ADCIRC Model Research Articles

Numerical Modeling of Extreme Sea Levels on the Laptev Sea Coast

The present study is devoted to the analysis of extreme sea level oscillations of the Laptev Sea using the ADCIRC model. The numerical modeling is performed on a high-resolution grid and verified for sea level observations from three tide gauges. We have revealed regional characteristics of extreme sea level oscillations for different parts of the Laptev Sea coast. The maximum total sea level range was 544 cm in Ebelyakh Bay, while the minimum was 267 cm in Khatanga Bay, where maximum tidal ranges were obtained. Some areas in Khatanga Bay and Anabar Bay had maximum tidal ranges exceeding 200 cm. The study provided an estimation of the possible magnitude of coastal flooding by calculating the extreme total and residual sea levels for different return periods: 1, 2, 5, 10, 20, 50, and 100 years. The amplitude of extreme surges calculated for the 100-year return period can exceed 300 cm for several sections of the Laptev Sea coast, with the maximum sea level range being about 680 cm for Anabar and Ebelyakh Bays.

Predictability of Hurricane Storm Surge: An Ensemble Forecasting Approach Using Global Atmospheric Model Data

Providing storm surge risk information at multi-day lead times is critical for hurricane evacuation decisions, but predictability of storm surge inundation at these lead times is limited. This study develops a method to parameterize and adjust tropical cyclones derived from global atmospheric model data, for use in storm surge research and prediction. We implement the method to generate storm tide (surge + tide) ensemble forecasts for Hurricane Michael (2018) at five initialization times, using archived operational ECMWF ensemble forecasts and the dynamical storm surge model ADCIRC. The results elucidate the potential for extending hurricane storm surge prediction to several-day lead times, along with the challenges of predicting the details of storm surge inundation even 18 h before landfall. They also indicate that accurately predicting Hurricane Michael’s rapid intensification was not needed to predict the storm surge risk. In addition, the analysis illustrates how this approach can help identify situationally and physically realistic scenarios that pose greater storm surge risk. From a practical perspective, the study suggests potential approaches for improving real-time probabilistic storm surge prediction. The method can also be useful for other applications of atmospheric model data in storm surge research, forecasting, and risk analysis, across weather and climate time scales.

A deep-learning model for rapid spatiotemporal prediction of coastal water levels

With the increasing impact of climate change and relative sea level rise, low-lying coastal communities face growing risks from recurrent nuisance flooding and storm tides. Thus, timely and reliable predictions of coastal water levels are critical to resilience in vulnerable coastal areas. Over the past decade, there has been increasing interest in utilizing machine learning (ML) based models for emulation and prediction of coastal water levels. However, flood advisory systems still rely on running computationally demanding hydrodynamic models. To alleviate the computational burden, these physics-based models are either run at small scales with high resolution or at large scales with low resolution. While ML-based models are very fast, they face challenges in terms of ensuring reliability and ability to capture any surge levels. In this paper, we develop a deep neural network for spatiotemporal prediction of water levels in coastal areas of the Chesapeake Bay in the U.S. Our model relies on data from numerical weather prediction models as the atmospheric input and astronomical tide levels, while its outputs are time series of predicted water levels at several tide gauge locations across the Chesapeake Bay. We utilized a CNN-LSTM setting as the architecture of the model. The CNN part extracts the features from a sequence of gridded wind fields and fuses its output to several independent LSTM units. The LSTM units concatenate the atmospheric features with respective astronomical tide levels and produce water level time series. The novel contribution of the present work is in spatiotemporality and in prioritization of the physical relationships in the model to maintain a high analogy to hydrodynamic modeling, either in the network architecture or in the selection of predictors and predictands. The results show that this setting yields a strong performance in predicting coastal water levels that cause flooding from minor to major levels. We also show that the model stands up successfully to the rigorous comparison with a high-fidelity ADCIRC model, yielding mean RMSE and correlation coefficient of 14.3 cm and 0.94, respectively, in two extreme cases, versus 12.30 cm and 0.96 for the ADCIRC model. The results highlight the practical feasibility of employing fast yet inexpensive data-driven models for resilient coastal management.

Impact of tidal dynamics and typhoon-induced inundation on saltwater intrusion in coastal farms

The increase in storm surge events caused by climate change exacerbates adverse effects on seawater inundation in coastal areas. An accurate description of the water level curve is crucial for understanding the process of saltwater intrusion (SWI) resulting from storm surge. Most studies involving empirical surges as inputs to groundwater models, often simplify spatial and temporal seawater inundation processes, which may increase the uncertainty in vertical seawater intrusion. To address this gap, we employed a comprehensive modeling approach using storm surge model ADCIRC and numerical simulator HydroGeoSphere to reveal SWI dynamics during a historical storm surge event in a coastal farm, considering varying tidal-surge phases and typhoon intensities. Our findings indicate pronounced SWI variations even with consistently highest water level during a storm surge, contingent on prior tidal processes. The timing of typhoon landfall on an hourly scale yielded diverse water level curves, altering the function of SWI. Intriguingly, SWI exacerbates following a high tide with 31.2 % average salinity higher, highlighting the profound modulation effect of tidal levels on SWI. Local topography significantly influenced SWI dynamics. Ponds, for instance, retained elevated salinity levels for over 15 h, indicating a more prolonged exposure to salinity than roads. These findings underscore the importance of considering both tidal influences and topographical factors in understanding and mitigating SWI in coastal agricultural management.

Life-cycle thinking-based decision support framework for multispan simply supported bridges under typhoon-induced wave, current and surge conditions

Coastal bridges usually suffer from wave, current, and storm surge hazards simultaneously under typhoons. Comprehensive mitigation measures can reduce the structural failure probability under these hazards but usually lead to a conservative structural design and a significant increase in the project budget. With the recent development of sustainable structural design, the multicriteria decision-making method can assist engineers in incorporating the life-cycle investment and probability of hazards in the design selection. In this paper, a life-cycle thinking-based decision support framework that considers multicriteria trade-offs and sustainable design was proposed for the design of coastal bridges under typhoon-induced wave, current and surge conditions. The simulation of the typhoon-induced wave, current and surge conditions was developed using SWAN + ADCIRC model, joint probability and environmental contours. The multispan simply supported (MSSS) bridge was then used to illustrate the framework. The main findings include that the void slab girder is better than the other girder types in the equal-weighted, risk-averse and pro-economic scenarios for the example bridge, but the change in girder types has a small impact on the economic cost index score. The increase in the girder height can increase the failure probability when deck shifting dominates the superstructure's failure.

Understanding the Effects of Wind Intensity, Forward Speed, and Wave on the Propagation of Hurricane Harvey Surges

Hurricane storm surges are influenced by wind intensity, forward speed, width and slope of the ocean bottom, central pressure, angle of approach, shape of coastal lines, local features, and storm size. A numerical experiment is conducted using the Advanced Circulation + Simulation and Simulating Waves Nearshore (ADCIRC + SWAN) coupled model for understanding the effects of wind intensity, forward speed, and wave on the storm surges caused by Hurricane Harvey. The ADCIRC + SWAN is used to simulate hurricane storm surges and waves. The wind fields of Hurricane Harvey were reconstructed from observed data, aided by a variety of methodologies and analyses conducted by Ocean Weather Inc (OWI) after the event. These reconstructed wind fields were used as the meteorological forcing in the base case in ADCIRC+SWAN to investigate the storm surges caused by the hurricane. Hurricane Harvey was the second most costly hurricane in the United States, causing severe urban flooding by dropping more than 60 inches of rainfall in Texas. The hurricane made three landfalls, with its first landfall as a Category 4 based on the Saffir–Simpson Hurricane Wind Scale (SSHWS), with wind intensities of 212.98 km/h (59 m/s). The storm surges caused by Hurricane Harvey were unique due to the slow speed, crooked tracks, triple landfalls in the USA, and excessive rain. The model’s storm surge and wave results were compared against observed data. High water marks at 21 locations and time series at 12 National Oceanic and Atmospheric Administration (NOAA) gauges were compared with the generated results. Several cases were investigated by increasing or decreasing the wind intensity or hurricane forward speed by 25% of the OWI wind and pressure data. The effects of the wave were analyzed by comparing the results obtained from ADCIRC + SWAN (with waves) and ADCIRC (without waves) models. The study found that the changes in wind intensity had the most significant effect on storm surges, followed by wave and forward speed changes. This study signifies the importance of considering these factors to enhance accuracy in predicting storm surges.

Future projections of storm surges and associated coastal inundation along the east coast of India

Abstract This study aims to analyze several aspects of storm surges and associated coastal inundation along the east coast of India. The current study utilizes historical cyclone tracks over the past five decades and, synthetic tracks are projected for the next 100 years to develop a comprehensive analysis of the storm surges in India. The impact of climate change on cyclone path and intensity is also considered. The ADCIRC model is used to compute storm surge heights and associated coastal inundation for historical and future cyclone tracks. An in-depth analysis is carried out using composite maps explaining the storm surge characteristics at various coastal locations. The novelty of this study lies in the comprehensive analysis of potential storm surges and associated coastal flooding related to exaggerated cyclones that are expected in a changing climate scenario. The outcome of the study is beneficial to storm surge operational centers and disaster management applications.

Simulating the spatial impacts of a coastal barrier in Galveston Island, Texas: a three-dimensional urban modeling approach

Due to its vulnerability to hurricanes, Galveston Island, TX, USA, is exploring the implementation of a coastal surge barrier (also referred to as the ‘Ike Dike’) for protection from severe flood events. This research evaluates the predicted effects that the coastal spine will have across four different storm scenarios, including a Hurricane Ike scenario and 10-year, 100-year, and 500-year storm events with and without a 2.4 ft. sea level rise (SLR). To achieve this, we develop a 1:1 ratio, 3-dimensional urban model and ran real-time flood projections using ADCIRC model data with and without the coastal barrier in place. Findings show that inundated area and property damages due to flooding will both significantly decrease if the coastal spine is implemented, with a 36% decrease in the inundated area and $4 billion less in property damage across all storm scenarios, on average. When including SLR, the amount of protection of the Ike Dike diminishes due to flooding from the bay side of the island. While the Ike Dike does appear to offer substantial protection from flooding in the short term, integrating the coastal barrier with other non-structural mechanisms would facilitate more long-term protection when considering SLR.

Improving the accuracy of hurricane wave modeling in Gulf of Mexico with dynamically-coupled SWAN and ADCIRC

Dynamically-coupled SWAN and ADCIRC models have been applied to enhance the predictions of extreme waves and storm surges induced by hurricanes and sea level rise (SLR) in the Gulf of Mexico. The model performance was evaluated using Hurricane Michael, a Category-5 hurricane, as a case study. Modeled wave heights were compared to the observations. Results indicate that the dynamically-coupled SWAN-ADCIRC models substantially enhance the modeling accuracy. By comparing to the maximum observed 2.69 m of wave height near the hurricane landing site, the error is 0.04 m by the SWAN-ADCIRC models in comparison to the 0.39 m by the SWAN stand-alone simulation. Effects of sea level rise on hurricane wave heights were investigated under four SLR scenarios of 0.2m, 0.5m, 1m, and 1.5m. Results indicate that, as sea level rises, wave heights increase non-linearly in shallow waters near the hurricane landing site. At the wave observation station near the hurricane landing site, the ratio of the wave-height change to SLR increases to 117% and the ratio of the combined wave-surge change to SLR increases to 265%. Analysis indicates that this is due to the substantial percentage changes in water depth occurring in shallow water compared to deep water caused by SLR.

Integrated Approach for Estimating Extreme Hydrodynamic Loads on Elevated Pile Cap Foundation Using Environmental Contour of Simulated Typhoon Wave, Current, and Surge Conditions

Abstract Typhoon is a disastrous weather system, which usually induces strong waves, currents, and surges along the coastal area, and causes severe hydrodynamic loads on the elevated pile cap foundation, which is widely used to support the sea-crossing bridge. Estimating the hydrodynamic loads under typhoons is essential to ensure the bridge's safety. This paper develops an environmental contour-based framework that can estimate the extreme hydrodynamic loads induced by typhoons while considering the correlation among environmental conditions. The elevated pile cap foundation of the Xihoumen Rail-cum-road Bridge was used to illustrate the framework. The SWAN + ADCIRC model was employed to simulate the environmental conditions under typhoons. The pair-copulas were adopted to construct joint probability distributions, and the environmental contours with a given return period were then established by the inverse first-order reliability method. Given the hydrodynamic model and short-term peak value of the structural response, the AK-LHS method was then used to find the maximum hydrodynamic loads based on the environmental contours. The environmental contour constructing methods and selection methods of short-term peak values were compared and discussed. The main findings include: (1) ignoring correlations of the environmental conditions overestimates the extreme hydrodynamic loads and results in a conservative design; (2) the estimation of extreme hydrodynamic loads is affected by the selection and fitting of short-term peak values significantly; and (3) the extreme hydrodynamic loads estimated by either Rosenblatt transformation or Nataf transformation shows similar results.

Storm Surges and Extreme Wind Waves in the Caspian Sea in the Present and Future Climate

The Caspian Sea is of particular interest. Against the background of long-term sea level changes, low-lying coastal areas in the northern part are subject to constant flooding as a result of storm surges. The elongation of the sea in the meridional direction allows the development of strong waves in the middle and southern parts. A comprehensive understanding of the characteristics of storm surges and storm waves is especially important in the context of ongoing climate change. This study is devoted to the analysis of storm surges for the time period from 1979 up to 2017 and wind waves from 1979 to 2020 in the Caspian Sea region. The circulation model ADCIRC and the wave model WAVEWATCH III with wind and pressure forcing from the NCEP/CFSR reanalysis were used. The modeling is performed on different unstructured grids with spacings of 500–900 m in the coastal zone. Mean and extreme values of surges, wave parameters and storm activity are provided in the research. The maximum significant wave height for the whole period was 8.2 m. The average long-term SWH did not exceed 1.1 m. No significant trends in the storm activity were found. The maximum surge height was 2.7 m. The analysis of the interannual variability of the surges' occurrence showed that 7–10 surges with a height of more than 1 meter were detected every year. The total duration of these surges was 20–30 days per year. Assessment of the risks of coastal flooding was carried out by calculating the extreme values of the sea for different return periods: 5, 10, 25, 50, and 100 years. The extreme sea level values in the northern part of the Caspian Sea for the 100-year return period are close to 3 m, and the areas with big surges are located along the eastern and western coasts. A forecast is made for the recurrence of storm wind waves in the 21st century based on climatic scenarios in CMIP5. A statistically significant increase in the recurrence of storm waves is to be expected in the near future, but that increase is not severe. Doi: 10.28991/CEJ-2022-08-11-01 Full Text: PDF

Evaluation of Wave Contributions in Hurricane Irma Storm Surge Hindcast

This paper evaluates the contribution of waves to the total predicted storm surges in a Hurricane Irma hindcast, using ADCIRC+SWAN and ADCIRC models. The contribution of waves is quantified by subtracting the water levels hindcasted by ADCIRC from those hindcasted by ADCIRC+SWAN, using OWI meteorological forcing in both models. Databases of water level time series, wave characteristic time series, and high-water marks are used to validate the model performance. Based on the application of our methodology to the coastline around Florida, a peninsula with unique geomorphic characteristics, we find that wave runup has the largest contribution to the total water levels on the south and northeast coasts. Waves increase the surge on the south and northeast coasts, due to large fetch and wave runups. On the west coast, the wave effect is not significant, due to limited fetch. However, significant wave heights become greater as the waves propagate into the deep inner gulf. The continental shelf on Florida’s west coast plays a critical role in decreasing the significant wave height and sheltering the coastal areas from large wave effects. Both models underpredict the high-water marks, but ADCIRC+SWAN reduces the underprediction and improves the parity with the observed data, although the scatter is slightly higher than that of ADCIRC.

Use of 1D Unsteady HEC-RAS in a Coupled System for Compound Flood Modeling: North Carolina Case Study

The research presented herein develops and compares an ADCIRC and ADCIRC/HEC-RAS (1D) paired model for the purpose of compound flood modeling within the Tar River and Pamlico Sound basins of North Carolina. Both the ADCIRC and 1D HEC-RAS models are capable of simulating river systems but differ in their underlying numerical formulations. A case-study comparison of each model’s ability to simulate flooding accurately and quickly in a riverine/estuarine system is investigated herein; results may serve as a valuable reference to forecasters and model developers. Individual models of the Tar River and Pamlico Sound area in North Carolina were used, and pairings of these models were devised to determine the benefits and drawbacks of using ADCIRC alone, or ADCIRC + 1D HEC-RAS, to simulate the response of the Tar River and Pamlico Sound during three test events: Hurricane Irene, Hurricane Floyd, and an unnamed April 2003 event. With increased emphasis on predicting total water levels, the results of this study can provide information for the possible development of similarly paired models for coastal river systems across the US and improve the body of knowledge about each model’s relative performance in riverine and estuarine areas.

The Impact of Typhoon Intensity on Wave Height and Storm Surge in the Northern East China Sea: A Comparative Case Study of Typhoon Muifa and Typhoon Lekima

A comparative study was conducted on typhoon intensity factors affecting the marine environment using two representative cases: Typhoon Lekima, which made landfall at Shandong Peninsula, the Northern East China Sea, and Typhoon Muifa, which did not. Using the ADCIRC and SWAN models, we developed a coupled numerical model and applied it to simulate the storm surge and destructive waves caused by typhoons. Three typhoon parameters—maximum wind speed, radius of maximum wind speed, and translation speed—were investigated through sensitivity experiments. The storm surge during the typhoon that made landfall showed a positive correlation with the distance of the typhoon’s center. The maximum significant wave height and storm surge had near-linear growth with a maximum wind speed but decreased with the growth rate of the radius of maximum wind. A rapid typhoon translation speed from 47 km/h to 60 km/h could cause a storm surge resonance phenomenon at the northern coast of the East China Sea.

Multi-decadal changes of mangrove forest and its response to the tidal dynamics of thane creek, Mumbai

Mangroves are one of the world threatened ecosystems, which is protected and categorised under CRZ-I according to the Coastal Regulation Zone (CRZ) notification. The present study marked the decadal (1990–2017, Landsat series) change of mangroves and mapped the species distribution (2017, Sentinel-2) around Thane creek, Mumbai using SMLC with QGIS-SCP software. ADCIRC model was used to simulate the tidal flooding/ebbing towards mangroves, and the model was validated with the in-situ observation of tides and currents. From 1990 to 2017, the mangrove area increased from 79.14 km2 to 154.5 km2 and expanded towards landward and seaward regions. Between 2010 and 2017, there was a fluctuation in the mangrove area with ups and downs in their distribution caused by different climatic conditions and anthropogenic activities. The increase in built-up area was two times than mangrove area increase. The dominance of Avicennia marina species confirms the increased anthropogenic activity along the landward side. To understand the response of mangroves to the tidal dynamics, the model was simulated with two scenarios; with mangroves and without mangroves. In the absence of mangroves (without mangroves), Thane Creek demonstrated a perfect funnelling effect by increased tidal amplification with strong flood currents, resulting in severe coastal inundation and erosion. While with mangroves, tidal currents attenuated 80% of its magnitude and favoured the sediment deposition in mangrove areas, which further enhanced mangrove growth, thereby stabilising the coast. The present study has found that the mangroves in the Thane creek are in the saturation stage and reached the maximum growth towards the landward. The study envisages that the stakeholders should adopt a proper management plan for the restoration of mangroves. The highlight of the present study is the combination of satellite imagery and hydrodynamic modelling. Satellite imagery provides the estimated extent of the mangroves, and this information will be used when simulating the model, which provides maximum inundation and attenuation. The utilisation of LULC classification and ADCIRC model results would be helpful to examine the threatening built-up area due to the tidal inundation. The combination of satellite classification and hydrodynamic model findings will be decisive for management authorities towards the conservation and regeneration activities for a balanced mangrove-creek ecosystem.

Numerical simulations of compound flooding caused by storm surge and heavy rain with the presence of urban drainage system, coastal dam and tide gates: A case study of Xiangshan, China

Nowadays, most coastal cities have complex drainage systems (i.e., rivers and pipelines) connected to the sea, affecting the flooding during the co-occurrence of rain and storm surges. In this study, this compound flooding is studied by developing a coupled model based on a one-dimensional (1D) hydrological model SWMM and a two-dimensional (2D) hydrodynamic model ADCIRC. The coupling is achieved by setting the 1D model as a subroutine of the 2D model while the parallel computing scheme of the 2D model is kept using the Message Passing Interface (MPI). The coupled model is applied in Xiangshan, Zhejiang Province, along the eastern coast of China. The model accurately ensures water conservation and reproduces the observed tidal elevation, storm surge, and river water stages during Typhoons Haikui (2012) and Fitow (2013). A series of simulations are carried out to quantify the influences of coastal dams, drainage systems, control of tide gates, rain, and storm surges on the compound flooding. The results show that the drainage system enhances the connectivity between the land and the sea no matter whether the coastal dam exists, leading to faster flooding and draining. Furthermore, when a storm surge occurs, the high surge level can significantly reduce the drainage efficiency of the inland flooding during rain and thus causes more severe flooding hazards. The simulation results also suggest that urban pipelines play an important role in preventing urban flooding caused by rain. And for the prevention of storm surge inundation, an effective gate control strategy is suggested that the gates should be closed when the water levels on both sides of the dam are equal for the first time before the peak of the storm surge and are open when the water levels are equal again. Finally, the flooded area can be divided into the tidal zone, the hydrologic zone, and the transition zone to identify different flood mitigation strategies.

Analysis of tidal currents modeling at Baubau City fuel oil terminal with adcirc model - SMS software

Tidal Currents are one of the important hydro oceanography components for studying coastal characteristics. The purpose of this study is to find out the types of tides and tidal current patterns at the fuel oil terminal in Baubau City (Buton). The method used to determine the speed of tidal currents and tidal type models using SMS (Surface Water Modelling System) applications with ADCIRC models taking into account the data of bathymetry and some components of the tidal currents in Baubau city Fuel oil Terminal area. The results obtained in the study showed that the type of ups and downs that occur in the Baubau fuel oil terminal is Mixed Tidal Leaning to Double Daily. The Highest Sea Level Elevation of the least-squares method is 1.07 m and Lowest at -1.07 m, on SMS modeling ADCIRC Highest Sea Level Elevation ranges from 0.78 m and the lowest at -1.02 m. The result of current speed using SMS ADCIRC modelling obtained the highest tidal current speed value in Baubau Fuel oil Terminal which is 0.63 m/s and the lowest current speed of 0.01 - 0.06 m/s. The direction of the current at low tide towards the dominant tide to the Southwest while at high tide towards the tide dominant current to the South.

Impact of varying landfall time and cyclone intensity on storm surges in the Bay of Bengal using ADCIRC model

Impact of varying landfall time and cyclone intensity on storm surges in the Bay of Bengal using ADCIRC model

Numerical estimation of the typhoon-induced wind and wave fields in Taiwan Strait

Typhoons are usually accompanied by storm surges, strong waves which are quite harmful to coastal buildings and infrastructures. Such disasters are quite critical for the Taiwan Strait which experiences typhoons nearly every year. In this paper, the SWAN + ADCIRC coupled model driven by hybrid wind field is adopted to simulate the wind and wave fields in Taiwan Strait. The drive files of wind and pressure are constructed by the hybrid model which combined the parametric model and the reanalysis wind field data provided by European Centre for Medium-Range Weather Forecasts (ECMWF). To validate the simulation results, the wind and wave measured data are compared with the simulation data of typhoons Nesat (T1709) and Maria (T1808). The results show the hybrid model has a better approximation to the actual wind speed value. Two different hybrid models are selected to drive the SWAN + ADCIRC model and the results are presented in the paper. According to the typhoon dataset of China Meteorological Administration (CMA), typhoons affecting the Taiwan Strait are classified into five categories (TP1 to TP5). Following this classification, the risk map of typhoon-induced wave at Taiwan Strait under different kinds of tracks are presented based on the coupled model and hybrid wind fields.

MULTI-HAZARD HURRICANE VULNERABILITY MODEL TO ENABLE RESILIENCE-INFORMED DECISION

Hurricanes or typhoons are multi-hazard events that usually result in strong winds, storm surge, waves, and debris flow. A community-level multi-hazard hurricane risk analysis approach is proposed herein to account for the combined impacts of hazards driven by hurricanes including surge, wave, and wind. A tightly coupled ADCIRC and SWAN model is used to account for the surge and wave hazard. Community-level exposure analysis is conducted using a portfolio of building archetypes associated with each hazard. A building-level hurricane vulnerability model is developed using fragility functions to account for content, building envelope, and structural damage. These fragility functions calculate the exceedance probability of predefined damage states associated with each hazard. Then, a building damage state is calculated based on the maximum probability of being in each damage state corresponding to each hazard. The proposed hurricane risk model is then applied to Waveland, Mississippi, a community that was severely impacted by Hurricane Katrina in 2005. The main contribution of this research is modeling the community-level hurricane vulnerability in terms of damage to the building envelope and interior contents driven by surge, wave, and wind using fragility functions to provide a comprehensive model for resilience-informed decision-making.