Influence of landscape restoration and degradation on storm surge and waves in southern Louisiana

The purpose of this investigation was to examine storm surge and wave reduction benefits of different environmental restoration features (marsh restoration and barrier island changes), as well as the impact of future wetland degradation on local surge and wave conditions. Storm surge simulations of two representative hurricanes were performed using the ADCIRC storm surge model with the inclusion of radiation stress gradients from the STWAVE nearshore wave model. Coupled model simulations were made for a number of landscape configurations that involved both restored and degraded wetland features. The impact of barrier island condition on hurricane surge and waves was also evaluated. Effects of landscape features were represented by changes in elevation and frictional resistance. Restoration and degradation of marsh resulted in decreases (for restoration cases) and increases (for degradation cases) in both surge and waves. The magnitude of change was correlated with the magnitude of the horizontal extent and elevation changes in the marsh. In general, the wave change patterns are consistent with the water level changes. Deflation of the Chandeleur Islands (barrier island chain) resulted in slightly increased surge. Results suggest that coastal marsh does have surge and wave reduction potential. Results also indicate that the impact of the landscape features is amplified in areas where there are levee “pockets.” Barrier islands and coastal ridges reduce wave heights, even if in a degraded condition and thus can reduce wave energy in wetland areas, protecting them from erosion.     

A hurricane surge risk assessment framework using the joint probability method and surge response functions

Hurricane surge events have caused devastating damage in active-hurricane areas all over the world. The ability to predict surge elevations and to use this information for damage estimation is fundamental for saving lives and protecting property. In this study, we developed a framework for evaluating hurricane flood risk and identifying areas that are more prone to them. The approach is based on the joint probability method with optimal sampling (JPM-OS) using surge response functions (SRFs) (JPM-OS-SRF). Derived from a discrete set of high-fidelity storm surge simulations, SRFs are non-dimensional, physics-based empirical equations with an algebraic form, used to rapidly estimate surge as a function of hurricane parameters (i.e., central pressure, radius, forward speed, approach angle and landfall location). The advantage of an SRF-based approach is that a continuum of storm scenarios can be efficiently evaluated and used to estimate continuous probability density functions for surge extremes, producing more statistically stable surge hazard assessments without adding measurably to epistemic uncertainty. SRFs were developed along the coastline and then used to estimate maximum surge elevations with respect to a set of hurricane parameters. Integrating information such as ground elevation, property value and population with the JPM-OS-SRF allows quantification of storm surge-induced hazard impacts over the continuum of storm possibilities, yielding a framework to create the following risk-based products, which can be used to assist in hurricane hazard management and decision making: (1) expected annual loss maps; (2) flood damage versus return period relationships; and (3) affected business (e.g., number of business, number of employees) versus return period relationships. By employing several simplifying assumptions, the framework is demonstrated at three northern Gulf of Mexico study sites exhibiting similar surge hazard exposure. The framework results reveal Gulfport, MS, USA is at relatively more risk of economic loss than Corpus Christi, TX, USA, and Panama City, FL, USA. Note that economic processes are complex and very interrelated to most other human activities. Our intention here is to present a methodology to quantify the flood damage (i.e., infrastructure economic loss, number of businesses affected, number of employees in these affected businesses and sales volume in these affected businesses) but not to discuss the complex interactions of these damages with other economic activities and recovery plans.     

Regional attributes of hurricane surge response functions for hazard assessment

Accurate quantification of hurricane surge probabilities is critically important for coastal planning and design. Recently, the joint probability method has been shown to yield statistically reliable surge probabilities and has quickly become the method of choice for extreme-value surge analysis in the United States. A main disadvantage of the joint probability method is the requirement to have accurate computational surge simulations for a large array of hurricane conditions. Recently, this shortcoming has been overcome by using a variety of interpolation schemes to reduce the number of surge simulations required to an optimal sample for joint probability analysis. One interpolation scheme uses response functions, or physically based dimensionless scaling laws, that consider the relative impact of hurricane landfall position, central pressure, and storm size on surge magnitude at the location of interest. Here, the influence of regional changes in bathymetry on the physically based response function form is investigated. It will be shown that the influence of continental shelf width on surge generation along a continuous coast is coupled with the influence of storm size and that this coupled physical effect can be treated within the response functions via dimensionless scaling. The surge response function model presented here has an algebraic form for rapid calculation. This model performs well for the entire 600-km Texas coast, yielding accurate surge estimates (root-mean-square errors less than 0.22?m and R ² correlations better than 0.97) with virtually no bias (mean error magnitudes less than 0.03?m).     

A surge response function approach to coastal hazard assessment. Part 2: Quantification of spatial attributes of response functions

In response to the 2004 and 2005 hurricane seasons, surge risk assessment approaches have been re-evaluated to develop more rapid, reliable methods for predicting the risk associated with extreme hurricanes. Here, the development of dimensionless surge response functions relating surge to hurricane meteorological parameters is presented. Such response functions present an opportunity to maximize surge data usage and to improve statistical estimates of surge probability by providing a means for defining continuous probability density functions. A numerical modeling investigation was carried out for the Texas, USA coastline to develop physical scaling laws relating storm surge response with hurricane parameters including storm size, intensity, and track. It will be shown that these scaling laws successfully estimate the surge response at any arbitrary location for any arbitrary storm track within the study region. Such a prediction methodology has the potential to decrease numerical computation requirements by 75% for hurricane risk assessment studies.     

A hurricane surge risk assessment framework using the joint probability method and surge response functions

Hurricane surge events have caused devastating damage in active-hurricane areas all over the world. The ability to predict surge elevations and to use this information for damage estimation is fundamental for saving lives and protecting property. In this study, we developed a framework for evaluating hurricane flood risk and identifying areas that are more prone to them. The approach is based on the joint probability method with optimal sampling (JPM-OS) using surge response functions (SRFs) (JPM-OS-SRF). Derived from a discrete set of high-fidelity storm surge simulations, SRFs are non-dimensional, physics-based empirical equations with an algebraic form, used to rapidly estimate surge as a function of hurricane parameters (i.e., central pressure, radius, forward speed, approach angle and landfall location). The advantage of an SRF-based approach is that a continuum of storm scenarios can be efficiently evaluated and used to estimate continuous probability density functions for surge extremes, producing more statistically stable surge hazard assessments without adding measurably to epistemic uncertainty. SRFs were developed along the coastline and then used to estimate maximum surge elevations with respect to a set of hurricane parameters. Integrating information such as ground elevation, property value and population with the JPM-OS-SRF allows quantification of storm surge-induced hazard impacts over the continuum of storm possibilities, yielding a framework to create the following risk-based products, which can be used to assist in hurricane hazard management and decision making: (1) expected annual loss maps; (2) flood damage versus return period relationships; and (3) affected business (e.g., number of business, number of employees) versus return period relationships. By employing several simplifying assumptions, the framework is demonstrated at three northern Gulf of Mexico study sites exhibiting similar surge hazard exposure. The framework results reveal Gulfport, MS, USA is at relatively more risk of economic loss than Corpus Christi, TX, USA, and Panama City, FL, USA. Note that economic processes are complex and very interrelated to most other human activities. Our intention here is to present a methodology to quantify the flood damage (i.e., infrastructure economic loss, number of businesses affected, number of employees in these affected businesses and sales volume in these affected businesses) but not to discuss the complex interactions of these damages with other economic activities and recovery plans.

     

Evaluation of coastal inundation hazard for present and future climates

Coastal inundation from hurricane storm surges causes catastrophic damage to lives and property, as evidenced by recent hurricanes including Katrina and Wilma in 2005 and Ike in 2008. Changes in hurricane activity and sea level due to a warming climate, together with growing coastal population, are expected to increase the potential for loss of property and lives. Current inundation hazard maps: Base Flood Elevation maps and Maximum of Maximums are computationally expensive to create in order to fully represent the hurricane climatology, and do not account for climate change. This paper evaluates the coastal inundation hazard in Southwest Florida for present and future climates, using a high resolution storm surge modeling system, CH3D-SSMS, and an optimal storm ensemble with multivariate interpolation, while accounting for climate change. Storm surges associated with the optimal storms are simulated with CH3D-SSMS and the results are used to obtain the response to any storm via interpolation, allowing accurate representation of the hurricane climatology and efficient generation of hazard maps. Incorporating the impact of anticipated climate change on hurricane and sea level, the inundation maps for future climate scenarios are made and affected people and property estimated. The future climate scenarios produce little change to coastal inundation, due likely to the reduction in hurricane frequency, except when extreme sea level rise is included. Calculated coastal inundation due to sea level rise without using a coastal surge model is also determined and shown to significantly overestimate the inundation due to neglect of land dissipation.     

The impact of extra-tropical transitioning on storm surge and waves in catastrophe risk modelling: application to the Japanese coastline

Catastrophe risk models are used to assess and manage the economic and societal impacts of natural perils such as tropical cyclones. Large ensembles of event simulations are required to generate useful model output. For example, to estimate the risk due to wind-driven storm surge and waves in tropical cyclone risk models, computationally efficient parametric representations of the wind forcing are required to enable the generation of large ensembles. This paper presents new results on the impact of including explicit representations of extra-tropical transitioning in parametric wind models used to force storm surge and wave simulations in a catastrophe risk modelling context. Extra-tropical transitioning is particularly important in modelling risk on the Japanese coastline, as roughly 40 % of typhoons hitting the Japanese mainland are transitioning before landfall. Using both a historical and idealized track set, we compare maximum storm surge and wave footprints along the Japanese coastline for models that include, and do not include, explicit representations of extra-tropical transitioning. We find that the inclusion of extra-tropical transitioning leads to lower storm surge (10–20 %) and waves (5–15 %) on the southern Japanese coast, with significantly higher storm surge and waves along the northern coast (25–50 %). The results of this paper demonstrate that useful risk assessment of coastal flood risk in Japan must consider the extra-tropical transitioning process.     

Hurricane storm surge simulations for Tampa Bay

Using a high resolution, three-dimensional, primitive equation, finite volume coastal ocean model with flooding and drying capabilities, supported by a merged bathymetric-topographic data set and driven by prototypical hurricane winds and atmospheric pressure fields, we investigated the storm surge responses for the Tampa Bay, Florida, vicinity and their sensitivities to point of landfall, direction and speed of approach, and intensity. All of these factors were found to be important. Flooding potential by wind stress and atmospheric pressure induced surge is significant for a category 2 hurricane and catastrophic for a category 4 hurricane. Tide, river, and wave effects are additive, making the potential for flood-induced damage even greater. Since storm surge sets up as a slope to the sea surface, the highest surge tends to occur over the upper reaches of the bay, Old Tampa Bay and Hillsborough Bay in particular. For point of landfall sensitivity, the worst case is when the hurricane center is positioned north of the bay mouth such that the maximum winds associated with the eye wall are at the bay mouth. Northerly (southerly) approaching storms yield larger (smaller) surges since the winds initially set up (set down) water level. As a hybrid between the landfall and direction sensitivity experiments, a storm transiting up the bay axis from southwest to northeast yields the smallest surge, debunking a misconception that this is the worst Tampa Bay flooding case. Hurricanes with slow (fast) translation speeds yield larger (smaller) surges within Tampa Bay due to the time required to redistribute mass.     

Slope Stability Analysis of Earthen Levee Strengthened by High Performance Turf Reinforcement Mat under Hurricane Overtopping Flow Conditions

The slope stability of levees during hurricane overtopping conditions involving storm surge and wind generated wave action is an important aspect to assess the safety of earthen levees. A comprehensive slope stability investigation was conducted in this study for an earthen levee subjected to full-scale overtopping scenarios, including storm surge only overflow, wave only overtopping, and combined wave and surge overtopping conditions. The crest and the landside of the levee were strengthened by high performance turf reinforcement mat (HPTRM) to protect against overtopping erosion. A conceptual model for HPTRM strengthened levee as well as a methodology for analysis and incorporation of various overtopping flow conditions in levee slope stability is presented. The findings of this study indicate that HPTRM strengthening of the levee improves the stability of the levee significantly during wave only as well as combined storm surge and wave overtopping conditions. However, during the storm surge conditions, the factor of safety is only improved slightly as a result of strengthening of the levee by HPTRM.     

A geospatial framework to estimate depth of scour under buildings due to storm surge in coastal areas

Hurricanes and tropical storms represent one of the major hazards in coastal communities. Storm surge generated by strong winds and low pressure from these systems have the potential to bring extensive flooding in coastal areas. In many cases, the damage caused by the storm surge may exceed the damage from the wind resulting in the total collapse of buildings. Therefore, in coastal areas, one of the sources for major structural damage could be due to scour, where the soil below the building that serves as the foundation is swept away by the movement of the water. The existing methodologies to forecast hurricane flood damage do not differentiate between the different damage mechanisms (e.g., inundation vs. scour). Currently, there are no tools available that predominantly focus on forecasting scour-related damage for buildings. Such a tool could provide significant advantages for planning and/or preparing emergency responses. Therefore, the focus of this study was to develop a methodology to predict possible scour depth due to hurricane storm surges using an automated ArcGIS tool that incorporates the expected hurricane conditions (flow depth, velocity, and flood duration), site-specific building information, and the associated soil types for the foundation. A case study from Monmouth County (NJ), where the scour damages from 2012 Hurricane Sandy were recorded after the storm, was used to evaluate the accuracy of the developed forecasting tool and to relate the scour depth to potential scour damage. The results indicate that the developed tool provides relatively consistent results with the field observations.     

Slope stability of earthen levee strengthened by roller-compacted concrete under hurricane overtopping flow conditions

Although an important aspect of the assessment of safety of earthen levees is the consideration for its global stability, little is known regarding the slope stability of levees during hurricane overtopping conditions involving storm surge and wind generated wave action. In this study, a comprehensive slope stability investigation was undertaken where an earthen levee, representing full-scale overtopping conditions, was subjected to storm surge only overflow, wave only overtopping and combined wave and surge overtopping conditions. The crest and the landside of the levee were strengthened by roller-compacted concrete (RCC) to protect against overtopping. This paper presents a conceptual model for an RCC strengthened levee as well as a methodology for analysis and incorporation of various overtopping flow conditions in levee slope stability. The findings of this study indicate that RCC strengthening of the levee improves the stability of the levee significantly during wave only as well as combined storm surge and wave overtopping conditions. However, strengthening of the levee by RCC does not increase the factor of safety during the storm surge conditions.     

A modeling study of coastal inundation induced by storm surge,sea-level rise,and subsidence in the Gulf of Mexico

The northern coasts of the Gulf of Mexico (GoM) are highly vulnerable to the direct threats of climate change, such as hurricane-induced storm surge, and such risks are exacerbated by land subsidence and global sea-level rise. This paper presents an application of a coastal storm surge model to study the coastal inundation process induced by tide and storm surge, and its response to the effects of land subsidence and sea-level rise in the northern Gulf coast. The unstructured-grid finite-volume coastal ocean model was used to simulate tides and hurricane-induced storm surges in the GoM. Simulated distributions of co-amplitude and co-phase lines for semi-diurnal and diurnal tides are in good agreement with previous modeling studies. The storm surges induced by four historical hurricanes (Rita, Katrina, Ivan, and Dolly) were simulated and compared to observed water levels at National Oceanic and Atmospheric Administration tide stations. Effects of coastal subsidence and future global sea-level rise on coastal inundation in the Louisiana coast were evaluated using a “change of inundation depth” parameter through sensitivity simulations that were based on a projected future subsidence scenario and 1-m global sea-level rise by the end of the century. Model results suggested that hurricane-induced storm surge height and coastal inundation could be exacerbated by future global sea-level rise and subsidence, and that responses of storm surge and coastal inundation to the effects of sea-level rise and subsidence are highly nonlinear and vary on temporal and spatial scales.     

Quantifying the impact of ecosystem services for landscape management under wildfire hazard

Natural Hazards - In order to accommodate the computational burden of high-fidelity storm surge numerical models, surrogate modeling (metamodeling) techniques have gained significant popularity...     

海洋环境因素极值组合及设计标准

由于海洋环境条件的复杂性、多变性及随机性,设计标准的选取是决定工程结构安全度、造价、效益及合理型式的主要因素。传统的设计标准,无法考虑海洋环境条件的随机组合,往往过高估计环境条件设计标准,造成不必要的浪费,甚至使具有开发前景的油田失去开采价值。以实测和后报资料为基础,使用多维联合概率的随机模拟技术,结合不同结构型式的极值响应及不同资料样本的选择方法,提出了海洋工程结构物上的风、浪、流、潮联合荷载及相应的联合概率水平问题,用以作为海洋工程环境荷载设计标准。     

Spatially explicit mapping of hurricane risk in New England, USA using ArcGIS

Hurricanes are one of the major natural disturbances affecting human livelihoods in coastal zones worldwide. Assessing hurricane risk is an important step toward mitigating the impact of tropical storms on human life and property. This study uses NOAA’s historical tropical cyclone database (HURDAT or ‘best-track’), geographic information systems, and kernel smoothing techniques to generate spatially explicit hurricane risk maps for New England. Southern New England had the highest hurricane risk across the region for all storm intensities. Long Island, western Connecticut, western Massachusetts, and southern Cape Cod, Martha’s Vineyard, and Nantucket had high storm probabilities and wind speeds. Results from this study suggest that these locations may be of central importance for focusing risk amelioration resources along the Long Island and New England coastlines. This paper presents a simple methodology for hurricane risk assessment that could be applied to other regions where long-term spatial storm track data exist.     

Dynamic analysis of emergency inter-organizational communication network under public health emergency: a case study of COVID-19 in Hubei Province of China

Storm surge induced by hurricane is a major threat to the Gulf Coasts of the United States. A numerical modeling study was conducted to simulate the storm surge during Hurricane Michael, a category 5 hurricane that landed on the Florida Panhandle in 2018. A high-resolution model mesh was used in the ADCIRC hydrodynamic model to simulate storm surge and tides during the hurricane. Two parametric wind models, Holland 1980 model and Holland 2010 model, have been evaluated for their effects on the accuracy of storm surge modeling by comparing simulated and observed maximum water levels along the coast. The wind model parameters are determined by observed hurricane wind and pressure data. Results indicate that both Holland 1980 and Holland 2010 wind models produce reasonable accuracy in predicting maximum water level in Mexico Beach, with errors between 1 and 3.7%. Comparing to the observed peak water level of 4.74 m in Mexico Beach, Holland 1980 wind model with radius of 64-knot wind speed for parameter estimation results in the lowest error of 1%. For a given wind model, the wind profiles are also affected by the wind data used for parameter estimation. Away from hurricane eye wall, using radius of 64-knot wind speed for parameter estimation generally produces weaker wind than those using radius of 34-knot wind speed for parameter estimation. Comparing model simulated storm tides with 17 water marks observed along the coast, Holland 2010 wind model using radius of 34-knot wind speed for parameter estimation leads to the minimum mean absolute error. The results will provide a good reference for researchers to improve storm surge modeling. The validated model can be used to support coastal hazard mitigation planning.

     

The role of overwash in the evolution of mixing zone morphology within barrier islands

Overwash is a major controlling factor in the morphology of the mixing zone of coastal aquifers. Conceptual models of the mixing zone describe an interface controlled by tidal oscillations, wave run-up, and other factors; however, few describe the influence of large storm events. In August 1993, Hatteras Island, North Carolina, USA, experienced a 3-m storm surge due to Hurricane Emily. Sound-side flooding infiltrated a wellfield, causing a dramatic increase in TDS levels that persisted for more than 3 years. Two-dimensional simulations with SUTRA, the USGS finite-element model, are calibrated to the TDS breakthrough data of this storm to infer model dispersivity values. Simulations using the calibrated dispersivity values, predicted flooding levels, and 54 years of hurricane records to determine the influence of the overwash events suggest that it is rare for the mixing zone to approximate the conceptual morphology. Even during quiescent periods such as between 1965 and 1975, TDS levels do not return to theoretical levels before being elevated by a subsequent storm event. Thus, while tidal oscillations and other factors are important to mixing zone development, basic wind events and more severe storm events may have more influence and lasting effect on the morphology of the mixing zone.     

Vulnerability of Hampton Roads,Virginia to Storm-Surge Flooding and Sea-Level Rise

Sea-level rise will increase the area covered by hurricane storm surges in coastal zones. This research assesses how patterns of vulnerability to storm-surge flooding could change in Hampton Roads, Virginia as a result of sea-level rise. Physical exposure to storm-surge flooding is mapped for all categories of hurricane, both for present sea level and for future sea-level rise. The locations of vulnerable sub-populations are determined through an analysis and mapping of socioeconomic characteristics commonly associated with vulnerability to environmental hazards and are compared to the flood-risk exposure zones. Scenarios are also developed that address uncertainties regarding future population growth and distribution. The results show that hurricane storm surge presents a significant hazard to Hampton Roads today, especially to the most vulnerable inhabitants of the region. In addition, future sea-level rise, population growth, and poorly planned development will increase the risk of storm-surge flooding, especially for vulnerable people, thus suggesting that planning should steer development away from low-lying coastal and near-coastal zones.     

Advances in surrogate modeling for storm surge prediction: storm selection and addressing characteristics related to climate change

This paper establishes various advancements for the application of surrogate modeling techniques for storm surge prediction utilizing an existing database of high-fidelity, synthetic storms (tropical cyclones). Kriging, also known as Gaussian process regression, is specifically chosen as the surrogate model in this study. Emphasis is first placed on the storm selection for developing the database of synthetic storms. An adaptive, sequential selection is examined here that iteratively identifies the storm (or multiple storms) that is expected to provide the greatest enhancement of the prediction accuracy when that storm is added into the already available database. Appropriate error statistics are discussed for assessing convergence of this iterative selection, and its performance is compared to the joint probability method with optimal sampling, utilizing the required number of synthetic storms to achieve the same level of accuracy as comparison metric. The impact on risk estimation is also examined. The discussion then moves to adjustments of the surrogate modeling framework to support two implementation issues that might become more relevant due to climate change considerations: future storm intensification and sea level rise (SLR). For storm intensification, the use of the surrogate model for prediction extrapolation is examined. Tuning of the surrogate model characteristics using cross-validation techniques and modification of the tuning to prioritize storms with specific characteristics are proposed, whereas an augmentation of the database with new/additional storms is also considered. With respect to SLR, the recently developed database for the US Army Corps of Engineers’ North Atlantic Comprehensive Coastal Study is exploited to demonstrate how surrogate modeling can support predictions that include SLR considerations.     

On the use of NOAA's storm surge model,SLOSH, in managing coastal hazards — the experience in Puerto Rico

A numerical-dynamic, tropical storm surge model, SLOSH (Sea, Land, and Overland Surges from Hurricanes), was originally developed for real-time forecasting of hurricane storm surges on continental shelves, across inland water bodies and along coastlines and for inland routing of water -either from the sea or from inland water bodies. The model is two-dimensional, covering water bodies and inundated terrain. In the present version available at the University of Puerto Rico a curvilinear, polar coordinate grid scheme is used. The grid cells are approximately 3.2 × 3.2 km in size.The model has been used in a revision of all coastal Flood Insurance Rate Maps (FIRM) for Puerto Rico and the U.S. Virgin Islands, and in hurricane evacuation studies. The FIRM's, since they are based on the 100 year stillwater elevation, are also used by the state Planning Board for regulatory purposes. The hurricane evacuation studies are used by emergency planners and personnel to assign shelters, escape routes, and delimit coastal zones that need to be evacuated during a hurricane threat.Recently, the acquisition of data from hurricane Hugo has allowed the first comparison of model results and observations for Puerto Rico and the other islands.