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

Our plain-English summary of Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems, by M.H. Eid, A. Shebl, M. Eissa, et al (Heliyon, 2024).

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The study

  • Authors: M.H. Eid, A. Shebl, M. Eissa, E.A. Mohamed, A.S. Fahil, H.S. Ramadan, M.R. Abukhadra, A.M. El-Sherbeeny, A. Kovacs, P. Szűcs
  • Journal: Heliyon
  • Published: 2024;10(12):e32992
  • Cited by: 7 articles, as counted by NIH iCite
  • Read it: PubMed · Publisher · Free full text

Abstract

The current study integrates remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems. Fifty-two water samples were collected from all water resources in Siwa Oasis and analyzed for physical (pH, T°C, EC, and TDS) chemical (SO4 2-, HCO3 -, NO3 -, Cl-, CO3 2-, SiO2, Mg2+, Na+, Ca2+, and K+), and trace metals (AL, Fe, Sr, Ba, B, and Mn). A digital elevation model supported by machine learning was used to predict the change in the land cover (surface lake area, soil salinity, and water logging) and its effect on water quality deterioration. The groundwater circulation and interaction between the deep aquifer (NSSA) and shallow aquifer (TCA) were detected from the pressure-depth profile of 27 production wells penetrating NSSA. The chemical facies evolution in the aquifer systems were (Ca-Mg-HCO3) in the first stage (freshwater of NSSA) and changed to (Na-Cl) type in the last stage (brackish water of TCA and springs). Support vector machine successfully predicted the rapid increase of the hypersaline lake area from 22.6 km2 to 60.6 km2 within 30 years, which deteriorated a large part of the cultivated land, reflecting the environmental risk of over-extraction of water for irrigation of agricultural land by flooding technique and lack of suitable drainage network. The waterlogging in the study was due to a reduction in the infiltration rate (low permeability) of the soil and quaternary aquifer. The cause of this issue could be a complete saturation of agricultural water with chrysotile, calcite, talc, dolomite, gibbsite, chlorite, Ca-montmorillonite, illite, hematite, kaolinite and K-mica (saturation index >1), giving the chance of these minerals to precipitate in the pore spaces of the soil and decrease the infiltration rate. The NSSA is appropriate for irrigation, whereas TCA is inappropriate due to potential salinity and magnesium risks. The best way to manage water resources in Siwa Oasis could be to use underground drip irrigation and combine water with TCA and NSSA.

© 2024 The Authors.

In plain English

This study was not about asbestos exposure or disease. It examined groundwater in Siwa Oasis, a closed desert depression in northwestern Egypt. In February 2022 the authors analyzed 52 water samples from a deep aquifer (NSSA), a shallow aquifer (TCA), springs, drains and salt lakes. They also used pressure data from 27 deep wells and machine-learning classification of 1990 to 2020 satellite images. From 1990 to 2020 salt lakes grew from 22.6 to 60.6 square kilometers. Shallow-aquifer salinity (EC) averaged 6880 microsiemens per centimeter in 1998. For 2022 the text gives 14425, but a table gives 11384.4. Chrysotile was one of 14 minerals whose saturation in the water was computer-modeled, which shows whether a mineral could settle out; its saturation index ranged from minus 9.1 to 8.9. No asbestos fibers were measured. Citing another publication, the authors wrote that drinking water with these supersaturated minerals can lead to health problems including lung and ovarian cancer; this study collected no health data. The authors concluded that the deep aquifer is appropriate for agriculture and the shallow aquifer is not appropriate for irrigation.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

  • Design: Field hydrogeochemical study (one round of water sampling) combined with satellite-image change detection over 1990 to 2020 using a support vector machine, well pressure analysis, and geochemical modeling (PHREEQC)
  • Who was studied: Water resources of Siwa Oasis, northwestern desert of Egypt. The authors collected 52 surface and groundwater samples in February 2022 from the deep Nubian sandstone aquifer (NSSA), the shallow Tertiary carbonate aquifer (TCA), springs, drains and lakes. They also used pressure data from 27 production wells in the NSSA. No people were studied.
  • Exposure: No asbestos exposure was studied. Chrysotile was one of 14 minerals whose saturation state in the water was calculated by geochemical modeling. The other 13 were Ca-montmorillonite, calcite, kaolinite, K-mica, gypsum, dolomite, talc, potassium feldspar, chlorite, gibbsite, hematite, anhydrite and illite.
  • Main results:
    • Total area of the hypersaline lakes was 22.6, 42.6, 53.1 and 60.6 square kilometers in 1990, 2000, 2010 and 2020 respectively.
    • Cultivated area in Siwa Oasis was estimated at 23.9, 34.5, 82.5 and 89 square kilometers in 1990, 2000, 2010 and 2020 respectively.
    • In the deep aquifer (NSSA) wells, 18 samples fell above the hydrostatic line, indicating upward groundwater movement. Three fell below it, indicating downward movement. The rest fell on the line.
    • Shallow aquifer (TCA) salinity: in 1998, EC ranged from 2400 to 11000 with an average of 6880 microsiemens per centimeter. For 2022, the text gives a range of 7450 to 24250 with a mean of 14425 microsiemens per centimeter. Table 3 gives the 2022 TCA average EC as 11384.4.
    • Mean total dissolved solids were 286 mg/L in the deep aquifer (NSSA) and 8843 mg/L in the shallow aquifer (TCA). The authors described the water as fresh in NSSA, brackish in TCA and springs, saline in drains and hypersaline in lakes.
    • Water type changed from Ca-Mg-HCO3 in the deep aquifer (NSSA) to Na-Cl in the shallow aquifer (TCA) and surface water.
    • A significant number of samples were calculated to be over-saturated with talc, illite, chrysotile and other minerals. For chrysotile, the saturation index ranged from minus 9.1 to 8.9. The number of samples over-saturated with chrysotile was not given.
    • Citing another publication, the authors wrote that exposure to the supersaturated minerals in drinking water can lead to health problems including lung cancer and ovarian cancer. This study did not investigate health outcomes.
    • Irrigation indices across all 52 samples: 86.5 % had a magnesium hazard value above 50, and 67.3 % fell in the injurious-to-unsatisfactory potential salinity category.
  • The authors' conclusion: The authors concluded that the deep aquifer (NSSA) is appropriate for agriculture. They concluded that the shallow aquifer (TCA) is not appropriate for irrigation because of the magnesium hazard and potential salinity indices.
  • Limitations the authors state:
    • The authors stated that the minerals they linked to hydrothermal systems may indicate geothermal water at depth, but that further research is needed.

Topics

Medical terms in this study, explained in our Lexicon: Chrysotile, Talc, Dolomite, Chlorite, Hematite, Mica.

Browse more research in Heliyon, or return to medical research.

How to cite it

Cite the study

M.H. Eid, A. Shebl, M. Eissa, E.A. Mohamed, A.S. Fahil, H.S. Ramadan, et al. Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems. Heliyon 2024;10(12):e32992. doi:10.1016/j.heliyon.2024.e32992. PMID: 39022055.

Cite our summary

“Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems.” AsbestosClaims.Law Library. https://asbestosclaims.law/library/research/comprehensive-approach-integrating-remote-sensing-machine-learning.

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