Hurricanes are devastating natural hazards that often cause damage to the built environment as a result of their loadings, which include storm surge, waves, and wind, often in combination. Modeling these hazards individually and their effects on buildings is a complex process because each loading component within the hazard behaves differently, affecting either the building envelope, the structural system, or the interior contents. Realistic modeling of hurricane effects requires a multihazard approach that considers the combined effects of wind, surge, and waves. Previous studies focused primarily on modeling these hazards individually, with less focus on the multihazard impact on the whole building system made up of the combination of the structure and its interior contents. The analysis resolution used in previous studies did not fully enable hurricane risk assessment through a detailed investigation of the vulnerability at the component-level or subassembly-level (a group of components such as interior contents, structural components, or nonstructural components). To address these research gaps, a robust multihazard hurricane risk analysis model that uses high-resolution hazard, exposure, and vulnerability models was developed. This model uses a novel approach to combine the storm surge and wave fragility functions with a suite of existing wind fragilities to account for structural damage and then combines them with another suite of flood-based fragilities to account for interior content damage. The proposed vulnerability model was applied to the state of North Carolina as an example of a regional-scale assessment to demonstrate the ability of the method to predict damage at the building level across this large spatial domain. This model enables better understanding of the damages caused by hurricanes in coastal regions, thereby setting initial post-impact conditions for community resilience assessment and investigation of recovery policy alternatives.
OM Nofal, JW van de Lindt, TQ Do, G Yan, S Hamideh, DT Cox, JC Dietrich (2021). “Methodology for Regional Multihazard Hurricane Damage and Risk Assessment.” Journal of Structural Engineering, 147(11), 04021185, DOI: 10.1061/(ASCE)ST.1943-541X.0003144.
Dunes and beaches are vulnerable to erosion during storm events. Numerical models can predict beach response to storms with fidelity, but their computational costs, the domain-specific knowledge necessary to use them, and the wide range of potential future storm and beach conditions can hinder their use in forecasting storm erosion for short- and long-term horizons. We develop an emulator, which is an efficient predictive model that behaves like a numerical model, to predict the morphologic response of the subaerial beach to storms. Specific emphasis is placed on providing antecedent beach states as an input to the emulator and predicting the post-storm profile shape. Training data include beach profiles at multiple stages in a nourishment life cycle to assess if such a framework can be applied in locations that nourish as a coastal defense policy. Development and application of the emulator is focused on Nags Head, North Carolina, which nourishes its beaches to mitigate hazards of storm waves, flooding, and erosion. A high-fidelity, process-based morphodynamic model is used to train the emulator with 1250 scenarios of sea-storms and beach profiles. The post-storm beach state is emulated with a parameterized power-law function fit to the eroded portion of the subaerial profile. When the emulator was tested for a sequence of real storms from 2019, the eroded beach profiles were predicted with a skill score of 0.66. This emulator is promising for future efforts to predict storm-induced beach erosion in hazard warnings or adaptation studies.
Predictions of storm surge and flooding require models with higher resolution of coastal regions, to describe fine-scale bathymetric and topographic variations, natural and artificial channels, flow features, and barriers. However, models for real-time forecasting often use a lower resolution to improve efficiency. There is a need to understand how resolution of inland regions can translate to predictive accuracy, but previous studies have not considered differences between models that both represent conveyance into floodplains and are intended to be used in real time. In this study, the effects of model resolution and coverage are explored using comparisons between forecast-ready and production-grade models that both represent floodplains along the US southeast coast, but with typical resolutions in coastal regions of 400 and 50 m, respectively. For two storms that impacted the US southeast coast, it is shown that, although the overall error statistics are similar between simulations on the two meshes, the production-grade model allowed a greater conveyance into inland regions, which improved the tide and surge signals in small channels and increased the inundation volumes between 40% and 60%. Its extended coverage also removed water level errors of 20–40 cm associated with boundary effects in smaller regional models.
Barrier islands are a primary coastal defense and often experience erosion during storms. When they fail due to storm-induced breaching, there can be significant changes to the small- and large-scale hydrodynamics and morphodynamics of the region. In this study, we explore the formation of a breach on Hatteras Island, North Carolina, during Isabel (2003) and the subsequent flooding into Pamlico Sound. Two-way coupling of high-fidelity, high-resolution numerical models for coastal erosion and flooding enables a better understanding of the formation of the breach, as well as scenarios of the breach’s effects on the circulation in the region. The breach connecting the ocean to the sound formed during the day of landfall. It is shown that, during the storm, overwash and inundation from the ocean led to deterioration of the beach and dunes, and then after the storm, the creation of channels through the island was sensitive to elevated water levels in the lagoon. Then flooding scenarios are considered in which the ground surface of the hydrodynamic model was (a) static, updated with the (b) pre- and post-storm observations, and updated dynamically with (c) erosion model predictions and (d) erosion model predictions with elevated lagoon-side water levels. The model results show that the breach has region-scale effects on flooding that extend 10 to 13 km into the lagoon, increasing the local water levels by as much as 1.5 m. These results have implications for similar island-lagoon systems threatened by storms.
Coastal flooding models are used to predict the timing and magnitude of inundation during storms, both for real-time forecasting and long-term design. However, there is a need for faster flooding predictions that also represent flow pathways and barriers at the scales of critical infrastructure. This need can be addressed via subgrid corrections, which use information at smaller scales to ‘correct’ the flow variables (water levels, current velocities) averaged over the mesh scale. Recent studies have shown a decrease in run time by 1 to 2 orders of magnitude, with the ability to decrease further if the model time step is also increased. In this study, subgrid corrections are added to a widely used, finite-element-based, shallow water model to better understand how they can improve the accuracy and efficiency of inundation predictions. The performance of the model, with and without subgrid corrections, is evaluated on scenarios of tidal flooding in a synthetic domain and a small bay in Massachusetts, as well as a scenario with a real atmospheric forcing and storm surge in southwest Louisiana. In these tests we observed that the subgrid corrections can increase model speed by 10 to 50 times, while still representing flow through channels below the mesh scale to inland locations.
Storm surge and coastal flooding predictions can require high resolution of critical flow pathways and barriers, typically with simulations using grids/meshes with millions of cells/elements to represent a coastal region. However, the cost of this resolution can slow forecasts during a storm. To add resolution when and where it is needed, previous studies have used adaptive mesh methods, which update resolution at single or multiple cells but which require hierarchies of and thresholds for refinement, and nesting methods, which update resolution at subdomains but which require additional simulations. This research proposes a middle way, in which predictions from a coarse mesh are mapped, mid-simulation, onto a fine mesh with increased resolution near the storm’s projected landfall location. The coarse and fine meshes are pre-developed, thus removing any refinement decisions during the simulation, the solution mapping uses a widely used framework, thus enabling an efficient interpolation, and the same simulation is continued, thus eliminating a separate full-domain simulation. For four historical storms, results show efficiency gains of up to 53 percent, with minimal accuracy losses relative to a static simulation.
Subgrid modeling to account for unresolved topography within the context of shallow water equations relies on the use of coarse grids for computational efficiency. However, excessively coarse grids can lead to artificial cross flows between hydrologically disconnected areas separated by physical barriers smaller than the grid size. An approach based on introducing cell and edge clones, consisting of connected groups of pixels in each cell, is able to systematically remove such artificial cross flows. Such an approach considers that the subgrid barriers permanently divide flow among clones and effectively restrict flow to a predetermined path. In this work, a simple algorithm, along with the use of an overtopping formula, is proposed to extend the clone approach to a scenario in which clones are allowed to be further split and merged as needed, depending on the surface elevation during a given runtime. The algorithm is intended for accommodating the possibility of the subgrid barriers being inundated and no-longer dividing the flow during an extreme event. The performance of the proposed algorithm is demonstrated through a series of idealized and more realistic test cases, showing considerable improvements over existing methodologies.
As coastal circulation models have evolved to predict storm-induced flooding, they must include progressively more overland regions that are normally dry, to where now it is possible for more than half of the domain to be needed in none or only some of the computations. While this evolution has improved real-time forecasting and long-term mitigation of coastal flooding, it poses a problem for parallelization in an HPC environment, especially for static paradigms in which the workload is balanced only at the start of the simulation. In this study, a dynamic rebalancing of computational work is developed for a finite-element-based, shallow-water, ocean circulation model of extensive overland flooding. The implementation has a low overhead cost, and we demonstrate a realistic hurricane-forced coastal flooding simulation can achieve peak speed-ups near 45% over the static case, thus operating now at 80−90% efficiency.