Predictive model for progressive salinization in a coastal aquifer using artificial intelligence and hydrogeochemical techniques: a case study of the Nile Delta aquifer, Egypt

Faculty Science Year: 2021
Type of Publication: ZU Hosted Pages:
Authors:
Ahmed Mohamed Mahmoud Nosseir
Journal: Environmental Science and Pollution Research Springer Volume:
Keywords : Predictive model , progressive salinization , , coastal aquifer    
Abstract:
To monitor groundwater salinization due to seawater intrusion (SWI) in the aquifer of the eastern Nile Delta, Egypt, we developed a predictive regression model based on an innovative approach using SWI indicators and artificial intelligence (AI) methodologies. Hydrogeological and hydrogeochemical data of the groundwater wells in three periods (1996, 2007, and 2018) were used as input data for the AI methods. All the studied indicators were enrolled in feature extraction process where the most significant inputs were determined, including the studied year, the distance from the shoreline, the aquifer type, and the hydraulic head. These inputs were used to build four basic
    
     
 
       

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