Storm Surge Hazard Research Articles

Storm surge hazard over Bengal delta: a probabilistic–deterministic modelling approach

Abstract. Storm-surge-induced coastal inundation constitutes a substantial threat to lives and properties along the vast coastline of the Bengal delta. Some of the deadliest cyclones in history made landfall in the Bengal delta region claiming more than half a million lives over the last five decades. Complex hydrodynamics and observational constraints have hindered the understanding of the risk of storm surge flooding of this low-lying (less than 5 m above mean sea level), densely populated (> 150 million) mega-delta. Here, we generated and analysed a storm surge database derived from a large ensemble of 3600 statistically and physically consistent synthetic storm events and a high-resolution storm surge modelling system. The storm surge modelling system is developed based on a custom high-accuracy regional bathymetry enabling us to estimate the surges with high confidence. From the storm surge dataset, we performed a robust probabilistic estimate of the storm surge extremes. Our ensemble estimate shows that there is a diverse range of water level extremes along the coast and the estuaries of the Bengal delta, with well-defined regional patterns. We confirm that the risk of inland storm surge flooding at a given return period is firmly controlled by the presence of coastal embankments and their height. We also conclude that about 10 % of the coastal population is living under the exposure of a 50-year return period inundation under current climate scenarios. In the face of ongoing climate change, which is likely to worsen the future storm surge hazard, we expect our flood maps to provide relevant information for coastal infrastructure engineering, risk zoning, resource allocation, and future research planning.

Controls on coastal flooding in the southern Baltic Sea revealed from the late Holocene sedimentary records

Climate change and related sea-level rise pose significant threats to lowland coasts. However, the role of key controlling factors responsible for the frequency and landward extent of extreme storm surges is not yet fully understood. Here, we present a high-resolution sedimentary record of extreme storm surge flooding from the non-tidal southern Baltic Sea, spanning two periods: 3.6–2.9 ka BP and 0.7 ka BP until present. Sediments from coastal wetland, including sandy event layers, were analyzed by sedimentological (grain size, loss-on-ignition, micromorphology), geochronological (14C), geochemical (XRF), mineralogical (heavy minerals) and micropaleontological (diatoms) methods. The results show that both periods were characterized by high-frequency of storm surge flooding, in order of 1.3–4.2 events per century. These periods correlate with phases of enhanced storminess in northwest Europe and took place during both rising and fluctuating sea levels. The study shows that the frequency and landward extent of coastal inundation, largely depended on the development of natural barriers (e.g. beach ridges and aeolian foredunes). Thus, in the context of the future coastal storm-surge hazard, the protection of existing coastal barriers and their morphology is essential.

Artificial intelligence for hurricane storm surge hazard assessment

Risk-informed coastal management requires assessment of extreme flood hazards from a large number of storm scenarios. To account for impact of climate change based on potential variations in greenhouse gas concentration and climate models, the number of storm scenarios would be even larger. Although physics-based hydrodynamic numerical models could predict flood levels and their impact from storm scenarios, the high computational cost of the solutions hinders the ability to perform the required number of simulations. Towards alleviating that cost, we show that physics-based simulations can be combined with Artificial Neural Network models to support more faster and effective prediction of low-probability events that account for uncertainties associated with climate change. We show this capability by predicting 10, 100, and 1,000 years return periods for peak storm surge height at a specific location on an idealized coastline. A large data set of synthetic tropical cyclones is generated from physics-based simulations and used for training, validating and testing the constructed neural network model. The ANN predicted values are validated against values from the physics-based simulations. The advantage of the combined approach is that, once the training was complete, it was performed in a fraction of the time required for the physics-based simulations.

Future changes in typhoons and storm surges along the Pacific coast in Japan: proposal of an empirical pseudo-global-warming downscaling

ABSTRACT In this study, dynamical pseudo-global-warming downscaling (d-PGWD) was performed with a high-resolution typhoon model for 49 typhoons that made landfall in Japan between 2000 and 2017. It was revealed that the averaged typhoon intensity under future climatic conditions tends to increase at both the peak and landfall times as a result of global warming (averaged central pressures of −45.7 and −5.5 hPa at peak and landfall, respectively). Furthermore, detailed analyses of the time of landfall revealed significant differences in the degree of future changes in typhoon intensity based on both the elapsed time from the genesis to landfall (Tl ) and the radius of maximum wind speed (Rml ) at the time of landfall. Considering the relationships of Tl and Rml between present and future climates, statistical formulas for future changes in the central pressure and Rml were derived as an empirical PGWD (e-PGWD) method. The validity of this method was confirmed via comparison with d-PGWD results. It is expected that disaster prevention and mitigation measures for future typhoons and coastal disasters in individual regions and ports can be developed by revising storm surge hazard maps using the proposed e-PGWD approach.

Tropical Cyclones Affecting Japan Central Coast and Changing Storm Surge Hazard since 1980

Tropical Cyclones Affecting Japan Central Coast and Changing Storm Surge Hazard since 1980

Large-scale cloud-based building elevation data extraction and flood insurance estimation to support floodplain management

Factors that often make coastal areas prone to high-cost flood damage include its low-lying topography, tropical and subtropical climates, miles of coastline exposed to hurricane and storm surge hazards, and older housing stock. In this study, we sought to develop a platform that can be used by various stakeholders to re-evaluate and reframe community risk through the use of mobile LiDAR technology to create a current 3D digital elevation model of all homes, businesses, and infrastructure in shoreline communities within the current 100-year floodplain in one county in New Jersey. An innovative strategy for extracting property elevation information from mobile LiDAR and mobile imagery was developed utilizing a web-based approach. Unlike traditional elevation extraction approaches that require field surveys, the proposed method does not require an onsite inspection from certified surveyors, which is often computationally expensive but the key method to current elevation certificate generation. Thus, the proposed approach makes it possible to obtain accurate structure elevation and realize the elevation extraction for large-scale community areas. Results indicate that overall, 96.5% of building diagrams identified with our method have the same value as the original elevation certificate documents. For the estimation of elevation certificate C2a elevation, the estimated error is between 0.082 ft (0.025 m) and 0.104 ft (0.032 m) at the 95% confidence level. Similarly, the C2b elevation had an estimated error between 0.133 ft (0.040 m) and 0.136 ft (0.041 m) at the 95% confidence level.

Effectiveness of selected planned adaptations in micro level: Evidence from coastal community in Bangladesh

A community level field survey is conducted in the coastal zone of Bangladesh to assess the effectiveness of five selected planned adaptations against storm surge in micro scale which are already proved effective in macro scale. The five selected planned adaptations are: cyclone shelter, plantation, paka & semi-paka house, loan, and communication infrastructure. The selected study area is well-known for storm surge hazard. The study site and sample size are selected by using Probability Proportional to Size (PPS) and cluster sampling methods. Semi-structured household questionnaire, Focus Group Discussion (FGD), and Key Informative Interviews (KII) were conducted for understanding community perceptions on adaptations. Effectiveness of planned adaptations are assessed by applying an Index developed by using five-point Likert scale. Barriers against the adaptations are assessed by probabilistic analysis and represented by Venn diagram. Interrelationships among the adaptations are assessed through causal relation network. The study results show a mismatch of effectiveness of planned adaptations between the macro scale and micro scale. It is found that cyclone shelter, paka & semi-paka house, loan, and communication infrastructure do not exhibit a similar level of effectiveness in micro scale as these are expected to be effective in macro scale. Among the five selected planned adaptations, plantation is the only adaption which is found to be effective in both micro scale and macro scale because of its high economic return for the community. The reasons for the mismatch of this effectiveness between macro scale and micro scale are – barriers and causal relation for these adaptations in micro scale are not considered in macro scale. A comprehensive analysis is recommended to ensure a similar level of effectiveness of an adaptation both in macro scale and in micro scale.

A new tropical cyclone surge index incorporating the effects of coastal geometry, bathymetry and storm information

This study presents a new storm surge hazard potential index (SSHPI) for estimating tropical cyclone (TC) induced peak surge levels at a coast. The SSHPI incorporates parameters that are often readily available at real-time: intensity in 10-min maximum wind speed, radius of 50-kt wind, translation speed, coastal geometry, and bathymetry information. The inclusion of translation speed and coastal geometry information lead to improvements of the SSHPI to other existing surge indices. A retrospective analysis of SSHPI using data from 1978–2019 in Japan suggests that this index captures historical events reasonably well. In particular, it explains ~ 66% of the observed variance and ~ 74% for those induced by TCs whose landfall intensity was larger than 79-kt. The performance of SSHPI is not sensitive to the type of coastal geometry (open coasts or semi-enclosed bays). Such a prediction methodology can decrease numerical computation requirements, improve public awareness of surge hazards, and may also be useful for communicating surge risk.

Probabilistic storm surge hazard using a steady-state surge model for the Pearl River Delta Region, China

Storm surges caused by tropical cyclones (TCs) are one of the costliest threats to coastal communities in southern China. Numerical surge models remain computationally challenging when used to simulate the large number of TC events required for probabilistic hazard assessments at regional scale. The present study demonstrates the applicability of a simple 1D steady-state storm surge representation for such regional scale hazard assessment. The surge setups from wind shear stress and barometric pressure difference are calculated with the meteorological forcing derived from parametric wind models and TC track information. Being computationally efficient, the surge model results do not require further empirical coefficients derived from correlation against observed data as compared to the previous statistical and semi-empirical surge estimations. Using the Pearl River Delta (PRD) region in China as a case study, the root-mean-square errors between the estimated and reported peak storm surges along the PRD coastline are 0.37 m and 0.45 m using two different TC best track inputs, respectively, covering 118 observed surge records from 39 historical TC events. Probabilistic surge hazard maps are further developed for the PRD coastline using the two TC best track datasets covering 1951–2018 as inputs. The mean surge heights along the coastline are in the range of 1.5–3.2 m and 2.0–3.5 m under 100-year and 200-year return periods, respectively. Areas in the west and near the estuary outlet are more prone to higher surge levels due to more frequent TCs affecting the areas historically. Differences in TC characteristics exist between the two best track datasets, which gives rise to localised difference in surge heights along the PRD coastline. The maximum differences in the 100-year and 200-year return period surge levels from the two best track datasets are 0.51 m and 0.64 m, respectively.

The lasting impacts of the Saffir-Simpson Hurricane Wind Scale on storm surge risk communication: The need for multidisciplinary research in addressing a multidisciplinary challenge

Historically, storm surge risk was indicated alongside the Saffir-Simpson Hurricane Wind Scale (SSHWS), and a lasting association remains among the general public. In recent years, the National Hurricane Center (NHC) has continually developed their advisories and products to explicitly communicate the storm surge hazard. In this study, we examine these developments to understand its impact on risk perception and discuss that though not explicitly, underlying associations to the SSHWS remain. We also find that despite the messaging produced through official storm surge guidance, the SSHWS continues to influence public perception and response. Our findings suggest that while improvements in storm surge messaging can improve risk communication and perception and ultimately save lives, it only addresses one component of the multidisciplinary system that defines storm surge risk. Truly effective resilience efforts will require comprehensive, multidisciplinary approaches.

Simulating major storm surge events in a complex coastal region

Climate change and increased coastal urbanization are causing low-lying coastlines to become increasingly susceptible to the threat of extreme water levels and coastal flooding. Robust decision-making on adaptation in the coastal zone, based on reliable ocean-modelling tools, is therefore crucially contingent on accurate assessments of current and future storm surge hazards. This accuracy relies considerably on the quality of the wind forcing used in the ocean models. In this paper, we use a high-resolution, regional 3D ocean model (HBM) covering the North Sea and Baltic Sea to simulate extreme water levels during three extreme storm surge events with different dynamics and patterns, in order to assess their impacts along Denmark’s coastlines, which are of varying levels of complexity. We demonstrate that the model is able to reproduce the observed extreme high-water levels accurately, indicating that the system is well suited for producing simulations of present and future projections of extreme storm surges with high resulting impacts and damage potentials. Additionally, we quantify the level at which acknowledged deficiencies in the otherwise most suitable atmospheric forcing data set influence the results of the storm surge simulations. We found that reducing the temporal resolution of the forcing data – that is, replacing two out of every six time stamps with linearly interpolated values – is preferable to using the original forcing data set when recurring noise is present in these time stamps. As a result, for given storm surge events, and depending on the stage reached in the storm’s evolution, mean absolute errors can be reduced by 4.5cm. This emphasizes the importance of considering such model fluctuations when coupling high-resolution atmosphere and ocean models.

Quantitative risk assessment of storm surge using GIS techniques and open data: A case study of Daya Bay Zone, China

Storm surge is a natural disaster, often causing economic damage and loss of human life in the coastal communities. In recent decades, with more people attracted to coastal areas, the potential economic losses resulted from storm surges are increasing. Therefore, it is important to make risk assessments to identify areas at risk and design risk reduction strategies. However, the quantitative risk assessment of storm surge for coastal cities in China is often difficult due to the lack of adequate data regarding the building footprint and vulnerability curves. This paper aims to provide a methodology for conducting the quantitative risk assessment of storm surge, estimating direct tangible damage, by using Geographical Information System (GIS) techniques and open data. The proposed methodology was applied to a coastal area with a high concentration of petroleum industries in the Daya Bay zone. At first, five individual typhoon scenarios with different return periods (1000, 100, 50, 20, and 10 years) were defined. Then, the Advanced Circulation model and the Simulating Waves Nearshore model were utilized to simulate storm surge. The model outputs were imported into GIS software, transformed into inundation area and inundation depth. Subsequently, the building footprint data were extracted by the use of GIS techniques, including spatial analysis and image analysis. The layer containing building footprints was superimposed on the inundation area layer to identify and quantify the exposed elements to storm surge hazard. Combining the exposed elements with their related depth–damage functions, the quantitative risk assessment translates the spatial extent and depth of storm surge into the estimation of economic losses. The quantitative risk assessment and zonation maps for sub-zones in the study area can help local decision-makers to prioritize the sub-zones that are more likely to be affected by storm surge, make risk mitigation strategies, and develop long-term urban plans.

Developing Vulnerability Index for the Coastal Storm Surge Hazards Considering Climate Change

Developing Vulnerability Index for the Coastal Storm Surge Hazards Considering Climate Change

Numerical Analysis of Storm Surges on Canada’s Western Arctic Coastline

A numerical study was conducted to characterize the probability and intensity of storm surge hazards in Canada’s western Arctic. The utility of the European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation (ERA5) dataset to force numerical simulations of storm surges was explored. Fifty historical storm surge events that were captured on a tide gauge near Tuktoyaktuk, Northwest Territories, were simulated using a two-dimensional (depth-averaged) hydrodynamic model accounting for the influence of sea ice on air-sea momentum transfer. The extent of sea ice and the duration of the ice season has been reducing in the Arctic region, which may contribute to increasing risk from storm surge-driven hazards. Comparisons between winter storm events under present-day ice concentrations and future open-water scenarios revealed that the decline in ice cover has potential to result in storm surges that are up to three times higher. The numerical model was also used to hindcast a significant surge event that was not recorded by the tide gauge, but for which driftwood lines along the coast provided insights to the high-water marks. Compared to measurements at proximate meteorological stations, the ERA5 reanalysis dataset provided reasonable estimates of atmospheric pressure but did not accurately capture peak wind speeds during storm surge events. By adjusting the wind drag coefficients to compensate, reasonably accurate predictions of storm surges were attained for most of the simulated events. The extreme value probability distributions (i.e., return periods and values) of the storm surges were significantly altered when events absent from the tide gauge record were included in the frequency analysis, demonstrating the value of non-conventional data sources, such as driftwood line surveys, in supporting coastal hazard assessments in remote regions.

Risk assessment for typhoon-induced storm surges in Wenchang, Hainan Island of China

A risk assessment for storm surge disasters can provide scientific support for coastal management as well as marine disaster prevention and mitigation. By taking the Wenchang City of Hainan Province as a pilot area, a risk assessment approach for typhoon-induced storm surge disasters is introduced in detail in this article. First, a numerical simulation system for storm surge inundation is developed, which is applied for the simulation and calculation of the probable maximum storm surge in Wenchang, and the obtained inundation areas and depths are used to assess the storm surge hazard. Then, the data of land use and disaster-bearing bodies are used to classify and assess the vulnerability of Wenchang. Finally, by taking the community as unit, the risk assessment for typhoon-induced storm surge affecting Wenchang is performed by combining the assessment results of both hazard and vulnerability, thereby obtaining a level map of risk distribution. The results show that there are risks of typhoon-induced storm surge in most of the coastal areas of Wenchang, especially for its northeast and east coastal areas, where the risks reach Levels I–II. This approach can be conveniently applied to risk assessments of storm surge in other coastal areas. Note that this approach focuses on the current risk of typhoon-induced storm surge in coastal areas, and further studies will be conducted on the assessment methods for the potential risk.

A COMPREHENSIVE EVALUATION OF FLOOD HAZARDS FOR SABINE TO GALVESTON, TX, USA REGION

The Sabine Pass to Galveston Bay, TX Pre-Construction, Engineering and Design: Hurricane Coastal Storm Surge and Wave Hazard Assessment (S2G) includes flood hazard assessment for over 100 km of levee/floodwall/gate coastal storm risk management systems. The focus of the flood hazard assessment was to compute coupled water level and wave response near the structures, runup, and overtopping rate, combined hydrostatic and hydrodynamic pressure distributions on walls, overtopping nappe characteristics and other pertinent responses stochastically. Joint statistical analysis of forcing parameters, including epistemic uncertainty, was conducted to compute hazards. Design was based on varied confidence levels and thus reflected uncertainty. The approach brought high-fidelity components together to produce accurate probabilistic coastal flood hazard assessment.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/U_dFfj2oJ2A

IMPROVED COASTAL FLOOD RISK ESTIMATES THROUGH INTEGRATED JPM AND COUPLED PHYSICS APPROACH

Large scale flood risk computation has enjoyed a metamorphosis since Hurricane Katrina. Improved characterization of risk is the result of improved computational capabilities due to super computer capacity combined with coupled regional hydrodynamic models, improved local hydrodynamic models, improved joint probability models, inclusion of the most important uncertainties, metamodels and increased computational capacity for stochastic simulation. Improvements in our understanding of, and the ability to model, the coupled hydrodynamics of surge and waves has been well documented as has been improvements in the joint probability method with optimal sampling (JPM-OS) for synthesizing synthetic tropical cyclones (TC) that correctly span the practical hazard probability space. However, maintaining the coupled physics and multivariate probability integrity through the entire flood risk computation while incorporating epistemic uncertainty has had relatively little attention. This paper addresses this latter topic within the context of the Sabine Pass to Galveston Bay, TX Pre-Construction, Engineering and Design, Hurricane Coastal Storm Surge and Wave Hazard Assessment.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/qYFTO6l7UME

Analysis of storm surge characteristics based on stochastic process

Most of the offshore projects will be impacted by storm surge, especially in the sea area where typhoons are frequent, and storm surge disasters are inevitable. The establishment of a theoretical distribution model of the number of typhoon occurrences and random waves is of great theoretical and practical significance for the study of the number of storm surge impacts and damage to marine engineering as well as the safety evaluation of offshore engineering. Based on stochastic process theory, this paper discusses the effects of the number of typhoon occurrences and typhoon intensity on wave displacement and water level by constructing a compound Poisson process model of typhoon frequency and typhoon intensity. The limitations of using typhoon intensity and wave height as random variables in the marine environment are improved. The average cumulative damage, reliability, and average service life of marine works were analyzed by marine works reliability analysis and a compound Poisson process of the number of storm surge impacts on marine works and the damage caused to marine works by each impact. The results show that the statistical theoretical model and reliability analysis of the storm surge hazard factors based on the stochastic process covers the original extreme value statistical distribution model, and can determine the parameters in the model according to different thresholds in line with the objective facts, and then deduce the design return level, while the deduced return level still has a certain degree of reliability in the case of short or missing data. Therefore, the stochastic process-based model of the imputed level of design parameters for the marine environment provides a new option for marine engineering design and risk management.

Storm Surge Hazard Assessment of the Levee of a Rapidly Developing City-Based on LiDAR and Numerical Models

Rapidly developing cities could require an urgent hazard assessment to ensure the protection of their economy and population against natural disasters. However, these cities that have rapidly developed should have historical records of observations that are too short to provide sufficient data information for such an assessment. This study used ocean numerical models (i.e., Finite-Volume Community Ocean Model (FVCOM) and Parabolic Mild-Slope Wave Module (MIKE 21 PMS) to reconstruct data for a storm surge hazard assessment of the levee at Weifang (China). LiDAR (Light Detection and Ranging) data were also used to obtain 3D point cloud data and the structure of the levee. The designed levee height was calculated based on the simulations and 3D point cloud data, and the results were compared with measured heights to evaluate whether the levee is sufficiently high to satisfy the safety requirement. The findings of this work will enhance the marine disaster prevention capacity of the region and could help reduce economic losses associated with marine-related disasters. The results could also provide support for future work on disaster prevention in the field of coastal marine engineering.

Risk-based determination of polder height against storm surge Hazard in the south-west coastal area of Bangladesh

Bangladesh was introduced with the polder system during 1960s to secure agricultural production from salinity intrusion. Existing polder design practice follows traditional return-period based approach. The article introduces a risk-based framework to determine optimal polder level in the coastal area of Bangladesh. Distinguishable features of risk-based framework over previous method is its inclusion of risk cost and optimal project size. Storm surge flooding was considered as the hazard intensity in this study. Agricultural losses due to storm surge flooding were factorized to get total losses. The optimum level of the polder was determined by summing up the annualized costs of raising polder and the risk cost due to storm surge flooding. The optimal polder level was found to be about 5.63 mPWD with a return period of about 37 years. The optimum design return-period for the polder in Bangladesh is considerably low compared to the current global design practices. This underscores the local peculiarities of the area (e.g., land use, economic activities, hazard sensitivity) in balancing incremental investment costs with reduced risk costs in a risk-based concept. The demonstration of the risk-based concept that is made for designing a coastal polder has potential for replication in other infrastructure designs.