Evaluating water quality, mineralization mechanisms, and potential health risks of nitrate contamination in the Continental Intercalaire aquifer of Reggane, Algeria

Environmental Earth Sciences, Год журнала: 2024, Номер 83(18)

Опубликована: Сен. 1, 2024

Язык: Английский

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Exploring groundwater recharge potential zones mapping in the northern upper Boussellam region: a novel approach integrating TDS levels

Applied Water Science, Год журнала: 2025, Номер 15(5)

Опубликована: Апрель 29, 2025

Язык: Английский

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Modeling groundwater recharge mechanisms in semi-arid regions: integration of hydrochemical and isotopic data

Euro-Mediterranean Journal for Environmental Integration, Год журнала: 2023, Номер 8(4), С. 893 - 905

Опубликована: Авг. 18, 2023

Язык: Английский

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The investigation of energy dissipation in ogee profile spillway model

Arabian Journal of Geosciences, Год журнала: 2024, Номер 17(2)

Опубликована: Янв. 26, 2024

Язык: Английский

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Predicted impacts of global warming and climate change on groundwater resources in a semi-arid region, southeastern Tunisia

Euro-Mediterranean Journal for Environmental Integration, Год журнала: 2023, Номер 9(1), С. 325 - 337

Опубликована: Дек. 14, 2023

Язык: Английский

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Rooftop rainwater harvesting potential for kitchen gardening in the Rawal watershed, Pakistan

Arabian Journal of Geosciences, Год журнала: 2024, Номер 17(3)

Опубликована: Фев. 7, 2024

Язык: Английский

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Harnessing the sustainable potential of groundwater in Saudi Arabia via remote sensing

Discover Water, Год журнала: 2024, Номер 4(1)

Опубликована: Окт. 1, 2024

Язык: Английский

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Assessing drinking water quality in Eloued, south-East Algeria, using the groundwater pollution index (GPI) and the synthetic pollution index (SPI) model

Environmental Monitoring and Assessment, Год журнала: 2024, Номер 196(11)

Опубликована: Окт. 5, 2024

Язык: Английский

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Optimization of land subsidence prediction features based on machine learning and SHAP value with Sentinel-1 InSAR Data

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Янв. 23, 2024

Abstract Land subsidence has always been a concern of geoscience, and exploring the factors affecting land to predict future is essential research. However, current research rarely scientific unified feature screening process for features. This study applies neural networks SHAP values prediction. We used instead traditional random forest (RF) quantify features areas where likely occur in cities Chongqing Chengdu, encompassing majority possible scenarios future. The results show that prediction using improves model accuracy by 16% compared method. After input optimization, performance nearly 22%. found optimization method based on proposed this more helpful prediction, derived from data analysis with complex terrain are also consistent previous studies. can contribute variable selection model, improve accuracy, provide solid theoretical support preventing urban subsidence.

Язык: Английский

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Linear correlation and regression analysis of tap water quality parameters in rural area of Malwa Punjab

Arabian Journal of Geosciences, Год журнала: 2024, Номер 17(3)

Опубликована: Фев. 19, 2024

Язык: Английский

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