity concerning key indicators such COD, NH3-N, TN, TP Reservoir. results indicated that nutrient fell mid-trophic range, with being superior central region compared other areas. However, when target Class II surface mandated by functional zoning, current TN content exceeds acceptable levels. Consequently, targeted measures are imperative enhance reservoir.

Язык: Английский

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