Integration of hydrogeochemical, isotopic, remote sensing and machine learning to assess seawater intrusion in an arid coastal aquifer, Sudr area, South Sinai, Egypt

Seawater intrusion (SWI) in coastal aquifers in arid areas is a global threat to the groundwater quality. This study aimed to assess SWI in the Sudr coastal aquifer in South Sinai, Egypt, by integration of hydrochemical, isotopic, remote sensing (RS) and machine learning (ML) approaches. The developed ML technique is based on the random vector functional link (RVFL) using the Tactical unit algorithm (TAU) to predict the value of the parameters of the RVFL, which leads to an enhancement in the prediction of seawater intrusion indicators. The hydrogeochemical data of the groundwater wells in the two periods (1996 and 2022) were used as inputs for the ML method. The groundwater chemistry in the study area was in the following order: Na > Ca > Mg > K and Cl > SO₄ > HCO₃. Ionic ratios highlighted groundwater–seawater mixing and reverse ion exchange processes. Based on the Cl⁻/Br⁻ ratio and O¹⁸& D data, seawater intrusion is the primary source of groundwater salinization. The results show that 83.33% of groundwater has a seawater mixing index (SMI) > 1, indicating that mixing with seawater has a significant impact on groundwater chemistry. Also, the Hydrochemical Facies Evolution Diagram (HFE-D) revealed that 83.33% of the area is affected by SWI. According to monitoring years (1996–2022), vegetation cover represented by the NDVI has increased by 1522.21 ha in the region, consequently, groundwater extraction increased. Groundwater salinity accelerated to 30.41% and 5.59% for highly saline and very saline during this period. The results of the ML technique were compatible with the previous analysis, and we compared the RVFL results based on TAU with other state-of-the-art methods using different performance metrics. The outcomes demonstrated a high applicability of RVFL to enhance the model prediction. Additionally, the applied ML model could effectively predict the seawater intrusion indicators in coastal aquifers such as Cl/HCO₃, Cl/Br, TDS and Cl. Therefore, these findings can help policy makers and stakeholders manage water resources sustainably in coastal aquifers.