干旱区生态环境知识资源中心(Arid): Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems

Arid

DOI	10.1016/j.heliyon.2024.e32992
	Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems
	Eid, Mohamed Hamdy; Shebl, Ali; Eissa, Mustafa; Mohamed, Essam A.; Fahil, Amr S.; Ramadan, Hatem Saad; Abukhadra, Mostafa R.; El-Sherbeeny, Ahmed M.; Kovacs, Attila; Szucs, Peter
通讯作者	Eid, MH
来源期刊	HELIYON
EISSN	2405-8440
出版年	2024
卷号	10 期号:12
英文摘要	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 degrees C, EC, and TDS) chemical (SO42-, HCO3-, NO3-, Cl-, CO32-, 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 km(2) to 60.6 km(2) 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.
英文关键词	Siwa oasis Soil salinization water quality deterioration Hydrodynamic condition Hydrochemistry Geochemical modeling
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:001260286600001
WOS关键词	IRRIGATION PURPOSES ; SIWA OASIS ; WATER ; CLASSIFICATION ; RESOURCES ; EVOLUTION ; INDEX ; BASIN
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/404038
推荐引用方式 GB/T 7714	Eid, Mohamed Hamdy,Shebl, Ali,Eissa, Mustafa,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[J],2024,10(12).
APA	Eid, Mohamed Hamdy.,Shebl, Ali.,Eissa, Mustafa.,Mohamed, Essam A..,Fahil, Amr S..,...&Szucs, Peter.(2024).Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems.HELIYON,10(12).
MLA	Eid, Mohamed Hamdy,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 10.12(2024).