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In this study, a review of the overlay/index methods served for delineation of vulnerable zones in coastal aquifers affected by SWI is provided. Then, a more realistic presentation of the vulnerability mapping of coastal aquifers to SWI through modified GALDIT index method by incorporating the influential factors on SWI is established. The modifications on GALDIT method including incorporating the seaward hydraulic gradient (i) instead of the height of groundwater level above sea level (L) (so-called GAiDIT), and considering hydraulic gradient (i) as an additional parameter to the GALDIT (so-called GALDIT-i). Three GALDIT, GAiDIT, and GALDIT-i methods were evaluated with data from three coastal confined and phreatic/confined aquifers located in the south of the Caspian Sea, northern Iran. While no highly vulnerable zone was recognized by GALDIT method across three studied aquifers, averagely 43.4% and 50.5% of aquifers area were defined as highly vulnerable zones by GAiDIT and GALDIT-i, respectively. Furthermore, the final vulnerability maps obtained by GALDIT-i and then GAiDIT indicates higher correlation by three groundwater quality indices specific to SWI including f(sea) (r = 0.72 and 0.63) and GQI (r = 0.69 and 0.62) and also the distribution of TDS in groundwater (r = 0.71 and 0.61) compared with GALDIT (r = 0.33, 0.42, and 0.36, respectively). The values of vulnerability index obtained by GALDIT-i and GAiDIT are more strongly correlated with the length of SWI into the aquifer (L-x) based on Strack's analytical approach than GALDIT (r = 0.52, 0.36, and 0.32, respectively). The results of sensitivity analysis indicated that the hydraulic gradient, height of groundwater level above sea level, aquifer type, and existing status of seawater intrusion has the greatest impact on the groundwater vulnerability across the studied aquifers by GALDIT-i and GAiDIT methods. Results also indicated that serving the influential parameters in GALDIT methods regarding the hydrological and anthropogenic characteristics across the aquifer provide a more realistic characterization of the SWI. This modification leads to an accurate aquifer vulnerability mapping to SWI in aquifers characterized by transient anthropogenic drivers (e.g. pumping) which can be served as a promising tool for decision-making to properly assess and manage risk.