Storm Surge Research Articles

On the Relation between Overwater Friction Velocity and the Wind Speed During Tropical Cyclones

In the realm of marine meteorology, physical oceanography, and coastal and ocean engineering, the wind-stress across the air-sea interface plays a dominant role. However, under tropical cyclone conditions, there is no consensus for the formulation of the drag coefficient, <em>C</em><sub>d</sub>, in the literature. Based on the wind-gust method and the measurements from data buoy 42001 during Hurricane Lili, it is demonstrated that, <em>U</em><sub>*</sub> = 0.073<em>U</em><sub>10</sub> - 0.44, which is valid up to wind speed 47 m s<sup>-1</sup> and wind gust to 66 m s<sup>-1</sup>, here <em>U</em><sub>*</sub> is the friction velocity and <em>U</em><sub>10</sub> is the wind speed at 10-m height. This formula is also supported by the atmospheric vorticity method. Applications for this proposed formula to estimate the variation of the wind speed with height and to determine the wind-stress storm surge or saltwater flooding during the most recent Hurricane Helene in 2024 are successful. In addition, it is found that <em>C</em><sub>d</sub> = (1.29<em>Ln</em>(<em>H</em><sub>s</sub>) + 0.27)/1000, which may be used to explain the behavior of the variation of <em>C</em><sub>d</sub> with the significant wave height, <em>H</em><sub>s</sub>. In order to further substantiate the proposed formula, more datasets during other tropical cyclones are incorporated for the validation.

Preserving History: Assessments and Climate Adaptations at the House of the Seven Gables in Salem, Massachusetts, USA

Salem, Massachusetts, is one of the oldest cities in the United States (1629) and its coastal location on the Atlantic helped create one of the wealthiest cities in America during the late 18th century, but today its coastal location threatens many of its buildings due to sea level rise and increased storm activity. The House of the Seven Gables, a National Historic Landmark District, consists of five important historic buildings, the most famous being The Turner Ingersoll Mansion (1668), more commonly known as The House of the Seven Gables. Considered one of the most important houses in America, it is also one of the most threatened historic buildings due to its location on Salem’s harbor. The House of the Seven Gables conducted a two-year study funded by Massachusetts Coastal Zone Management to evaluate the risks posed by climate change. This process included the use of data from groundwater monitoring wells and a tidal gauge installed on-site, along with soil samples and a detailed survey base plan including topography and subsurface infrastructure. The project team then used the Massachusetts Coastal Flood Risk Model (MC-FRM) to assess climate change impacts on the site in 2030, 2050, and 2070, and then created a plan for adaptations that should be implemented before those risks materialize. Strategies for adapting to storm surges, increasing groundwater, and intense surface water runoff were evaluated for their effectiveness and appropriateness for the historic site. The conclusion of the study resulted in a five-phase plan ending in the managed retreat of the historic buildings to higher ground on the existing site. This article goes beyond other research that suggests coastal retreats by demonstrating how to quantitatively evaluate current and future coastal issues with predictive models and how to set viable dates for adaptive solutions and a managed retreat.

Scoping the suitability of water‐tolerant species of trees for swamp restorations across Australia and its Great Barrier Reef catchment

Wetlands are vital for humanity and include some of the most productive, diverse, and service‐rich ecosystems in the world. Service provided include food production (e.g., fish, birds, and vegetables), protection from flooding and storm surge inundation, provision of clean water and climate stability, and timber resources for construction. Despite these benefits, vast areas of wetlands have been drained across the globe, including in Australia. With growing awareness of the value of wetlands, there is increasing push to restore wetlands and the values they support, such as carbon sequestration. A major challenge for restoration practitioners is to identify what land parcels could be restored and what species they could support. This study scoped the environmental suitability of 125 water‐tolerant species of trees across Australia, using random forest modeling to relate records observed within the Atlas of Living Australia database with spatial datasets of soil and climatic characteristics and water observations from space. Of the 125 species of trees examined, 105 species were modeled with excellent performance. Models were then used to predict tree suitability for existing wetlands nationally, as well as across potentially suitable restoration sites within the Great Barrier Reef catchment, given the strong push for wetland restoration to improve water quality. Within the Great Barrier Reef catchment, over 2200 land parcels covering over 20,000 ha were identified as being potentially suitable for restoration with diverse tree swamps. This study allows restoration practitioners to identify where swamp restoration could occur and potentially suitable trees for planting at those locations.

Paradigm Shift in Typhoon Forecasting for the Korean Peninsula: A Case Study on the Applicability of the Typhoon-Ready System

Climate change has significantly increased multi-hazard disasters caused by typhoons, exposing the limitations of conventional forecasting systems that often neglect regional socio-economic vulnerabilities. This study develops and validates the Typhoon-Ready System (TRS) as an effective disaster-management framework for the Korean Peninsula. The TRS integrates hazard data with socio-economic and environmental vulnerability factors to produce region-specific risk indices. The analysis of four representative typhoons—Lingling (2019), Rusa (2002), Maemi (2003), and Mitak (2019)—demonstrates TRS’s applicability in identifying high-risk zones and supporting disaster preparedness strategies. The TRS framework incorporates indices, such as the Strong Wind Index (SWI), Heavy Rainfall Index (HRI), Storm Surge Index (SSI), and Air Quality Index (AQI), effectively combining meteorological modeling with vulnerability analysis. Results demonstrate that the TRS outperforms traditional systems by accurately identifying high-risk zones and correlating them with observed damage patterns. For example, the TRS successfully pinpointed high wind risks in Seoul and Incheon during Typhoon Lingling and forecasted severe flooding in Gangneung and Samcheok during Typhoon Rusa. By integrating vulnerability factors, including population density, infrastructure aging, and urbanization levels, the TRS provides a more holistic and accurate risk assessment. This research highlights the necessity of a multi-dimensional forecasting approach for enhancing disaster preparedness and resilience against climate change-induced typhoon impacts.

Evaluating the influence of human activities on flood severity and its spatial heterogeneity across the Pearl River Delta.

With climate change and intensified human activities, disasters such as heavy rainfall, flooding, typhoons, and storm surges are becoming more frequent, posing significant threats to lives, property, and economic development. We propose a method combining extreme value theory and probability distribution to examine the flood severity under the effect of strong human activities. By focusing on the Pearl River Delta (PRD), as one of the most populated areas of China, we quantified changes in the severity of extreme water level for different return levels between 1966 and 1990 and 1991-2016 (with strong human activities), associated with the spatial patterns over the PRD. The flood severity decreased near inland areas of the delta but increased in coastal areas. Additionally, in coastal areas, the flood severity of long return levels has increased more significantly than that of short return levels, under the effect of strong anthropogenic activities. This study further examined the spatial heterogeneity in extreme water levels under the influence of human activities over the PRD. This study provides new insights into basin-scale flood responses to human activities and strategies for mitigating flood disasters over the PRD. The proposed method offers a promising approach for evaluating the severity of flooding in regions experiencing hydrological changes similar to those observed in the PRD under the influence of human intervention.

In search of non-stationary dependence between estuarine river discharge and storm surge based on large-scale climate teleconnections

Compound floods may happen in low-lying estuarine environments when sea level above normal tide co-occurs with high river flow. Thus, comprehensive flood risk assessments for estuaries should not only account for the individual hazard arising from each environmental variable in isolation, but also for the case of bivariate hazard. Characterization of the dependence structure of the two flood drivers becomes then crucial, especially under climatic variability and/or change that may affect their relationship. In this article, we demonstrate our search for evidence of non-stationarity in the dependence between river discharge and storm surge along the East and Gulf coasts of the United States, driven by large-scale climate variability, particularly El-Niño Southern Oscillation and North Atlantic Oscillation (NAO). Leveraging prolonged overlapping observational records and copula theory, we recover parameters of both stationary and dynamic copulas using state-of-the-art Markov Chain Monte Carlo methods. Physics-informed copulas are developed by modeling the magnitude of dependence as a linear function of large-scale climate indices, i.e., Oceanic Niño Index or NAO index. After model comparison via suitable Bayesian metrics, we find no strong indication of such non-stationarity for most estuaries included in our analysis. However, when non-stationarity due to these climate modes cannot be neglected, this work highlights the importance of appropriately characterizing bivariate hazard under non-stationarity assumption. As an example, we find that during a strong El-Niño year, Galveston Bay, TX, is much more likely to experience a coincidence of abnormal sea level and elevated river stage.

Enhanced understanding on spatial and dependence properties of rainfall extremes and storm tides in coastal cities

Enhanced understanding on spatial and dependence properties of rainfall extremes and storm tides in coastal cities

Coastal storm surge amplification by wave radiation stress: The case study of 2015 Typhoon Soudelor in East Taiwan

Coastal storm surge amplification by wave radiation stress: The case study of 2015 Typhoon Soudelor in East Taiwan

Water Table Fluctuations Control Nitrate and Ammonium Fate in Coastal Aquifers

AbstractCoastal aquifers experience water table fluctuations that push and pull water and air through organic‐rich soils. This exchange affects the supply of oxygen, dissolved organic carbon (DOC), and nitrogen (N) to shallow aquifers and influences groundwater quality. To investigate the fate of N species, we used a meter‐long column containing a sequence of natural organic topsoil and aquifer sediments. A fluctuating head was imposed at the column bottom with local, nitrate‐rich groundwater (16.5 mg/L NO3‐N). We monitored in‐situ redox potential and collected pore water samples for analysis of inorganic N species and DOC over 16 days. Reactive processes were more complex than anticipated. The organic‐rich topsoil remained anaerobic, while mineral sediments beneath alternated between aerobic, when the water table dropped and sucked air across preferential flow paths, and anaerobic conditions, when the water table was high. A fluid flow and reactive transport model shows that when the water table rises into organic‐rich soils, it limits the flow of oxygen, while the soils release DOC, which stimulates the removal of nitrate from groundwater by denitrification. At the end of the experiment, we introduced seawater to the column to mimic a storm surge. Seawater mobilized N and DOC from shallow soil horizons, which could reach the aquifer if the surge is long enough. These processes are relevant for groundwater quality in developed coastal areas with anthropogenic N sources, as climate change and rising seas will drive changes in water table and flood dynamics.

Evaluation of Inundation Probability Using Storm Surge Coastal Inundation Prediction Map DB

This study evaluates the probability of inundation, which is not provided by deterministic storm surge coastal inundation prediction maps based on return periods. Busan was selected as the study area and an inundation database was constructed using hypothetical typhoon scenarios to create coastal inundation prediction maps. Areas with a storm surge inundation probability of more than 90% were identified along the coastline, accounting for up to 5% of the total inundated area. Most other inundated regions demonstrated an inundation probability of approximately 20%. The probabilities for inundation depths of over 2.0 m and 3.0 m were evaluated to be no more than 50%, and 30%, respectively. The generated probability information for the storm surge inundation can be utilized not only to assess coastal inundation risk, but also in other applications to account for uncertainties due to climate change-induced variations in typhoon intensity and numerical model errors, which are not considered in return period-based coastal inundation prediction maps using hypothetical scenarios and numerical models.

Geographical Information Systems-Based Assessment of Evacuation Accessibility to Special Needs Shelters Comparing Storm Surge Impacts of Hurricane Irma (2017) and Ian (2022)

Research on hurricane impacts in Florida’s coastal regions has been extensive, yet there remains a gap in comparing the effects and potential damage of different hurricanes within the same geographical area. Additionally, there is a need for reliable discussions on how variations in storm surges during these events influence evacuation accessibility to hurricane shelters. This is especially significant for rural areas with a vast number of aging populations, whose evacuation may require extra attention due to their special needs (i.e., access and functional needs). Therefore, this study aims to address this gap by conducting a comparative assessment of storm surge impacts on the evacuation accessibility of southwest Florida communities (e.g., Lee and Collier Counties) affected by two significant hurricanes: Irma in 2017 and Ian in 2022. Utilizing the floating catchment area method and examining Replica’s OD Matrix data with Geographical Information Systems (GISs)-based technical tools, this research seeks to provide insights into the effectiveness of evacuation plans and identify areas that need enhancements for special needs sheltering. By highlighting the differential impacts of storm surges on evacuation accessibility between these two hurricanes, this assessment contributes to refining disaster risk reduction strategies and has the potential to inform decision-making processes for mitigating the impacts of future coastal hazards.

Medieval Overexploitation of Peat Triggered Large-Scale Drowning and Permanent Land Loss in Coastal North Frisia (Wadden Sea Region, Germany)

Along the southern North Sea coast from the Netherlands to Denmark, human cultivation efforts have created a unique cultural landscape. Since the Middle Ages, these interactions between humans and natural forces have induced major coastal changes. In North Frisia (Germany), storm floods in 1362 AD and 1634 AD turned wide areas of embanked cultural land into tidal flats. Systematic geoarchaeological investigations between Nordstrand and Hallig Südfall comprise coring, trenching, sedimentary, geochemical and microfaunal palaeoenvironmental parameter analyses and radiocarbon dating. Together with geophysical prospection results and archaeological surveys, they give insights into the landscape’s development and causes for land losses. Results reveal that fens and bogs dominated from c. 800 BC to 1000 AD but are mostly missing in the stratigraphy. Instead, we found 12th to 14th cent. AD settlement remains directly on top of a pre-800 BC fossil marsh. This hiatus of c. 2000 years combined with local ‘Hufen’ settlements implies an extensive removal of peat during cultivation eventually resulting in the use of underlying marshland for agricultural purposes. Fifteenth cent. AD tidal flat deposits on top of the cultivated marsh prove that human impact lowered the ground surface below the mean high water of that time, clearly increasing the coastal vulnerability. We consider these intensive human–environment interactions as a decisive trigger for the massive loss of land and establishment of the tidal flats in North Frisia that are currently part of the UNESCO World Heritage “Wadden Sea”.

Innovative absolute probability approach for coastal vulnerability assessment due to sea level rise: Application in Tagus Estuary, Portugal.

In coastal urban areas highly susceptible to flooding, whether from sea level rise (SLR) or storms, it is crucial to assess the vulnerability and risks posed by extreme and frequent floods. Reliable estimates of extreme natural events' return periods rely on historical data or probabilistic models, requiring extensive and robust data. From climate-scenario-based or semi-empirical models, SLR projections are represented by a central estimate or the full domain cumulative density function (CDF), entailing uncertainties. Each scenario or projection having its own CDF results in relative probability solutions rather than absolute probability. This article presents an innovative approach for determining absolute flood probability for the medium-to-long-term (2090) and long-term (2120), encompassing extreme and frequent floods over the next 100years, by combining the individual CDF of SLR, tide, and storm surge. This approach allowed the production of a new vulnerability mapping, with high spatial resolution, by adding an image processing algorithm to eliminate all flood areas isolated from tidal surface flow at the maximum total hydrostatic water level (THWL). Geographic Information Systems (GIS) can replicate this methodology. Still, as a test zone, it is specifically applied as a demonstration to the Tagus Estuary, Portugal. In 2090, the highest flood level estimation on the Tagus Estuary margins is 4.06m, corresponding to a total vulnerable area of 92km2. However, by 2120, it is expected that maximum flood height will reach 4.87m, expanding the area to 102km2. After applying the image processing algorithm to clean isolated flood areas, a decrease of 20% in the medium-to-long-term and 17% in the long-term of the vulnerable area was obtained, relative to hazard assessment. The present study intends to obtain the absolute coastal vulnerability for further coastal risk assessment, based on a non-scenario-dependent flooding probability.

SWEMniCS: a software toolbox for modeling coastal ocean circulation, storm surges, inland, and compound flooding

Flooding from storm surges, rainfall-runoff, and their interaction into compounding events are major natural hazards in coastal regions. To assess risks of damages to life and properties alike, numerical models are needed to guide emergency responses and future assessments. Numerical models, such as ADCIRC have over many decades shown their usefulness in such assessments. However, these models have a high threshold in terms of new user engagement as development and compilation is not trivial for users trained in compiled programming languages. Here, we develop a new open-source finite element solver for the numerical simulation of flooding. The numerical solution of the underlying PDEs is developed using the finite element framework FEniCSx. The goal is a framework where new methods can be rapidly tested before time-consuming development into codes like ADCIRC. We validate the framework on several test cases, including large-scale computations in the Gulf of Mexico for Hurricane Ike (2008).

Technical assessment combined with an extended cost–benefit analysis for the restoration of groundwater and forest ecosystem services – an application for Grand Bahama

Abstract. A large storm surge caused by Hurricane Dorian in 2019 resulted in extensive flooding and saltwater intrusion into the aquifers of the island of Grand Bahama. This caused about 40 % of the island's water supply to become brackish with no or slow recovery to date and damage to more than 70 % of mangroves and forests on Grand Bahama. Managed aquifer recharge (MAR) and reforestation were considered nature-based solutions (NBS) to mitigate the impacts of Hurricane Dorian. First, a technical assessment of MAR investigated (hydro)geological aspects. As a result, potential locations for a MAR scheme are proposed. Further, a financial and an extended cost–benefit analysis (CBA) integrating ecosystem service (ES) assessments are conducted for proposed MAR and reforestation measures. Based on the current data availability, results indicate that the MAR scheme of rooftop rainwater harvesting is technically feasible. However, based on our first estimate with limited data, this MAR scheme will be able to provide only about 10 % of the water demand in the study area and thus would not be favorable from a financial perspective. Since MAR has a range of positive aspects (including potential reduction of desalinization efforts and improvement freshwater-dependent ecosystems), we recommend reassessment with more detailed hydrogeological data. On the other hand, reforestation measures are assessed to be financially profitable. The results of this study not only prove the technical feasibility and the added value of restoring groundwater and the forest ecosystem on Grand Bahama, but also highlight the associated high costs. The developed methods for investigating ecosystem services from an economic perspective was proven to allow for a systematic comparison of NBSs and reverse osmosis costs and benefits helping, e.g., policy- and decision-makers and to justify their implementation.

Enhanced Cyclone Intensity Estimation Using Deep Learning Models

Every year in India, tropical cyclones pose one of the greatest threats to life and property. They include a variety of hazards, each of which can have a significant impact on life and property, such as storm surge, flooding, extreme winds, tornadoes, and lighting. These hazards interact with one another, substantially increasing the risk of loss of life and material damage. According to a study on extreme weather events, as many as 117 cyclones hit India in 50 years from 1970 to 2019, claiming over 40,000 lives. Due to advancements in technology, detection of cyclones has become much easier. Cyclones are categorized into various categories based on their intensity which is calculated by various methods and sources. Estimation of the intensity of cyclone helps them to categorize. In this paper we are trying to estimate the intensity of cyclones by using the state- of-the-art deep learning models as they are pre-trained on large data sets. Keywords: Tropical cyclones, Hazards, Intensity estimation, Deep learning models, Detection, Data sets, Cyclone intensity, Weather prediction, Disaster management.

Sequential Maximal Updated Density Parameter Estimation for Dynamical Systems With Parameter Drift

ABSTRACTWe present a novel method for generating sequential parameter estimates and quantifying epistemic uncertainty in dynamical systems within a data‐consistent (DC) framework. The DC framework differs from traditional Bayesian approaches due to the incorporation of the push‐forward of an initial density, which performs selective regularization in parameter directions not informed by the data in the resulting updated density. This extends a previous study that included the linear Gaussian theory within the DC framework and introduced the maximal updated density (MUD) estimate as an alternative to both least squares and maximum a posterior (MAP) estimates. In this work, we introduce algorithms for operational settings of MUD estimation in real‐ or near‐real time where spatio‐temporal datasets arrive in packets to provide updated estimates of parameters and identify potential parameter drift. Computational diagnostics within the DC framework prove critical for evaluating (1) the quality of the DC update and MUD estimate and (2) the detection of parameter value drift. The algorithms are applied to estimate (1) wind drag parameters in a high‐fidelity storm surge model, (2) thermal diffusivity field for a heat conductivity problem, and (3) changing infection and incubation rates of an epidemiological model.

Regional Storm Surge Forecast Method Based on a Neural Network and the Coupled ADCIRC-SWAN Model

Regional Storm Surge Forecast Method Based on a Neural Network and the Coupled ADCIRC-SWAN Model

Influence of tropical cyclone moving speeds on the attenuation effect of Holland surface wind and storm surge simulation in Guangdong Province, China

The Holland wind model remains limitations on the accurate surface wind estimation of tropical cyclone (TC) and the storm surge modelling. This study investigates the influence of TC moving speeds on the attenuation effect of Holland surface wind and proposes a weakening factor to correct Holland surface wind. Then the corrected surface wind fields are combined with ERA5 to produce the improved hybrid surface wind fields to simulate total water levels. The significant linear correlation (R2 = 0.54) between TC moving speeds and the weakening factor shows that the slower the TC moves, the greater attenuation rate the surface wind speeds need. The improved Hybrid wind fields (Hybrid_f) have the best agreement with ground observations, with the Skills and RMSEs in the range of 0.65-0.93 and 2.3-6.9 m/s. The total water levels of storm surge simulated by the Hybrid_f have the best agreement with gauge measurements, with the Skills and RMSEs in the range of 0.72-0.99 and 0.16-0.51 m. In particular, the improved surface wind fields for TCs with slower movement substantially mitigate the severe reduction of water levels. These findings offer valuable insights for optimizing the surface wind fields to improve storm surge modeling and other applications.

Spatiotemporal dynamics of geomorphology, landuse, and storm surge inundation of FDMN settled in Bhasan Char island using geo-spatial techniques

Bhasan Char has undergone noteworthy transformations in its geographical characteristics since its emergence in 2003. Driven by sediment transported by the Ganges-Brahmaputra-Meghna river system, the island has gradually transitioned from a stretched-out configuration to a more rounded shape primarily due to continuous accretion, while erosion has been minimal since 2012. Currently, the island is being prepared to accommodate over 1 million Forcefully Displaced Myanmar Nationals (FDMN) refugees. This investigation, conducted over the time frame spanning from 2003 to 2023, utilizes multi-temporal satellite imagery to scrutinize the altering geography of the island, encompassing the processes of erosion and accretion, modifications in the coastline, and changes in land utilization and coverage influenced by seasonal variations. By employing the Advanced Land Observing Satellite (ALOS)/Phased Array Type L-Band Synthetic Aperture Radar (PALSAR), the study pioneers an evaluation of storm surge risks that are specific to this island. Additionally, the research utilizes water indices to understand the seasonal geomorphic dynamics of the island and performs a supervised classification to assess land utilization and coverage alterations. The inundation map shows accretion in the north and erosion in the south and southeast. Southwest is the most stable area with the majority population. After the 'Ashrayan -3′ project, significant land use and land cover changes occurred, including urbanization, embankment construction, and agricultural modifications. The average elevation of the island is 2.84 m above sea level, with a risk of inundation from storm surges exceeding 3 m. Rehabilitated populations are particularly threatened if the embankment height of 4.8 m is surpassed. The study's outcomes indicate that other projects worldwide might use the island restoration efforts as a model. This emphasizes how crucial it is to keep an eye on changes in land cover and use for upcoming planning and adaptation initiatives. Moreover, it highlights the necessity of proper assessments of storm surge hazards to guarantee the security and longevity of island communities.