Abstract
Worldwide coastal land-margins are prone to many flood hazards such as
astronomical tides, tropical cyclones, sea-level rise, and extreme
precipitation events. Compound flood events, in which two or more
flooding mechanisms occur simultaneously or in close succession
(Santiago-Collazo et al., 2019, https://doi.org/10.1016/j.envsoft.
2019.06.002), can exacerbate the inundation impacts due to the highly
non-linear interaction of coastal and hydrologic processes. Furthermore,
sea-level rise will increase the hazard at low-gradient coastal
land-margins when assessing future projections due to its non-linear
nuance on the compound flood (Santiago-Collazo et al., 2021,
https://doi.org/10.3389/fclim.2021.684035). Therefore, there is an
urgent need to develop new technologies capable of comprehensively
studying compound flood events and identifying hotspots prone to these
inundations. This research aims to develop a technique capable of
defining and classifying coastal land- margins based on physically-based
criteria due to surface flow hydrodynamics. A one-dimensional (1-D)
hydrodynamic model was used to quantify the hydrodynamic response of
thousands of different combinations of input parameters (e.g.,
astronomical tides, storm surge, precipitation, and landscape) that
define a coastal land-margin. This 1-D fully-coupled model, based on the
shallow water equations, was applied at a national spatial scale,
considering several coastal watersheds within the Gulf of Mexico and the
US East coast. One of the main goals of this tool is to identify coastal
land-margins vulnerable to compound flood hazards over broad spatial
scales (e.g., national or global scale). Findings suggest that
low-gradient (e.g., slopes less than 0.01 m km-1)
coastal land-margins are more susceptible to compound flood impacts than
ones with a steeper gradient under most flooding scenarios. Future
research will focus on applying this tool on a worldwide basis to test
its capabilities at low-resolution, scarce data regions. A worldwide
classification of coastal land-margins may help authorities,
policy-makers, and professionals converge on better coastal resilience
measures, such as comprehensive compound flood analysis to delineate
accurate compound flood hazard maps.