Low-gradient coastal watersheds are susceptible to flooding caused by various flows such as rainfall-runoff, astronomical tides, storm surges, and riverine flows. Compound flooding occurs when at least one coastal flood driver occurs simultaneously or in close succession with a pluvial and/or fluvial flood driver, such as during a tropical cyclone event. This study presents a one-dimensional (1-D), reduced-order physics compound inundation model tested over an idealized coastal watershed transect under various forcing conditions (e.g., storm surge, astronomical tides, and rainfall) that varied in magnitude, time, and space. This study aims to evaluate each flooding mechanism and the associated hydrodynamic responses to identify generalized coastal transition zones and enhance the production of flood maps for varying regions in a coastal watershed. Compound inundation levels are affected by the magnitude and timing of each flooding mechanism. The desire is a more holistic compound inundation model that can be a critical tool for decision-makers, stakeholders, and authorities who provide evacuation planning to save human lives and enhance resilience.

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.Full online poster version at agu2021fallmeeting-agu.ipostersessions.com/Default.aspx?s=FA-1F-20-67-21-4E-E7-69-9F-89-1E-33-BB-3D-2D-40

This presentation showcases a hydrodynamic assessment of natural and nature-based features (NNBFs) for the Pascagoula River, the Escatawpa River and Grand Bay, located along the Mississippi coast of the northern Gulf of Mexico. Two separate NNBF projects are being considered to: (1) restore the historical footprint (ca. 1848) of Grand Batture Island for coastal protection purposes; and (2) reconnect the hydraulics between the Escatawpa River and Grand Bay for ecosystem services purposes. The intended coastal protection benefits of the first project include buffering agency to wave attack and attenuation of storm surge with the restored island. The intended ecosystem services benefits of the second project include replenishment of sediments to the salt marsh via increased hydroperiod (duration of tidal inundation) and availability for sediment accumulation. Astronomic tide and storm surge simulations are performed with the advanced circulation (ADCIRC) plus simulating waves nearshore (+SWAN) model to evaluate the hydrodynamic impact of the NNBF projects (Image). The simulated hydrodynamics are assessed firstly in terms of storm surge and waves for the open coast with and without the restoration of Grand Batture Island (Passeri et al., 2015), and secondly for tidal datums and inundation extent for the salt marsh with and without the hydraulic reconnection of the Escatawpa River with Grand Bay (Alizad et al., 2018). A key outcome from the analysis is the interconnectedness of the hydrodynamics within the system, where the implementation of the NNBFs results in local and non-local impacts. The numerical modeling approach with high-resolution feature definition at a system-wide scale affords such methodical evaluation of NNBFs for ecosystem restoration.

Recent advances in the quality and availability of lidar permit high spatial resolution in digital elevation models (DEMs). However, large-scale lidar acquisitions may be flown during high tides, storm events, and irregular tidal regimes leading to temporal change differences, but ultimately the uneven penetration through dense vegetation impacts the reality of ground surface positions. For the low-gradient coastal land margin of the northern Gulf of Mexico, even a small elevation bias (on the order of 0.1 m) can adversely affect surface hydrodynamic model accuracy. Therefore, ground-truthing with a vertical elevation adjustment is essential for robust biogeophysical modeling. This study assessed measurement errors of lidar-derived DEM datasets (1 m DEMs), developed in 2021. The DEM was evaluated for distinct coastal wetlands, especially coastal marshes of Louisiana, Mississippi, and Alabama. Error analysis was conducted using Real-Time Kinematic (RTK) GPS to assess how well the lidar-derived elevations represent the actual marsh surface (ground surface). The performance of the temporally and spatially distinct lidar-derived elevation datasets was evaluated over 7,000 elevation points measured between 2011-2021. We also examined the relationship between measurement errors and vegetation characteristics (marsh type, height, and percent cover). This presentation will demonstrate our ongoing efforts to assess the high-resolution lidar-derived elevations in coastal wetlands and discuss the measurement errors.