Towards efficient coastal flood modeling: A comparative assessment of bathtub, extended hydrodynamic, and total water level approaches

Coastal flooding within Great Lakes communities poses severe threats to ecosystem and economic sustainability. Accurate and efficient flood predictions could provide critical advanced warnings and improve local resilience. Three types of modeling approaches, including the Bathtub Method (BTM), Extended Hydrodynamic model (EXT), and Total Water Level (TWL) approach, were evaluated for a flood event in the Great Lakes. These studied modeling approaches have successfully replicated water levels at four nearshore gauge stations in the lake, indicating a reliable starting point for coastal flood simulations. Comparisons were made between simulations of maximum flood extent using different methods in three typical high flooding risk areas, including an open-bay area, along coasts of drowned-river-mouth (estuaries) lakes, and a section of shoreline with heavy infrastructural facilities. In addition, aerial photos from news reports and synthetic aperture radar (SAR) data were analyzed in this study to provide observed information for the studied flooding events. According to the results, BTM and EXT were consistent in simulating flood extents for various types of coastal areas, while the TWL was limited in predicting flood propagation into inland areas, particularly in the coasts of river-mouth lakes. Despite slightly overestimating the flood extent in disconnected low-lying areas, the BTM can still serve as a cost-effective tool to provide preliminary flood simulations for the Great Lakes region. We further discuss operational perspectives of using BTM, EXT, and TWL for coastal flood modeling. The results of this study could be used to improve the guidance of coastal management by determining efficient and accurate approaches for coastal flood predictions.