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.     

Mapping joint hurricane wind and surge hazards for Charleston,South Carolina

Combined effects of hurricane wind and surge can pose significant threats to coastal cities. Although current design codes consider the joint occurrence of wind and surge, information on site-specific joint distributions of hurricane wind and surge along the US Coast is still sparse and limited. In this study, joint hazard maps for combined hurricane wind and surge for Charleston, South Carolina (SC), were developed. A stochastic Markov chain hurricane simulation program was utilized to generate 50,000 years of full-track hurricane events. The surface wind speeds and surge heights from individual hurricanes were computed using the Georgiou’s wind field model and the Sea, Lake and Overland Surges from Hurricanes (SLOSH) model, respectively. To validate the accuracy of the SLOSH model, the simulated surge levels were compared to the surge levels calculated by another state-of-the-art storm surge model, ADCIRC (Advanced Circulation), and the actual observed water elevations from historical hurricane events. Good agreements were found between the simulated and observed water elevations. The model surface wind speeds were also compared with the design wind speeds in ASCE 7-10 and were found to agree well with the design values. Using the peak wind speeds and maximum surge heights, the joint hazard surfaces and the joint hazard maps for Charleston, SC, were developed. As part of this study, an interactive computer program, which can be used to obtain the joint wind speed and surge height distributions for any location in terms of latitude and longitude in Charleston area, was created. These joint hazard surfaces and hazard maps can be used in a multi-hazard design or risk assessment framework to consider the combined effects of hurricane wind and surge.     

Dynamics of an outburst flood originating from a small and high-altitude glacier in the Arid Andes of Chile

The rise of total water levels at the coast is caused primarily by three factors that encompass storm surges, tides and wind waves. The accuracy of total water elevation (TWE) forecast depends not only on the cyclonic track and its intensity, but also on the spatial distribution of winds which include its speed and direction. In the present study, the cyclonic winds are validated using buoy winds for the recent cyclones formed in the Bay of Bengal since 2010 using Jelesnianski wind scheme. It is found that the cyclonic winds computed from the scheme show an underestimate in the magnitude and also a mismatch in its direction. Hence, the wind scheme is suitably modified based on the buoy observations available at different locations using a power law which reduces the exponential decay of winds by about 30%. Moreover, the cyclonic wind direction is also corrected by suitably modifying its inflow angle. The significance of modified exponential factor and inflow angle in the computation cyclonic winds is highlighted using statistical analysis. A hydrodynamic finite element-based Advanced Circulation 2D depth integrated (ADCIRC-2DDI) model is used here to compute TWE as a response to combined effect of cyclonic winds and astronomical tides. As contribution of wave setup plays an important role near the coast, a coupled ADCIRC + SWAN is used to perceive the contribution of wind waves on the TWE. The experiments are performed to validate computed surge residuals with available tide gauge data. On comparison of observed surge residuals with the simulations using modified winds from the uncoupled and coupled models, it is found that the simulated surge residuals are better compared, especially with the inclusion of wave effect through the coupled model.     

Impact of cyclonic wind field on interaction of surge–wave computations using finite-element and finite-difference models

Both finite-element and finite-difference numerical models are applied to simulate storm surges and associated currents generated by tropical cyclones that struck the coast of Andhra Pradesh, located on the east coast of India. During a cyclone, the total water level at any location on the coast is made up of the storm surge, surge–wind wave interaction and the tide. The advanced circulation two-dimensional depth-integrated (ADCIRC-2DDI) model based on finite-element formulation and the two-dimensional finite-difference model of storm surges developed at IIT Delhi, hereafter referred as IITD storm surge model, are used. These models are driven by astronomical tides at the open ocean boundary and cyclonic asymmetric winds over the surface of the computational domain. Comparison of model simulated sea-surface elevations with coarse and finer spatial resolutions suggests that the grid resolution near the coast is very crucial for accurate determination of the surges in addition to the local bathymetry. The model underpredicts surges, and the peak surge location shifts more to the right of the landfall as the spatial resolution of the model becomes coarser. The numerical experiments also demonstrate that the ADCIRC model is robust over the IITD storm surge model for surge computations as the coastline is better represented in the former.     

Consistency in hurricane surface wind forecasting: an improved parametric model

A parametric hurricane wind model has been developed based on the asymmetric Holland-type vortex model. The model creates a two-dimensional surface wind field based on the National Hurricane Center forecast (or observed) hurricane wind and track data. Three improvements have been made to retain consistency between the input parameters and the model output and to better resolve the asymmetric structure of the hurricane. First, in determination of the shape parameter B, the Coriolis effect is included and the range restriction is removed. It is found that ignoring the Coriolis effect can lead to an error greater than 20% in the maximum wind speed for weak but large tropical cyclones. Second, the effect of the translational velocity of a hurricane is excluded from the input of specified wind speeds before applying the Holland-type vortex to avoid exaggeration of the wind asymmetry. The translational velocity is added back in at the very end of the procedure. Third, a new method has been introduced to develop a weighted composite wind field that makes full use of all wind parameters, not just the largest available specified wind speed and its 4-quadrant radii. An idealized hurricane and two historical Gulf of Mexico hurricanes have been used to test the model. It is found that the modified parametric model leads to better agreement with field observation compared with the results from the unmodified model. This will result in better predictions of hurricane waves and storm surges.     

Application of a fast stochastic storm surge model on estimating the high water level frequency in the Lower Rhine Delta

In the Lower Rhine Delta of the Netherlands, the high water level is driven by a joint impact of the downstream storm surge and the upstream fluvial discharge, and affected by the operation of existing man-made structures. In scenario-based risk assessment, a large number of stochastic scenarios of storm surges are required for estimating the high water level frequency. In this article, a fast computing stochastic storm surge model is applied to the gauge station of Hook of Holland in the west of the Netherlands. A fixed number of tides are considered in this model based on the information of historical storm surge events. Based on this model, a large number of stochastic storm surge scenarios are derived and forced into a one-dimensional hydrodynamic model of the Netherlands, resulting in peak water levels in Rotterdam, the most vulnerable city in the delta. These peak water levels are statistically analyzed and converted to the high water level frequency curve in Rotterdam. The high water level frequency curve in Rotterdam tends to a much lower design water level compared to the official design water level that is used to design the dikes and structures for protection of the city. Moreover, there is a significant difference in the high water level frequency curves due to the fact that the stochastic storm surge model considers different numbers of tides. This highlights the critical impact of the storm surge duration on the high water level frequency in the Lower Rhine Delta.     

On the influence of changes in the drag relation on surface wind speeds and storm surge forecasts

In this study it is investigated how uncertainties in the magnitude of the drag coefficient translate into uncertainties in storm surge forecasts in the case of severe weather. A storm surge model is used with wind stress data from a numerical weather prediction (NWP) model, to simulate several recent storms over the North Sea. For a fixed wind speed, the wind stress is linear in the drag coefficient. However, in the NWP model the wind speed is not fixed and increasing the drag in the NWP model results into reduced wind speeds. The results from simulations show that for given increase in the drag coefficient, the weakening of the 10-m wind field reduces the increase in the stress considerably. When the Charnock parameter is increased in the NWP model, the resulting relative changes in the wind stress are almost independent of the wind speed. This is related to the fact that the depth of the surface boundary layer depends on the wind speed. The ratio between relative changes in the wind stress and relative changes in the drag coefficient depends on the wind speed. For 10-m wind speeds larger than 20?m?s^?1 the ratio is 0.52; for lower wind speed criteria the ratio is somewhat larger (??0.60). Approximately 36% of the relative change in the drag coefficient translates into a relative change in the surge in stations at the Dutch coast. The relative increase in the storm surge is approximately 68% of the relative increase in the stress.     

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.     

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.     

Simulation of atmospheric states for a storm surge on the west coast of Korea: model comparison between MM5, WRF and COAMPS

High-quality informations on sea level pressure and sea surface wind stress are required to accurately predict storm surges over the Korean Peninsula. The storm surge on 31 March 2007 at Yeonggwang, on the western coast, was an abrupt response to mesocyclone development. In the present study, we attempted to obtain reliable surface winds and sea level pressures. Using an optimal physical parameterization for wind conditions, MM5, WRF and COAMPS were used to simulate the atmospheric states that accompanied the storm surge. The use of MM5, WRF and COAMPS simulations indicated the development of high winds in the strong pressure gradient due to an anticyclone and a mesocyclone in the southern part of the western coast. The response to this situation to the storm surge was sensitive. A low-level warm advection was examined as a possible causal mechanism for the development of a mesocyclone in the generating storm surge. The low-level warm temperature advection was simulated using the three models, but MM5 and WRF tended to underestimate the warm tongue and overestimate the wind speed. The WRF simulation was closer to the observed data than the other simulations in terms of wind speed and the intensity of the mesocyclone. It can be concluded that the magnitude of the storm surge at Yeonggwang was dependent, not only on the development of a mesocyclone but on ocean effects as well.     

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.

     

Hydrodynamic Response of Northeastern Gulf of Mexico to Hurricanes

The northeastern Gulf of Mexico in the USA is extremely susceptible to the impacts of tropical cyclones because of its unique geometric and topographic features. Focusing on Hurricanes Ivan (2004) and Katrina (2005), this paper has addressed four scientific questions on this area’s response to hurricanes: (1) How does the shallow, abandoned Mississippi delta contribute to the storm surge? (2) What was the controlling factor that caused the record-high storm surge of Hurricane Katrina? (3) Why are the responses of an estuary to Hurricanes Ivan and Katrina so different from the corresponding surges on the open coast? (4) How would the storm surge differ if Hurricane Katrina had taken a different course? Guided by field observations of winds, waves, water levels, and currents, two state-of-the-art numerical models for storm surges and wind waves have been coupled to hindcast the relevant hydrodynamic conditions, including storm surges, surface waves, and depth-averaged currents. Fairly good agreement between the modeled and measured surge hydrographs was found. The quantitative numerical simulations and simple qualitative analysis have revealed that the record-high storm surge of Hurricane Katrina was caused by the interaction of the surge with the extremely shallow, ancient deltaic lobe of Mississippi River. A hypothetical scenario formed by shifting the path of Hurricane Katrina to the observed path of Hurricane Frederic (1979) resulted in a much smaller surge than that observed in coastal Mississippi and Louisiana. However, this scenario did still result in a high surge near the head of Mobile Bay. One of the important lessons learned from Hurricane Katrina is that the Saffir–Simpson scale should be systematically revised to reflect the topographic and geometric features of a complex, heterogeneous coast, including the possible surge amplification in an estuary or a submerged river delta.     

Effects of Hurricane Ivan on water quality in Pensacola Bay, Florida

Pensacola Bay, Florida, was in the strong northeast quadrant of Hurricane Ivan when it made landfall on September 16, 2004 as a category 3 hurricane on the Saffir-Simpson scale. We present data describing the timeline and maximum height of the storm surge, the extent of flooding of coastal land, and the magnitude of the freshwater inflow pulse that followed the storm. We computed the magnitude of tidal flushing associated with the surge using a tidal prism model. We also evaluated hurricane effects on water quality using water quality surveys conducted 20 and 50 d after the storm, which we compared with a survey 14 d before landfall. We evaluated the scale of hurricane effects relative to normal variability using a 5-yr monthly record. Ivan's 3.5 m storm surge inundated 165 km² of land, increasing the surface area of Pensacola Bay by 50% and its volume by 230%. The model suggests that 60% of the Bay's volume was flushed, initially increasing the average salinity of Bay waters from 23 to 30 and lowering nutrient and chlorophylla concentrations. Additional computations suggest that wind forcing was sufficient to completely mix the water column during the storm. Freshwater discharge from the largest river increased twentyfold during the subsequent 4 d, stimulating a modest phytoplankton bloom (chlorophyll up to 18 μg l⁻¹) and maintaining hypoxia for several months. Although the immediate physical perturbation was extreme, the water quality effects that persisted beyond the first several days were within the normal range of variability for this system. In terms of water quality and phytoplankton productivity effects, this ecosystem appears to be quite resilient in the face of a severe hurricane effect.     

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.     

Coastal flooding: impacts of coupled wave–surge–tide models

Wind waves and elevated water levels together can cause flooding in low-lying coastal areas, where the water level may be a combination of mean sea level, tides and surges generated by storm events. In areas with a wide continental shelf a travelling external surge may combine with the locally generated surge and waves and there can be significant interaction between the propagation of the tide and surge. Wave height at the coast is controlled largely by water depth. So the effect of tides and surges on waves must also be considered, while waves contribute to the total water level by means of wave setup through radiation stress. These processes are well understood and accurately predicted by models, assuming good bathymetry and wind forcing is available. Other interactions between surges and waves include the processes of surface wind-stress and bottom friction as well as depth and current refraction of waves by surge water levels and currents, and some of the details of these processes are still not well understood. The recent coastal flooding in Myanmar (May 2008) in the Irrawaddy River Delta is an example of the severity of such events, with a surge of over 3 m exacerbated by heavy precipitation. Here, we review the existing capability for combined modelling of tides, surges and waves, their interactions and the development of coupled models.     

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).     

台风风暴潮影响下潮滩沉积动力模拟初探--以江苏如东海岸为例

以江苏如东潮滩为研究区,采用沉积动力学垂向二维概念模型来模拟正常天气和台风期间潮滩沉积的空间分布特征,探讨台风风暴潮对潮滩正常沉积层序的改造作用.模拟结果表明,在涨落潮时间-流速对称特征明显的如东海岸,潮汐作用使潮滩沉积呈显著的分带性,且剖面形态向“双凸形”演化,两个“凸点”分别位于平均高潮位和平均低潮位附近.在台风期间风暴增水效应下,开边界悬沙浓度差异将导致潮滩冲淤和沉积分布格局的变化,潮上带和潮间带上部均堆积泥质沉积物,潮间带中下部在风暴过程中普遍遭受不同程度的砂质沉积物侵蚀或之后堆积泥质沉积物,在沉积层序中形成风暴冲刷面.因此,潮滩的风暴沉积记录存在于潮间带上部或更高部位.以此模型为基础,可进一步综合考虑极浅水边界层水动力结构、沉积物粒度分布变化、波-流联合作用、台风降水、互花米草等生物活动、潮沟摆动及人工围垦等因素,从而建立风暴事件在沉积层序中的时间序列,更好地解译沉积记录中的古环境信息.     

Numerical simulation of storm surges in Lake Winnipeg

A high-resolution unstructured grid two-dimensional finite-element model was applied to simulate the storm surge associated with the October 2010 extratropical storm in Lake Winnipeg. The wind and pressure fields from two high-resolution weather forecast models were used to drive the hydrodynamic model. The model results were compared with the observed water levels at several stations during the storm event. The model-predicted storm surge in the range of 0.6–1.5 m is comparable with observations in the southern basin of Lake Winnipeg. Model results are further analyzed to assess the transport of water between north and south basins of Lake Winnipeg during the event. Computed water surface elevations at specific locations at the outlet of the rivers and embayments indicate that the model needs some improvements in terms of grid resolution in those areas.     

The impact of a storm surge on business establishments in the Houston MSA

This paper examines the possible storm surge damage from a major hurricane to hit the Houston Metropolitan Statistical Area (MSA.) Using storm surge analysis on a unique data set compiled from the Texas Workforce Commission (QCEW), the paper estimates the expected industry-level damage for each county in the Houston MSA. The advantages of using GIS to analyze the expected storm surge damage estimation is that it provides an accurate estimation of the number of affected employees and probable wages losses, by industry and county, based on QCEW data. The results indicate that the ‘Basic Chemical Manufacturing’ and ‘Oil and Gas Extraction’ industries incur the highest employee and payroll losses while the ‘Restaurants and Eateries’ has the largest establishment damage if a major hurricane were to hit the Houston MSA.     

Nearshore propagation of cyclonic waves

Cyclone-generated surface waves are simulated using state-of-art SWAN (Simulating WAves Nearshore) model coupled with hydrodynamic model inputs. A severe cyclonic storm passed over the Arabian Sea during 4–9th November 1982 is selected from UNISYS track records. The cyclone lasted for nearly 6 days and subsided with a land fall at Gujarat coast, west coast of India. In this study, cyclonic wind fields are generated using a well-established relationship suggested by Jelesnianski and Taylor (1973). The associated water level variations due to storm surge and surge generated currents are simulated using POM (Princeton Ocean Model). The outputs are one-way coupled with the wave model SWAN for simulating wave parameters off Gujarat, north-east basin of Arabian Sea. An extensive literature review is carried out on the progress and methodology adopted for storm wave modelling and analysis. The results presented in this paper reveal the severity of the storm event and would be highly useful for assessing the extreme wave event/climate especially for the south coast of Gujarat.