Combined inversion and statistical workflow for advanced temporal analysis of the Nile River’s long term water level records

Szűcs, Péter; Dobróka, Mihály; Turai, Endre; Szarka, László; Ilyés, Csaba; Eid, Mohamed Hamdy; Szabó, Norbert Péter

doi:10.1016/j.jhydrol.2024.130693

Cited by 4 publications

(1 citation statement)

References 29 publications

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“…This issue will likely worsen in dry, densely populated areas and will have a crucial impact on agriculture in the future. To ensure sustainable agriculture, a holistic approach to managing soil, water, and crops will be necessary [ [1] , [2] , [3] , [4] , [5] , [6] , [7] , [8] ]. This approach will require tailored preventive measures and management strategies specific to each site and situation.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems

Eid,

Shebl,

Eissa

et al. 2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems

Eid,

Shebl,

Eissa

et al. 2024

Heliyon

Self Cite

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Comprehensive approach integrating water quality index and toxic element analysis for environmental and health risk assessment enhanced by simulation techniques

Eid,

Awad,

Mohamed

et al. 2024

Environ Geochem Health

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Due to water shortages and the potential impact of Ethiopia’s new dam on the Nile River, Egypt is seeking new water resources. This study assesses the drinking water quality and associated risks from potentially toxic elements (PTEs) in the Quaternary aquifer (QA) in Beni-Suef, Egypt. Using a comprehensive approach, including PHREEQC geochemical modeling, ionic ratios, multivariate statistical analyses, and the integrated weight water quality index (WQI), the study evaluated the sources of ion contamination and the mixing of Nile water with QA. Various indices, such as the Heavy Metal Pollution Index (HPI), ecological Risk Index (RI), Hazard Quotient (HQ), and Hazard Index (HI), were used to assess ecological and health risks. Monte Carlo simulations provided probabilistic assessments of non-carcinogenic risks for adults and children. GIS tools were used to map risk indices, identifying the most deteriorated locations for sustainable management. The hydrochemical analysis revealed water facies including Na–Cl, Ca–Mg–HCO3, and mixed types, influenced by carbonate dissolution, ion exchange, and silicate weathering. Contamination sources, particularly in the north and south, were linked to agricultural activities, irrigation return flow, municipal waste, and evaporation. The WQI indicated that 10.14% of samples were extremely poor, 21.7% were poor, 26% were medium, and 42% were good to excellent. PTE contamination varied, with HPI values indicating good water quality in the central area in 53.6% of the collected samples (HPI < 30), but contamination in the north and south is high (HPI > 51). Ecological Risk Index values were below the threshold in 100% of samples (RI < 30), confirming water safety regarding PTEs. In comparison, for hazard index (HI) through oral/ingestion, adults exhibited HI values ranging from 0.012 to 2.16, while children showed higher values, ranging from 0.045 to 8.25. However, the hazard index for oral/ingestion exceeded safe limits in the north and south (HI oral > 1), posing non-carcinogenic risks. Monte Carlo simulations revealed significant risks from oral exposure to manganese (HQ oral > 1), particularly in El-Wasta and El-Fashn, necessitating further treatment and management.

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Comprehensive evaluation and prediction of groundwater quality and risk indices using quantitative approaches, multivariate analysis, and machine learning models: An exploratory study

Gad,

Gaagai,

Agrama

et al. 2024

Heliyon

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Combined inversion and statistical workflow for advanced temporal analysis of the Nile River’s long term water level records

Cited by 4 publications

References 29 publications

Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems

Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems

Comprehensive approach integrating water quality index and toxic element analysis for environmental and health risk assessment enhanced by simulation techniques

Comprehensive evaluation and prediction of groundwater quality and risk indices using quantitative approaches, multivariate analysis, and machine learning models: An exploratory study

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