Storm Surge Risk Research Articles

Third assessment on impacts of climate change on tropical cyclones in the Typhoon Committee Region – Part II: Future projections

This paper assesses published findings on projections of future tropical cyclone (TC) activity in the ESCAP/WMO Typhoon Committee Region under climate change scenarios. This assessment also estimates the projected changes of key TC metrics for a 2 °C anthropogenic global warming scenario for the western North Pacific (WNP) following the approach of a WMO Task Team, together with other reported findings for this region. For projections of TC genesis/frequency, most models suggest a reduction of TC frequency, but an increase in the proportion of very intense TCs over the WNP in the future. However, some individual studies project an increase in WNP TC frequency. Most studies agree on a projected increase of WNP TC intensity over the 21st century. All available projections for TC related precipitation in the WNP indicate an increase in TC related precipitation rate in a warmer climate. Anthropogenic warming may also lead to changes in TC prevailing tracks. A further increase in storm surge risk may result from increases in TC intensity. The most confident aspect of forced anthropogenic change in TC inundation risk derives from the highly confident expectation of further sea level rise, which we expect will exacerbate storm inundation risk in coastal regions, assuming all other factors equal.

Fine-Scale Coastal Storm Surge Disaster Vulnerability and Risk Assessment Model: A Case Study of Laizhou Bay, China

In the assessment of storm surge vulnerability, existing studies have often selected several types of disaster-bearing bodies and assessed their exposure. In reality, however, storm surges impact all types of disaster-bearing bodies in coastal and estuarine areas. Therefore, all types of disaster-bearing bodies exposed to storm surges should be considered when assessing exposure. In addition, geographical factors will also have an impact on the exposure of the affected bodies, and thus need to be fully considered. Hence, we propose a fine-scale coastal storm surge disaster vulnerability and risk assessment model. First, fine-scale land-use data were obtained based on high-resolution remote sensing images. Combined with natural geographic factors, such as the digital elevation model (DEM), slope, and distance to water, the exposure of the disaster-bearing bodies in each geographic unit of the coastal zone was comprehensively determined. A total of five indicators, such as the percentage of females and ratio of fishery products to the gross domestic product (GDP), were then selected to assess sensitivity. In addition, six indicators, including GDP and general public budget expenditure, were selected to assess adaptability. Utilizing the indicators constructed from exposure, sensitivity, and adaptability, a vulnerability assessment was performed in the coastal area of Laizhou Bay, China, which is at high risk from storm surges. Furthermore, the storm surge risk assessment was achieved in combination with storm water statistics. The results revealed that the Kenli District, Changyi City, and the Hanting District have a higher risk of storm surge and require more attention during storm surges. The storm surge vulnerability and risk assessment model proposed in this experiment fully considers the impact of the natural environment on the exposure indicators of the coastal zone’s disaster-bearing bodies, and combines sensitivity, adaptability indicators, and storm water record data to conduct vulnerability and risk assessment. At the same time, the model proposed in this study can also realize multi-scale assessment of storm surge vulnerability and risk based on different scales of socioeconomic statistical data, which has the advantages of flexibility and ease of operation.

Identifying Ecosystem Surface Areas Available for Nature-Based Flood Risk Mitigation in Coastal Cities Around the World

Nature-based risk mitigation is increasingly proposed as a strategy to cope with global changes that increase flood risks in coastal areas. However, loss of coastal ecosystems reduces their mitigating effect on coastal flood risks in many places around the world. Here, we identify global urban hot spots exposed to storm surge flood risks, where conservation of existing coastal ecosystems can contribute to nature-based risk mitigation. We present a global procedure identifying the most likely pathways followed by storm surges from the open sea toward 136 cities around the world and quantifying the extent of mangrove forests, salt marshes, seagrass meadows, and coral reefs along these storm surge pathways. Instead of being locally precise, our procedure aims to be globally applicable, in order to identify cities around the world where ecosystems can have a positive effect on storm surge risk mitigation and where further local-scale, more precise assessments are advised. Our results show that cities that combine large flood-exposed populations (> 400,000 people exposed to 1-in-100-year storm events) and large potential for nature-based risk mitigation (> 200 km2 of coastal ecosystems) are located in large river deltas and estuaries, such as Khulna (Ganges-Brahmaputra delta, Bangladesh), Guayaquil (Guayas delta, Ecuador), Ho Chi Minh City (Mekong delta, Vietnam), and New Orleans (Mississippi Delta, USA). Here, conservation of mangroves and salt marshes plays a key role. Cities with large flood-exposed populations and/or assets, but few ecosystems, are either located directly adjacent to coastlines or where former wetlands have been reclaimed, especially in European and Asian cities. Overall, 75% of the studied cities benefit from flood risk mitigation by present ecosystems and from additional ecosystem services. Hence, our study identifies global urban hot spots where more detailed local studies are advised on the effectiveness of conservation and (re-)creation of coastal ecosystems as a sustainable strategy for nature-based mitigation of increasing coastal flood risks.

Storm surge risk assessment for the insurance system: A case study in Tokyo Bay, Japan

With the renewal of the basic disaster management plan in Japan, the transferring flood risk itself to insurance carriers is promoted by the Japanese government. An insurance company to which flood risks are transferred must assess infrequent flood risks to manage the overall risk of the company. Insurance systems may reach peak risk condition when a high wind coincides with a high storm surge level. However, there are few studies on the assessment of storm surges using stochastic approaches for Japan. This study suggests the procedure of stochastic storm surge risk assessment with low calculation load and applies it to the Tokyo Bay coast in Japan, a region exposed to large storm surges.Risk mapping and economic losses on the Tokyo Bay coast due to extreme flooding caused by storm surges are predicted for exceedance probability using stochastic approaches. Data on one thousand modeled typhoons passing through Tokyo Bay are extracted using a probabilistic tropical cyclone model over 10,000 years. Flooding due to storm surges is calculated with a validated numerical storm surge model. Next, a storm surge risk map that indicates inundation depth for a representative exceedance probability is created from the results of a series of stochastic hazard calculations. The inundation depth data sets for 1000 typhoons—along with the spatially distributed assets and values and damage functions provided by the Japanese government for Tokyo Bay—are used to estimate the economic loss from typhoons for corresponding exceedance probability. From the risk mapping, it was found that the storm surge risk in Chiba and Kanagawa prefectures is relatively high for exceedance probabilities and the economic losses estimated for the exceedance probability of 0.005 are 158.4 and 91.5 billion Japanese yen for the private and commercial sectors respectively along the Tokyo Bay coast. Moreover, the effect of the astronomical tide on the exceedance probability is evaluated using a neural network. However, it was found that the randomly determined astronomical tide does not have a significant influence on the exceedance probability targeted for insurance purposes when losses over 10,000 years are investigated.

Determinants of Hurricane Evacuation from a Large Representative Sample of the U.S. Gulf Coast.

Exposure to natural disasters like hurricanes negatively impacts the mental and physical health of populations, and evacuation is an important step taken to prevent these adverse health events. This study uses data from a large representative sample of U.S. Gulf Coast residents to explore the determinants of hurricane evacuation. In December 2017, data were collected from 3030 residents of the U.S. Gulf Coast, including Texas, Louisiana, Mississippi, Alabama, and Florida—2557 of whom reported being impacted during the 2017 hurricane season. Bivariate analyses were conducted using prevalence differences and tested for statistical significance with chi-square tests. Multivariable logistic regression models were fitted to identify factors associated with hurricane evacuation. One-third of the respondents (919 of 2557; 35.9%) evacuated from a hurricane that impacted the U.S. Gulf Coast in 2017. The determinants of hurricane evacuation in this population were: residing in a mobile home, higher perception of storm surge risk, higher perception of wind risk, self-sufficiency, carrying flood insurance, and reliance on media and family for evacuation decisions. These findings may be relevant for reducing the adverse health effects of hurricanes by improving emergency planning and evacuation in this highly vulnerable region.

Assessment and zonation of storm surge hazards in the coastal areas of China

Storm surge is one of the most devastating marine disasters in China, leading to tremendous economic damage and a large number of casualties. Combined storm surge hazard assessment and zonation is an important method for coastal disaster risk reduction and mitigation management. Based on observational data from tide-gauge and hydrological stations in coastal areas, we analyzed storm surge hazard intensity and generated a storm surge hazard map at the county level using the expected values of storm surge and over-warning water levels. The results show that 87, 67, 62, and 40 counties along the coast of China are exposed to the first (highest), second (higher), third (medium), and fourth (low) degree of hazard level, respectively. The areas with the highest risk of storm surge are the coasts of Bohai Bay, Laizhou Bay, and the Yangtze Delta, the coast from the north of Fuzhou to the south of Zhejiang, and the coastal area of Huizhou, Pearl River, and Yangjiang in Guangdong Province. This assessment, which is based on a national storm surge hazards map, can provide decision-making support for the government’s urban planning of coastal cities and site selection in large national projects.

The risk of typhoon and storm surge along the coast of Vietnam

The history (1951–2016) and the risk of typhoon and storm surge in coastal areas of Vietnam are analyzed and evaluated based on the observation data, results of statistical and numerical models. The Monte Carlo method was used to construct a bogus typhoon. A coupled numerical model of Surge, Wave and Tide (called SuWAT) was used for simulation of storm surge. The results show that in the period of 1951–2016 there were many typhoons which landed and induced high storm surge on the coast of the North and the North of Center of Vietnam. During one thousand years, there have been 4,678 typhoons entering the coastal zone from Quang Ninh to Ca Mau. In particular, the most severe typhoon in coastal area from Quang Ninh to Thanh Hoa is at level 16 (Beaufort scale), Nghe An - Quang Tri at level 16, Quang Binh - Phu Yen at level 17, Binh Dinh - Ninh Thuan at level 15 and Binh Thuan - Ca Mau at level 13. The coastal areas with highly vulnerable storm surge are provinces from Quang Ninh to Hai Phong (4.5 m), Thanh Hoa to Nghe An (4.0 m), Quang Tri (5.0 m). The results of this study are the basis for the preparation to cope with strong/super typhoon in the coast of Vietnam.

Optimization of multiple storm surge risk mitigation strategies for an island City On a Wedge

Managing coastal flood risks involves selecting a portfolio of different strategies. Analyzing this choice typically requires a model. State-of-the-art coastal risk models provide detailed regional information, but they can be difficult to implement, computationally challenging, and potentially inaccessible. Simple economic damage models are more accessible but may not incorporate important features and thus fail to model risks and trade offs with enough fidelity to support decision making. Here, we develop a new framework to analyze coastal flood risk management. The framework is computationally inexpensive yet incorporates common features of many coastal cities. We apply this framework to an idealized coastal city and assess and optimize two objectives using combinations of risk mitigation strategies against a wide range of future states of the world. We find that optimization using combinations of strategies allows for identification of Pareto optimal strategy combinations that outperform individual strategy options.

Simulation-Based Exceedance Probability Curves to Assess the Economic Impact of Storm Surge Inundations due to Climate Change: A Case Study in Ise Bay, Japan

Understanding storm surge inundation risk is essential for developing countermeasures and adaptation strategies for tackling climate change. Consistent assessment of storm surge inundation risk that links probability of hazard occurrence to distribution of economic consequence are scarce due to the lack of historical data and uncertainty of climate change, especially at local scales. This paper proposes a simulation-based method to construct exceedance probability (EP) curves for representing storm surge risk and identifying the economic impact of climate change in the coastal areas of Ise Bay, Japan. The region-specific exceedance probability curves show that risk could be different among different districts. The industry-specific exceedance probability curves show that manufacturing, transport and postal activities, electricity, gas, heat supply and water, and wholesale and retail trade are the most affected sectors in terms of property damage. Services also need to be of concern in terms of business interruption loss. Exceedance probability curves provide complete risk information and our simulation-based approach can contribute to a better understanding of storm surge risk, improve the quantitative assessment of the climate change-driven impacts on coastal areas, and identify vulnerable regions and industrial sectors in detail.

New Statistical Approach to Select Coastal Flood-Producing Extratropical Cyclones from a 10,000-Year Stochastic Catalog

Extratropical cyclones (ETCs) are the major storm surge-producing events along the Northwest European coastline. To evaluate the storm surge risk covering the return period up to 10,000 years in this region, a stochastic catalog is developed by perturbing European historical ETCs. Numerical simulation of the storm surge generated by the full 10,000-year stochastic catalog, however, is computationally expensive. Also, not all the stochastic ETC events are surge-producing storms. Here, we propose an efficient statistical approach to filter the stochastic catalog by estimating the storm surge elevation at tide gauges and then selecting only the non negligible surge-producing events. The proposed approach reduces the number of stochastic storms that need to be numerically simulated by 78%, thereby saving computational resources for high-resolution numerical simulations of surge producing storms.

COMBINED EFFECT OF STORM SURGE AND OVERLAND FLOW ON FLOODING IN A COASTAL URBAN AREA

The coastal regions in the U.S. East Coast and the Gulf of Mexico are under the risk of storm surge and precipitation-driven flooding. The adverse impacts of climate change including sea level rise (SLR), potential increase in intensity and frequency of extreme storms, and increase in precipitation intensity increases the vulnerability of coastal communities to flooding. The common practice for flood hazard assessment in urban coastal areas can result in some errors as the effect of storm surge and overland flow are not considered simultaneously. In this study, we combine the results of two hydrodynamic models, one for overland flow and the other for storm surge inundation, to develop an improved approach for flood hazard assessment.

Assessment of storm surge risk in aquaculture in the Northern coastal area of Vietnam

This research utilizes the disaster risk concept developed by the Intergovernmental Panel on Climate Change (IPCC) to determine and assess the storm surge risk in aquaculture in the coastal area from Quang Ninh to Ninh Binh province. The results indicated that the highest level of risk occurred in Thai Thuy district (Thai Binh province) and Quang Yen town (Quang Ninh province). The second highest level or risks occurred in Tien Hai district (Thai Binh province), Mong Cai city and Hai Ha district (Quang Ninh province). The lowest level of risk transpires in Uong Bi city (Quang Ninh province) and Kien An district (Hai Phong city). The results provide a scientific basis to support local government in establishing proactive response plans to storm surges, reduce and prevent storm surge damage to aquaculture, assist policy making and establish suitable development priorities for the coastal areas in the Northern region.

CONSIDERATION OF STORM SURGE CAUSED BY HURRICANE IRMA BASED ON STOC-WRF COUPLING MODEL

Hurricane Irma occurred in the Atlantic Ocean in 2017. It has developed to Category 5, the maximum wind speed is about 82.7 [m/s], minimum central pressure is about 914 [hPa]. Because there is concern that the risk of storm surge due to global warming is increasing, it is important to predict storm surge for prevention of the disasters. For that purpose, it is important to construct a method that can predict local area phenomena. Therefore, in this study, to achieve that purpose, a methodology of downscaling the mesoscale data is developed by using the STOC-ML and WRF, and the applicability is verified to the storm surge due to Irma. In addition, wave set up is also estimated using SWAN and the characteristics of Irma is considered.

High‐resolution optical dating of Late Holocene storm surge deposits – a showcase from Schokland (Noordoostpolder, the Netherlands)

AbstractStorm surges have a major impact on land use and human habitation in coastal regions. Our knowledge of this impact can be improved by correlating long‐term historical storm records with sedimentary evidence of storm surges, but so far few studies have applied such an approach. Here we apply, for the first time, state‐of‐the‐art optically stimulating luminescence (OSL) methods to obtain high‐resolution age information on a sequence of Late Holocene storm surge deposits. By combining this chronological framework of storm surges with other reconstruction methods, we investigate the storm surge impact on the former island Schokland, located in a former inlet of the North Sea (central Netherlands).During the Late Holocene, Schokland transformed from a peat area that gradually inundated (~800 CE) via an island in a marginal marine environment (~1600 CE) to a land‐locked island in the reclaimed Province of Flevoland (1942 CE). These transitions are recorded in the sediment archive of the island, consisting of silty clay with sandy intervals deposited during storm surges. A series of ten quartz OSL ages, obtained using best‐practice methods to deal with incomplete resetting of the OSL signal and dose rate heterogeneity, reveal two periods of storm surge deposition, around 1600 CE and between 1742 and 1822 CE. Historical sources indicate that major storm surges hit Schokland during these periods. Laboratory analyses (thermogravimetry, grain‐size, foraminifera, bivalves and ostracods) corroborates the existence of the two sets of storm surge deposits within the clay sequence. Our study sets a benchmark for obtaining robust depositional age constraints from storm surge sediments, and demonstrates the great potential of modern OSL methods to contribute to improved assessment of storm surge risk. © 2018 John Wiley & Sons, Ltd.

A Fiscally Based Scale for Tropical Cyclone Storm Surge

AbstractCategorization of storm surge with the Saffir–Simpson hurricane scale has been a useful means of communicating potential impacts for decades. However, storm surge was removed from this scale following Hurricane Katrina (2005), leaving no scale-based method for storm surge risk communication despite its significant impacts on life and property. This study seeks to create a new, theoretical storm surge scale based on fiscal damage for effective risk analysis. Advanced Circulation model simulation output data of maximum water height and velocity were obtained for four storms: Hurricane Katrina, Hurricane Gustav, Hurricane Ike, and Superstorm Sandy. Four countywide fiscal loss methods were then considered. The first three use National Centers for Environmental Information Storm Events Database (SED) property damages and Bureau of Economic Analysis (BEA) population, per capita personal income, or total income. The fourth uses National Flood Insurance Program total insured coverage and paid claims. Initial correlations indicated the statistical mode of storm surge data above the 90th percentile was most skillful; this metric was therefore chosen to represent countywide storm surge. Multiple linear regression assessed the most skillful combination of storm surge variables (height and velocity) and fiscal loss method (SED property damages and BEA population, i.e., loss per capita), and defined the proposed scale, named the Kuykendall scale. Comparison with the four storms’ actual losses shows skillful performance, notably a 20% skill increase over surge height-only approaches. The Kuykendall scale demonstrates promise for skillful future storm surge risk assessment in the analytical, academic, and operational domains.

2015A-GS19-1 伊勢湾沿岸の高潮特性を考慮した高潮ハザードマップに基づくコンテナ被害の検討

2015A-GS19-1 伊勢湾沿岸の高潮特性を考慮した高潮ハザードマップに基づくコンテナ被害の検討

Pricing Storm Surge Risks in Florida: Implications for Determining Flood Insurance Premiums and Evaluating Mitigation Measures.

The National Flood Insurance Program (NFIP) has been criticized for inaccurate flood hazard maps and premiums that are not risk based. We employ granular storm surge data comprised of five different event probabilities with associated flood elevations to calculate surge risk-based premiums for homes in Pensacola, Florida, which we compare with NFIP premiums that are based on flood risk data with only one event probability (1% annual chance floods). We demonstrate how more granular flood risk data used for calculating risk-based insurance premiums should be part of the NFIP mapping and rate-setting processes. We then examine three different sea-level rise (SLR) scenarios specific to Pensacola from the National Oceanic and Atmospheric Administration (NOAA), and assess surge risk-based premiums out to 2100. We analyze the cost effectiveness of elevating homes to mitigate surge risks when costs of elevation are one lump upfront sum, and when costs are spread over 30 years via low-interest mitigation loans. Benefits are the avoided future losses from surge risks going out to 2100 with the three different SLR scenarios. Findings show that it is cost effective to elevate high-value homes with low first-floor elevations in the most risky surge zones. Spreading costs of elevation with 30-year loans should be directed at low-income households to address affordability concerns. Alternative flood mitigation actions, such as wet floodproofing and elevating electrical and plumbing utilities, should be considered in instances where elevation is not cost effective.

Risk assessment of storm surge disaster based on numerical models and remote sensing

Storm surge is one of the most serious ocean disasters in the world. Risk assessment of storm surge disaster for coastal areas has important implications for planning economic development and reducing disaster losses. Based on risk assessment theory, this paper uses coastal hydrological observations, a numerical storm surge model and multi-source remote sensing data, proposes methods for valuing hazard and vulnerability for storm surge and builds a storm surge risk assessment model. Storm surges in different recurrence periods are simulated in numerical models and the flooding areas and depth are calculated, which are used for assessing the hazard of storm surge; remote sensing data and GIS technology are used for extraction of coastal key objects and classification of coastal land use are identified, which is used for vulnerability assessment of storm surge disaster. The storm surge risk assessment model is applied for a typical coastal city, and the result shows the reliability and validity of the risk assessment model. The building and application of storm surge risk assessment model provides some basis reference for the city development plan and strengthens disaster prevention and mitigation.

Malaria, Water Management, and Identity in the English Lowlands

AbstractMuch of the eastern seaboard of England lying between East Yorkshire and the Pevensey Levels in Kent constitutes an English Lowlands, a distinctive region characterized by large areas of ma...

Understanding the detectability of potential changes to the 100-year peak storm surge

In many coastal communities, the risks driven by storm surges are motivating substantial investments in flood risk management. The design of adaptive risk management strategies, however, hinges on the ability to detect future changes in storm surge statistics. Previous studies have used observations to identify changes in past storm surge statistics. Here, we focus on the simple and decision-relevant question: How fast can we learn from past and potential future storm surge observations about changes in future statistics? Using Observing System Simulation Experiments, we quantify the time required to detect changes in the probability of extreme storm surge events. We estimate low probabilities of detection when substantial but gradual changes to the 100-year storm surge occur. As a result, policy makers may underestimate considerable increases in storm surge risk over the typically long lifespans of major infrastructure projects.