Storm Surge Model Research Articles

DEVELOPMENT AND VALIDATION OF A STORM SURGE AND WAVE MODEL FOR LAKE HURON (GREAT LAKES, USA)

The Federal Emergency Management Agency (FEMA) is tasked with developing flood insurance rate maps along coastlines and major water bodies within the United States, which includes the U.S. portion of the Great Lakes shoreline. Previous flood studies have developed storm surge and wave models of the Great Lakes (including Lake Huron) in support of FEMA’s efforts; however, an independent technical review of those previous coastal flood studies in Lake Huron revealed technical deficiencies in the methods and tools used to generate the wave conditions needed to support overland mapping. Most paramount of these was the fact that starting wave conditions for one dimensional (1D) transformation from a two-dimensional (2D) model were taken from deep water. Using 1D methods to shoal and refract waves to the coastline for runup and/or overland wave analysis may fail to capture the more complex nature of wave refraction/diffraction that 2D wave models can capture. Further, this method omits the development of the directional wave spectra in the nearshore region. To address this concern, a coupled 2D wave and water level model (ADCIRC+SWAN) was developed to hindcast historical storms that have occurred in Lake Huron. These model results will be used to drive the 1D methods to assess nearshore wave hazards from locations near the surfzone limit.

LAND USE AND MITIGATION EFFECTS ON BARRIER BEACH EROSION IN STORMS: CASE STUDY IN RHODE ISLAND

Sea Level Rise (SLR) and storm intensification lead to re-evaluating inundation assessments along the North Atlantic US shoreline. A particular effort is devoted to assessing coastal community risk to “100-year storm” events in Rhode Island, US, using a chain of state-of-the-art storm surge, wave propagation, and coastal erosion 2D models. Damage risks imposed on infrastructures and services incited US federal and state agencies to come up with innovative engineering solutions to improve coastal resiliency while preserving natural coastal and marine environments. This study critically evaluates available design tools used to assess the performance of two types of Natural and Natural Based Features (NNBFs) for coastal protection: natural vegetated barrier islands and dunes reinforced with Geotextile Sand-filled Containers (GSCs), on urbanized barrier islands. Comparative analyses with field data identifies the capabilities and limitations of phase averaging and phase resolving hydro-morphodynamic models used for simulating bed level changes in dissipative beaches, during 3 Sallenger storm regimes. Recommendations are provided on modeling approaches for simulating effects of vegetation and using GSCs to limit coastal erosion.

THE IMPACT OF BARRIER ISLAND DEGRADATION ON HURRICANE-INDUCED SEDIMENT TRANSPORT

Hurricanes are recognized as a strong forcing in changing coastal morphology by redistributing sediments. Barrier islands protect estuaries from storm surge and severe waves and confine water and sediment discharge into estuaries during a hurricane event. In this study, we developed a three-dimensional, fully coupled storm surge, waves, and sediment transport model. The impacts of barrier islands degradation on hurricane hydrodynamics and sediment dynamics were evaluated by comparing a hypothetical model configuration for four major barrier islands in Terrebonne Bay and Barataria Bay against a baseline configuration. With the hypothetical deterioration of barrier islands, model results showed that the sediment transport from the shelf to the estuary increased in Terrebonne Bay but decreased in Barataria Bay. In the simulations, most of the deposition on coastal wetland still originated from the bay even when the barrier islands were degraded.

IMPROVING THE ACCURACY OF SURGE MODELS USING SUBGRID CORRECTIONS

Modern storm surge models to predict hurricane water levels have gone in two opposite directions: (1) Low resolution, fast, models that may be run thousands of times as a storm approaches land; and (2) High resolution, more accurate, models that are largely used for planning and hindcasts, and are too slow for real-time ensemble forecasts. Differences in predictions between the two types of models are particularly large over flooded ground, which is most important for human activities.

DEVELOPMENT OF FUTURE RETURN PERIOD STILLWATER FLOODPLAINS FOR THE COASTS OF MISSISSIPPI, ALABAMA, AND THE FLORIDA PANHANDLE

Rising seas increase the exposure, vulnerability, and thus the risk associated with storm surge flowing across the coastal floodplain (Passeri et al. 2015). This is especially true across low-gradient coastal landscapes such as Mississippi, Alabama, and the Florida Panhandle. The extent and depth of flooding will be exasperated over the long term by morphologic changes to the shoreline, dunes and barrier islands (Plant et al. 2016, Passeri et al. 2016), marsh evolution (Alizad et al. 2016, Kidwell et al. 2017, Morris et al. 2016), and land use and land cover changes (Bilskie et al. 2014 & 2016). This presentation will describe how to incorporate biogeophysical impacts of climate change into future tide and surge models. A methodology will be presented (Bilskie et al. 2018) to down select a suite of synthetic storms from recent flood insurance studies to force hurricane storm surge models that represent present day and future changes to the coastal landscape under four sea level rise (SLR) scenarios of low (0.2 m), intermediate-low (0.5 m), intermediate-high (1.2 m), and high (2.0 m). Results of peak storm surge are used to compute the 100-year and 500-year return period floodplain and stillwater surge heights for each SLR scenario.

INCORPORATING THREE-DIMENSIONAL BAROCLINIC PROCESSES FOR ACCURATE DEPTH-INTEGRATED COASTAL CIRCULATION MODELLING

Depth-integrated coastal circulation models have proven to provide high-fidelity solutions to storm surge, tides, tsunamis, and those with wave-coupling (Westerink et al. 2008; Titov & Synolakis 1998). They are able to provide high horizontal resolution, and stable, high-order and low-diffusion numerical schemes making them often more useful than their three-dimensional counterparts despite more assumptions on the physics. However, the assumptions of no baroclinicity means that some processes such as steric effects, barotropic energy to baroclinic tidal energy conversion, and major baroclinic current systems cannot be directly modelled, creating limitations. This is directly problematic for example in storm surge forecasting systems where an offset between measured and predicted hydrographs may be present due to seasonal heating and cooling, changes to nearshore stratification and to the transport rates of major current systems and fresh water outflows.
 
 This study presents a process coupling paradigm to incorporate three-dimensional baroclinic effects into a depth-integrated model from a widely used and available baroclinic model, HYCOM (http://hycom.org). The depth-integrated finite-element model, ADCIRC (Westerink et al. 1992) is able to provide high-resolution to the coastal area, and has proven to be extremely accurate for storm surge modelling in e.g. the Gulf of Mexico (Westerink et al. 2008). However, along the Gulf of Mexico and east-coast of USA there are noticeable seasonal and inter-annual trends in the coastal sea level making forecasting more challenging than hindcasting. We present the effects of applying the information provided by HYCOM to ADCIRC in order to improve predicted hydrographs throughout the year of 2012 and in particular during Hurricane Sandy.

The role of atmospheric rivers in compound events consisting of heavy precipitation and high storm surges along the Dutch coast

Abstract. Atmospheric river (AR) systems play a significant role in the simultaneous occurrence of high coastal water levels and heavy precipitation in the Netherlands. Based on observed precipitation values (E-OBS) and the output of a numerical storm surge model (WAQUA/DSCMv5) forced with ERA-Interim sea level pressure and wind fields, we find that the majority of compound events (CEs) between 1979 and 2015 have been accompanied by the presence of an AR over the Netherlands. In detail, we show that CEs have a 3 to 4 times higher chance of occurrence on days with an AR over the Netherlands compared to any random day (i.e. days without knowledge on presence of an AR). In contrast, the occurrence of a CE on a day without AR is 3 times less likely than on any random day. Additionally, by isolating and assessing the prevailing sea level pressure (SLP) and sea surface temperature (SST) conditions with and without AR involvement up to 7 days before the events, we show that the presence of ARs constitutes a specific type of forcing conditions that (i) resemble the SLP anomaly patterns during the positive phase of the North Atlantic Oscillation (NAO+) with a north–south pressure dipole over the North Atlantic and (ii) cause a cooling of the North Atlantic subpolar gyre and eastern boundary upwelling zone while warming the western boundary of the North Atlantic. These conditions are clearly distinguishable from those during compound events without the influence of an AR which occur under SLP conditions resembling the East Atlantic (EA) pattern with a west–east pressure dipole over northern Europe and are accompanied by a cooling of the West Atlantic. Thus, this study shows that ARs are a useful tool for the early identification of possible harmful meteorological conditions over the Netherlands and supports an effort for the establishment of an early warning system.

An integration and assessment of multiple covariates of nonstationary storm surge statistical behavior by Bayesian model averaging

Abstract. Projections of coastal storm surge hazard are a basic requirement for effective management of coastal risks. A common approach for estimating hazards posed by extreme sea levels is to use a statistical model, which may use a time series of a climate variable as a covariate to modulate the statistical model and account for potentially nonstationary storm surge behavior (e.g., North Atlantic Oscillation index). Previous works using nonstationary statistical approaches to assess coastal flood hazard have demonstrated the importance of accounting for many key modeling uncertainties. However, many assessments have typically relied on a single climate covariate, which may leave out important processes and lead to potential biases in the projected flood hazards. Here, I employ a recently developed approach to integrate stationary and nonstationary statistical models, and characterize the effects of choice of covariate time series on projected flood hazard. Furthermore, I expand upon this approach by developing a nonstationary storm surge statistical model that makes use of multiple covariate time series, namely, global mean temperature, sea level, the North Atlantic Oscillation index and time. Using Norfolk, Virginia, as a case study, I show that a storm surge model that accounts for additional processes raises the projected 100-year storm surge return level by up to 23 cm relative to a stationary model or one that employs a single covariate time series. I find that the total model posterior probability associated with each candidate covariate, as well as a stationary model, is about 20 %. These results shed light on how including a wider range of physical process information and considering nonstationary behavior can better enable modeling efforts to inform coastal risk management.

Towards robust pan-European storm surge forecasting

Operational forecasting systems are important for disaster risk reduction. In this work we implement a coupled storm surge and tidal model on an unstructured grid over Europe towards the development of a pan-European Storm Surge Forecasting System (EU-SSF). The skill to predict tidal, surge and total water levels was evaluated based on measurements from 208 tidal gauge stations. Results show satisfactory performance for the two atmospheric forcing datasets tested, a High Resolution Forecast and ERA-INTERIM reanalysis, both provided by the European Center for Medium range Weather Forecast. For tidal predictions, the total RSS is equal to 0.197 m, lower than the values estimated by the global tidal model FES2004, and outperformed only by FES2012 (RSS = 0.05 m), which however is a product of data assimilation. Storm surge validation results show good predictive skill, with 0.04 m < RMSE < 0.21 m and %RMSE within 4%–22%. Coupling with tides results in improved storm surge level predictions, with RMSE reducing by up to 0.033 m. The areas benefiting most from the coupling are the North Sea and the English Channel, resulting in up to 2% reduction of the %RMSE. Increasing the resolution of atmospheric forcing also improves the predictive skill, leading to a reduction of RMSE up to 0.06 m in terms of the extremes, especially in shallow areas where wind is the main driver for surge production. We propose a setup for operational pan-European storm surge forecasting combining tidal levels from the FES2012 model and storm surge residuals from the EU-SSF setup which couples meteorological and astronomic tides.

The effects of mean sea level rise and strengthened winds on extreme sea levels in the Baltic Sea

ABSTRACT Mean sea level rise and climatological wind speed changes occur as part of the ongoing climate change and future projections of both variables are still highly uncertain. Here the Baltic Sea's response in extreme sea levels to perturbations in mean sea level and wind speeds is investigated in a series of simulations with a newly developed storm surge model based on the nucleus for European modeling of the ocean (NEMO)-Nordic. A simple linear model with only two tunable parameters is found to capture the changes in the return levels extremely well. The response to mean sea level rise is linear and nearly spatially uniform, meaning that a mean sea level rise of 1 m increases the return levels by a equal amount everywhere. The response to wind speed perturbations is more complicated and return levels are found to increase more where they are already high. This behaviour is alarming as it suggests that already flooding prone regions like the Gulf of Finland will be disproportionally adversely affected in a future windier climate.

Field survey of Typhoon Hato (2017) and a comparison with storm surge modeling in Macau

Abstract. On 23 August 2017 a Category 3 hurricane, Typhoon Hato, struck southern China. Among the hardest hit cities, Macau experienced the worst flooding since 1925. In this paper, we present a high-resolution survey map recording inundation depths and distances at 278 sites in Macau. We show that one-half of the Macau Peninsula was inundated, with the extent largely confined by the hilly topography. The Inner Harbor area suffered the most, with a maximum inundation depth of 3.1 m at the coast. Using a combination of numerical models, we simulate and reproduce this typhoon and storm surge event. We further investigate the effects of tidal level and sea level rise on coastal inundations in Macau during the landfall of a “Hato-like” event.

POST PROCESSING AND ANALYSIS OF STORM SURGE: A CASE STUDY OF HUDHUD AND PHAILIN CYCLONES

Abstract. Tropical cyclones affect the east coast of India due to its distinctive topography which is formed with a network of estuaries, bays, rivers, and inlets that causes inland flooding. The inland inundation of sea water is inflicting severe damage to the life and property. The ocean water entering the beachfront zone results to storm surges. In order to mitigate these storm surges, real-time monitoring and warnings are essential. For better visualization and analyzing the outputs from storm surge models, efficient post-processing tools are required. Hence post-processing of storm surge using GIS is carried out for taking protective measures. Storm surge vulnerable locations along the east coast of India have been identified in perspective of the number of storm surge events. Blue Kenue and SMS softwares are used to generate the unstructured triangular mesh over the study domain. Cyclones Phailin and Hudhud are selected in the current study and the associated surge heights and inundation extents are examined.

Calculation of Storm Surge by Non-stationary GEV Distribution Model

In Republic of Korea, stationary extreme value distribution models are generally used for estimating the design of coastal and harbor structures. However, due to the impact of climate change, the probability of typhoon is recently increasing. In order to consider this tendency, a non-stationary extreme value distribution model was applied in this study. The annual maximum storm surges were calculated by the storm surge model, and then, results from the storm surge model were applied to a non-stationary GEV (Generalized Extreme Value) distribution model to calculate the extreme storm surge height. The storm surge height of 50 year return period by non-stationary model was 28% higher than the storm surge height of a previous study that used stationary models. The overall results achieved in this study are expected to provide data and useful in establishing a master paln for disaster prevention. Keywords: Non-Stationary, GEV Model, Maximum Likelihood Method, Storm Surge

Modeling wave effects on storm surge and coastal inundation

We present a parametric study of surface wave effects on storm surge and coastal inundation. Hurricane wind forcing terms, atmosphere pressure gradient terms, and radiation open boundary conditions are implemented into an existing quasi-3D nearshore model, NearCoM-TVD, which uses a shock-capturing TVD scheme and can better simulate the wetting-drying process during inundation than a conventional finite difference model. Systematic numerical experiments are carried out in an idealized continental shelf-beach-land system to identify the role of waves in modeling storm surge and inundation under different storm characteristics. Four storm parameters, including storm intensity, storm size, translation speed and incident angle are investigated. Modeling results reveal that the presence of waves can increase the maximum storm surge heights significantly through wave setup, and the contribution of waves varies considerably depending on the storm characteristics. In addition to direct wave forcing, the wave-enhanced bottom stress in the surfzone also promotes higher wave setup and hence higher surge heights. Waves also have a major influence on the maximum inland inundation distance, however, we find that waves do not always favor more inundation as expected. For storms traveling at very slow translation speeds or nearly parallel to the coast, waves surprisingly exert a negative effect on the maximum inundation distance. We argue that wave-enhanced bottom stress combined with longer forcing duration in such storms counteract the positive effect of wave setup, and thus less inundation is predicted in wave-current coupled simulations. Our results highlight the necessity of fully-incorporating wave effects in storm surge and inundation modeling.

Potential Impacts of Sea Level Rise and Coarse Scale Marsh Migration on Storm Surge Hydrodynamics and Waves on Coastal Protected Areas in the Chesapeake Bay

The increasing rate of sea level rise (SLR) poses a major threat to coastal lands and natural resources, especially affecting natural preserves and protected areas along the coast. These impacts are likely to exacerbate when combined with storm surges. It is also expected that SLR will cause spatial reduction and migration of coastal wetland and marsh ecosystems, which are common in the natural preserves. This study evaluates the potential impacts of SLR and marsh migration on the hydrodynamics and waves conditions inside natural protected areas during storm surge. The study focused on four protected areas located in different areas of the Chesapeake Bay representing different hydrodynamic regimes. Historical and synthetic storms are simulated using a coupled storm surge (ADCIRC) and wave (SWAN) model for the Bay region for current condition and future scenarios. The future scenarios include different rates of local SLR projections (0.48 m, 0.97 m, 1.68 m, and 2.31 m) and potential land use changes due to SLR driven marsh migration, which is discretized in the selected preserve areas in a coarse scale. The results showed a linear increase of maximum water depth with respect to SLR inside the protected areas. However, the inundation extent, the maximum wave heights, and the current velocities inside the coastal protected areas showed a non-linear relationship with SLR, indicating that the combined impacts of storm surge, SLR, and marsh migration depend on multiple factors such as storm track, intensity, local topography, and locations of coastal protected areas. Furthermore, the impacts of SLR were significantly greater after a 1 m threshold of rise, suggesting the presence of a critical limit for conservation strategies.

Study of the wind drag coefficient during the storm Xaver in the German Bight using data assimilation

Wind stress is the most important driving force for storm surge in coastal waters. Currently, the parameterization of wind stress is still not well developed and is the most uncertain parameters for storm surge models. In this paper, a storm surge model for the German Bight is developed using the model Delft3D. The data assimilation method, adjoint-free 4Dvar, which is relatively easier to be implemented than the adjoint method, is used to assimilate measured water level data into Delft3D. The storm surge prediction is more accurate when we adjusted the drag coefficient using the adjoint free data assimilation method, than in a companion forward model. The drag coefficient is consistent with results from previous studies. The wind drag coefficient is also calculated using results of a wave model. It has been found that the relation between the drag coefficient and wind speed is approximately linear in the deep water. But in the shallow water, wind drag coefficient shows larger variability due to the wave shoaling effect. The linear relation adjusted by data assimilation agrees well with that derived from a wave-related formula. It is also found that wave-related parameterization scheme is necessary for shallow waters.

Implementation of an Implicit Solver in ADCIRC Storm Surge Model

The current state of science does not offer any remedy to stop a hurricane from occurring. Therefore, accurate storm surge models capable of predicting water velocity and elevation are indispensable. In this paper, the implementation of an implicit solver in the Advanced Circulation (ADCIRC) storm surge model is presented. The implemented implicit solver uses hybrid finite element and finite volume techniques for solving shallow water equations. Objectives of this research include: Enhancing numerical stability, providing an option of using large timesteps, and the usage of a relatively easier mathematical formulation than the existing one in ADCIRC. The storm surge hindcast of Hurricane Katrina that hit Louisiana and Mississippi in 2005 is used as a case study. Stability of the solver, comparison of water elevation and velocity against observed data, impact of timestep sizes, and execution times of solvers are thoroughly investigated in this study. Results of the implemented implicit solver are compared with those of existing lumped explicit and semi-implicit solvers of ADCIRC; the findings appear to be very promising.

Modelling of Storm-induced Seawater Flooding in the Suyeong River Area, South Korea: A Case Study due to the Storm Surge and Waves during Typhoon Sanba

Yuk, J.-H.; Park, J.H., and Joh, M., 2018. Modelling of Storm-induced Seawater Flooding in the Suyeong River Area, South Korea: A Case Study due to the Storm Surge and Waves during Typhoon Sanba. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 746–750. Coconut Creek (Florida), ISSN 0749-0208.The Suyeong River Area (SRA), located in Busan, a major city on the southeastern coast of South Korea, is frequently damaged by storm-induced seawater flooding. One of the main reasons for seawater flooding is the propagation of storm surges and wind waves through the Suyeong River in the SRA. In this study, a series of prediction systems of storm tides, surges, waves and resultant seawater flooding for the SRA based on unstructured meshes with a high resolution of approximately 10 m covering the entire flood plain and a HPC-based parallel tide-surge-wave model were developed. Meteorological forcing variables such as wind and air pressure calculated by the parametric tropical cyclone model based on typhoon information were used in the storm-surge and wave models. The modeled meteorological data were in good agreement with observations of both the wind and air pressure. The simulated surge heights and wave properties showed good agreement with the observations as well. Waves reached the mid-stream area of the SRA, likely affecting the duration of seawater flooding. The prediction system in this study can reasonably simulate tide-surge-wave and resultant seawater flooding (coastal inundation) during extreme conditions, e.g., storms in the SRA of Busan, South Korea.

Study on Storm Surge Prediction Model Considering Typhoon Characteristics for Largest Scale

ABSTRACT Kim, Y.-J.; Itoh, S.; Oya, Y., and Yoon, J.-S., 2018. Study on storm surge prediction model considering typhoon characteristics for largest scale. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 736–740. Coconut Creek (Florida), ISSN 0749-0208. The coastal area of Japan has been damaged yearly with many storm surges and flooding disasters in the past, including those associated with tropical cyclones (TCs). Also, the scale of damage is increasing rapidly due to the changing global climate and environment. As the disasters due to storm surges become unpredictable, more measures should be taken to prevent serious damage and casualties. Therefore, in this study, the aim is to mitigate the unpredictable damage by assuming storm surges of the largest scale and to propose a storm surge model that considers the characteristics of TCs. The main objectives of ...

Simulation of Wave Overtopping and Inundation over a Dike Caused by Typhoon Chaba at Marine City, Busan, Korea

Suh, S.-W. and Kim, H.-J., 2018. Simulation of wave overtopping and inundation over a dike caused by Typhoon Chaba at Marine city, Busan, Korea. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 711–715. Coconut Creek (Florida), ISSN 0749-0208.This study follows up previous research on simulating the wave-induced overtopping of coastal dikes by incorporating the empirical formulas of EurOtop version 2007 into the storm surge model ADCIRC SWAN. Hindcasting simulations were performed for the wave overtopping and inundation induced by Typhoon Chaba along the dike of Marine City, South Korea, in 2016. The simulation results showed that the wave overtopping and inundation lasted for at least three hours and were spread over the dike. Normal storm surge inundation was not seen because the dike crest height of 4.40 m was higher than the peak water surface elevation (WSE) of 1.13 m and significant wave height of 3.09 m. Near the dike, the wave overtopped maximum inundation height was ~0.7 m and decreased along the overland road to the upper zone, which agrees with the field survey results. This tendency was almost the same as that reported previously regardless of the dike dimensions and incoming wave heights. The reduction factor in EurOtop is an important influence in generating the inundation. Sensitivity tests indicated that a value of 0.63 is appropriate for combining a rising WSE with storm waves and filling gap effects on two-layer tetrapod slopes. This kind of approach to inundation vulnerability is more applicable than the prevailing storm surge inundation for natural or low-lying coastal areas because more than 50% of the South Korean coast is artificial and should help in developing early warning systems and/or vulnerability analyses of mitigation projects at other artificial coasts.