Coastal interfaces blend processes dominated by upland region hydrology and ocean hydrodynamics (tides, winds, waves, baroclinic fluctuations, among others). These areas tend to be vulnerable to flooding, a matter of concern considering that around 40% of the world’s population lives within 100 km of the ocean. Specifically, The US East and Gulf of Mexico Coasts are heavily affected by extratropical storms every year with catastrophic consequences. Models that integrate the dynamics of both oceans and river networks are needed in order to better improve flood forecast systems in coastal areas. Due to their spatial and temporal scale differences, traditional models solve river and ocean hydrodynamics independently. As a first step toward unifying coastal interface modeling, we designed an ADCIRC-based model that uses unstructured, highly variable-sized triangular meshes that can accurately represent both ocean basins and inland river networks. This meshing technique allows for incorporating features that control the dynamics of the nearshore area, such as barrier islands, jetties, and dredged channels. We analyze how mesh design impacts water level estimations in the deep ocean as well as inland rivers. Accuracy in the deep ocean is sensitive primarily to bathymetry in areas with high energy dissipation, whereas water level prediction within river networks depends on both bathymetry and resolution. While a minimum resolution in the order of a hundred meters is enough to accurately predict water level for most rivers with tidal influence, smaller tributaries require resolutions down to tens of meters. Future research will use these findings to build precipitation and rainfall-runoff into the model for a more comprehensive understanding of the coastal interface hydrodynamics.