Coastal Storm Surge Research Articles

Storm surge modelling along European coastlines: The effect of the spatio-temporal resolution of the atmospheric forcing

The spatio-temporal resolution of atmospheric forcing plays a key role in the accuracy of simulated storm surges with hydrodynamic numerical models. Here, we generate five hydrodynamic hindcasts of coastal storm surges along the European Atlantic and the Mediterranean Sea coasts, forced with atmospheric fields of varying temporal (hourly and daily) and spatial (0.25° to 2°) resolution since 1940. Our results, that are validated with insitu tide gauge observations, show that storm surges obtained with daily forcing underestimate the magnitude of coastal extreme sea level events by up to 50% compared to hourly simulations and observations. Nevertheless, low-resolution simulations capture the temporal variability of storm surges, including strong episodes. Furthermore, taking advantage of the consistent set of coastal storm surge hindcasts, we demonstrate that storm surges forced with daily mean atmospheric fields, when bias corrected via quantile mapping, provide accurate values of daily maxima as calculated by a high-resolution hindcast. This transformation paves the way to obtain daily maxima storm surge estimates from low-resolution atmospheric fields, as those typically provided by large-scale and global climate models, at a lower computational cost.

Improving Coastal Storm Surge Monitoring Through Joint Modeling Based on Permanent and Temporary Tide Gauges

AbstractWith climate change, there will be higher requirements for monitoring storm surges (SSs) in nearshore areas. However, this capability is limited by the sparseness of tide gauge (TG) stations. Establishing and maintaining a permanent, high‐spatial coverage, in situ TG network is complex and expensive. Here, we propose a joint modeling method developed from the all‐site modeling data‐driven framework by importing temporary TGs into coastal regions with insufficient permanent TG stations. The assessments show that this method can significantly optimize the capability of extreme SS monitoring during typhoons and hurricanes. Moreover, the evaluation based on Coupled Model Intercomparison Project Phase 6 data indicates that it will monitor extreme SSs more effectively during 2025–2050 compared with only using existing permanent in situ TGs (reducing root mean square error and absolute mean bias by ∼50%). The joint modeling method provides an applicable and sustainable solution for optimizing the SS monitoring capability in coastal areas.

Four Storm Surge Cases on the Coast of São Paulo, Brazil: Weather Analyses and High-Resolution Forecasts

The coast of São Paulo, Brazil, is exposed to storm surges that can cause damage and floods. These storm surges are produced by slowly traveling cyclone–anticyclone systems. The motivation behind this work was the need to evaluate high-resolution forecasts of the mean sea-level pressure and 10 m winds, which are the major drivers of the wave model. This work is part of the activity in devising an early warning system for São Paulo coastal storm surges. For the evaluation, four case studies that had a major impact on the coast of São Paulo in 2020 were selected. Because storm surges that reach the coast may cause coastal flooding, precipitation forecasts were also evaluated. The mesoscale Eta model produces forecasts with a 5 km resolution for up to an 84 h lead time. The model was set up in a region that covers part of southeast and south Brazil. The ERA5 reanalysis was used to describe the large-scale synoptic conditions and to evaluate the weather forecasts. The cases showed a region in common between 35° S, 40° S and 35° W, 45° W where the low-pressure center deepened rapidly on the day before the highest waves reached the coast of São Paulo, with a mostly eastward, rather than northeastward, displacement of the associated surface cyclone and minimal or no tilt with height. The winds on the coast were the strongest on the day before the surge reached the coast of São Paulo, and then the winds weakened on the day of the maximum wave height. The pattern of the mean sea-level pressure and 10 m wind in the 36 h, 60 h, and 84 h forecasts agreed with the ERA5 reanalysis, but the pressure was slightly underestimated. In contrast, the winds along the coast were slightly overestimated. The 24 h accumulated precipitation pattern was also captured by the forecast, but was overestimated, especially at high precipitation rates. The 36 h forecasts showed the smallest error, but the growth in the error for longer lead times was small, which made the 84 h forecasts useful for driving wave models and other local applications, such as an early warning system.

Prediction of storm surge in the Pearl River Estuary based on data-driven model

Storm surges, a significant coastal hazard, cause substantial damage to both property and lives. Precise and efficient storm surge models are crucial for long-term risk assessment and guiding emergency management decisions. While high-fidelity dynamic models offer accurate predictions, their computational costs are substantial. Hence, recent efforts focus on developing data-driven storm surge surrogate models. This study focuses on the Pearl River Estuary in Guangdong Province. Initially, the dynamic ADvanced CIRCulation (ADCIRC) model was utilized to construct storm surge data for 16 historical typhoons, serving as training, validation, and testing data for data-driven models. Subsequently, Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and Informer deep learning (DL) models were employed for forecasting of storm surge over the next 1h, 3h, 6h, 12h, and 18h. Finally, Shapley Additive exPlanations (SHAP) values were used for interpretability analysis of the input factors across different models. Results indicated that the proposed DL storm surge prediction model can effectively replicate the dynamic model’s simulation results in short-term forecasts, significantly reducing computational costs. This model offers valuable scientific assistance for future coastal storm surge forecasts in the Greater Bay Area.

Fingerprinting Mediterranean hurricanes using pre-event thermal drops in seawater temperature

Extreme atmospheric-marine events, known as medicanes (short for “Mediterranean hurricanes”), have affected the Mediterranean basin in recent years, resulting in extensive coastal flooding and storm surges, and have occasionally been responsible for several casualties. Considering that the development mechanism of these events is similar to tropical cyclones, it is plausible that these phenomena are strongly affected by sea surface temperatures (SSTs) during their development period (winter and autumn seasons). In this study, we compared satellite data and the numerical reanalysis of SSTs from 1969 to 2023 with in situ data from dataloggers installed at different depths off the coast of southeastern Sicily as well as from data available on Argo floats on the Mediterranean basin. A spectral analysis was performed using a continuous wavelet transform (CWT) for each SST time series to highlight the changes in SSTs prior to the occurrence of Mediterranean Hurricanes as well as the energy content of the various frequencies of the SST signal. The results revealed that decreases in SST occurred prior to the formation of each Mediterranean hurricane, and that this thermal drop phenomenon was not observed in intense extra-tropical systems. The spectral analyses revealed that high CWT coefficients representing high SST energy contents were observed before the occurrence of a Mediterranean hurricane. This information may provide a useful fingerprint for distinguishing Mediterranean hurricanes from common seasonal storms at the onset of these events.

Investigating the Joint Probability of High Coastal Sea Level and High Precipitation

The design strategies for flood risk reduction in coastal towns must be informed by the likelihood of flooding resulting from both precipitation and coastal storm surge. This paper discusses various bivariate extreme value methods to investigate the joint probability of the exceedance of thresholds in both precipitation and sea level and estimate their dependence structure. We present the results of the dependence structure obtained using the observational record at Bridgeport, CT, a station with long data records representative of coastal Connecticut. Furthermore, we evaluate the dependence structure after removing the effects of harmonics in the sea level data. Through this comprehensive analysis, our study seeks to contribute to the understanding of the joint occurrence of sea level and precipitation extremes, providing insights that are crucial for effective coastal management.

Perception of climate change impacts, urbanization, and coastal planning in the Gaeta Gulf (central Tyrrhenian Sea): A multidimensional approach

<abstract> <p>The coasts, with their intricate combination of natural and anthropogenic fragilities, can always be considered a crucial component in the geography of risk and territorial governance. Furthermore, coastal areas worldwide are currently facing profound and immediate impacts of climate change, presenting unparalleled challenges for both ecosystems and coastal communities. In these contexts, high socio-environmental vulnerability has often been linked to planning and management practices that, at times, have exacerbated coastal exposure, making it more prone to extreme natural phenomena, such as coastal floods and storm surges, as well as degradation. The case of the Gaeta Gulf, a largely urbanized part of the central Tyrrhenian coast in Italy that encompasses two administrative areas between the northern Campania and the southern Lazio Regions, provides an opportunity to investigate these criticalities both along the coastline and within the interconnected inland areas. This research aims to understand how administrations and communities perceive, experience, and understand the coastal risks and challenges posed by climate change, as well as their level of information and preparedness to address such risks. These aspects will be analyzed through a multidisciplinary approach, shedding light on the political, social, environmental, and economic practices in these areas, and the potential implications for coastal planning policies. In addition, this contribution presents the results of a qualitative survey involving the administration of questionnaires related to the perception of climate change impacts on the coasts and the level of information on the mitigation and adaptation practices within the communities living in these areas.</p> </abstract>

Assessing Storm Surge Multiscenarios Based on Ensemble Tropical Cyclone Forecasting

AbstractEnsemble forecasting is a promising tool to aid in making informed decisions against risks of coastal storm surges. Although tropical cyclone (TC) ensemble forecasts are commonly used in operational numerical weather prediction systems, their potential for disaster prediction has not been maximized. Here we present a novel, efficient, and practical method to utilize a large ensemble forecast of 1,000 members to analyze storm surge scenarios toward effective decision making such as evacuation planning and issuing surge warnings. We perform the simulation of TC Hagibis (2019) using the Japan Meteorological Agency's (JMA) nonhydrostatic model. The simulated atmospheric predictions were utilized as inputs for a statistical surge model named the Storm Surge Hazard Potential Index to estimate peak surge heights along the central coast of Japan. We show that Pareto‐optimized solutions from an ensemble storm surge forecast can describe potential worst (maximum) and optimum (minimum) storm surge scenarios. These solutions exemplify a diversity of trade‐off surge outcomes across diverse coastal locations, reflecting variations in coastal geometry, including bathymetry. For example, some of the Pareto‐optimized solutions that illustrate worst surge scenarios for inner bay locations are not necessarily accountable for bringing severe surge cases in open coasts. We further emphasize that an in‐depth evaluation of Pareto‐optimal solutions can shed light on how meteorological variables such as track, intensity, and size of TCs influence the worst and optimum surge scenarios, which is not clearly quantified in current multiscenario assessment methods such as those used by JMA/National Hurricane Center in the United States.

Assessing the Potential Impacts of Climate Change on Current Coastal Ecosystems—A Canadian Case Study

Understanding how climate change affects coastal ecosystems is one of the most important elements in determining vulnerability and resilience for long-term ecosystem management in the face of the increasing risk of coastal hazards (e.g., sea level rise, coastal flooding, and storm surge). This research attempts to undertake a study on the ecosystem–climate nexus in the Canadian province of Prince Edward Island (PEI). Cloud-based remote sensing techniques with Google Earth Engine (GGE) are utilized to identify ecosystem changes over time. In addition, the effects of coastal flooding and storm surge ecosystems under different climate scenarios are examined. The results suggest a reduction in the forest (3%), open water or marsh component (9%), salt water (5%), no open water or marsh component (3%), and salt or brackish marsh (17%) ecosystems from 2013 to 2022. Dune and beach exhibit a non-uniform distribution across the period because of variations in natural processes, with an upward trend ranging from 0% to 11%. Approximately 257 km2 (9.4%) of PEI’s ecosystems would be affected by extreme coastal flooding (scenario 4), compared to 142 km2 (5.2%), 155 km2 (5.7%), and 191 km2 (7%) in scenarios 1, 2, and 3, respectively. Under a 4 m storm surge scenario, around 223 km2 (8.2%) of PEI’s ecosystems would be flooded, compared to 61 km2 (2.2%), 113 km2 (4.1%), and 168 km2 (6.1%) under 1 m, 2 m, and 3 m scenarios, respectively. The findings from this research would enable policymakers to take necessary actions to sustain ecosystem services in PEI while confronting the impacts of climate change.

Learning From Disaster: What Two Hurricanes Reveal About Ways to Design Public Space as Flood Infrastructure

Abstract This article examines the resilience of two urban parks in the United States after extreme flooding caused by separate hurricane events. It provides early lessons for designers, planners, and engineers of open and park space from a practice-based research group and two academic partnerships. The first site is coastal, a waterfront park in New York City, New York. The focus was on understanding how elements of the design and construction of Hunter’s Point South Waterfront Park, Phase 1, contributed to a high level of resilience during and after Hurricane Sandy, especially related to coastal flooding, storm surge, and heavy rains. The second site is on the principal river system in Houston, Texas. The focus was on understanding how elements of the design and construction of a 160-acre section of Buffalo Bayou Park contributed to a high level of resilience during and after Hurricane Harvey, which brought heavy rains, increased water velocity, and extended submergence.

Temporal changes in dependence between compound coastal and inland flooding drivers around the contiguous United States coastline

Flooding in low-lying coastal zones arises from coastal (storm surge, tides, and waves), fluvial (excessive river discharge), and pluvial (excessive surface runoff) drivers. We analyse changes in compound flooding potential around the contiguous United States (CONUS) coastline stemming from select combinations of these flooding drivers using long observational records with at least 55 years of data. We assess temporal changes in the tail (extremal) dependence (χ) using a 30-year sliding time window. Periods of strong tail dependence are found for the windows centered between the 1960s and 1980s/1990s at several locations for surge-discharge (S-Q) and surge-precipitation (S–P) combinations. Changes in dependence are associated with large-scale climate indices such as the Arctic Oscillation (AO) and El Nino Southern Oscillation indices (Niño 1.2 and Niño 3), among others. The significance of potential changes in the dependence structure is subsequently tested using Kullback–Leibler (KL) divergence. We find that changes are mostly not significant. Finally, we perform a complete multivariate statistical analysis exemplarily for one selected pair of variables at one location (S-Q in Washington, DC), allowing for varying dependence strength and structure as well as changes in the marginal distributions. Combined changes with increase in the dependence and marginals exacerbate the predicted compound flood potential. The comprehensive analysis presented here provides new insights into how and where compound flooding potential has changed with time, demonstrates associated links with large-scale climate indices, and highlights the effects of changes in the dependence and marginals in a multivariate statistical framework.

Plant trait-mediated drag forces on seedlings of four tidal marsh pioneer species

Salt marshes play an important role in coastal protection by reducing the impact of waves and shoreline erosion risks. While mature vegetation is responsible for the persistence and stability of marsh ecosystems, seedling survival of pioneer species is especially crucial for marsh propagation. Marsh seedlings, however, may be threatened by climate change induced increased coastal storm surge intensity and accompanying (extreme) wave conditions, imposing stronger drag forces on marsh seedlings. We test the hypothesis that drag forces experienced by seedlings increase with horizontal orbital velocity (Uw) in a species-specific manner, and that the drag forces experienced are individual-plant trait-mediated. To test our hypotheses, seedlings of four contrasting pioneer marsh species (Bolboschoenus maritimus, Schoenoplectus tabernaemontani, Spartina anglica, and Puccinellia maritima) were exposed to storm wave conditions in a flume, where Uw and experienced drag forces were measured. Linear mixed effect models demonstrated that seedling’s susceptibility to storm wave conditions is at least partly mediated by individual plant traits. Drag forces experienced by seedlings tended to increase with Uw, and with stem length and diameter. The interplay of both traits was complex, with increasing stem length being the most important trait accounting for increases in drag forces experienced at low to moderate Uw, while the stem diameter became more important with increasing Uw. Furthermore, experienced drag forces appeared to be affected by species-specific traits such as rigidity and leaf growth, being highest for Bolboschoenus maritimus and lowest for Puccinellia maritima. Our results provide important mechanistic insights into the drivers of tidal marsh seedling vulnerability to storm wave conditions due to experienced drag, both based on the traits of individual plants and species-specific ones. This type of knowledge is of key importance when modelling saltmarsh establishment and resilience under climate change.

Changes in Tropical Cyclones Undergoing Extratropical Transition in a Warming Climate: Quasi‐Idealized Numerical Experiments of North Atlantic Landfalling Events

AbstractThe current study extends earlier work that demonstrated future extratropical transition (ET) events will feature greater intensity and heavier precipitation to specifically consider potential changes in the impacts of landfalling ET events in a warming climate. A quasi‐idealized modeling framework allows comparison of highly similar present‐day and future event simulations; the model initial conditions are based on observational composites, increasing representativeness of the results. The future composite ET event features substantially more impactful weather conditions in coastal areas, with heavier precipitation and greater storm intensity. Specifically, a Category 2 present‐day storm attained Category 4 Saffir‐Simpson intensity in the future simulation and maintained greater intensity throughout the entire life cycle, although the storm undergoes less reintensification during the post‐ET process, a result of reduced baroclinic conversion. These findings suggest increased potential for coastal hazards due to stronger tropical cyclone winds and heavier rainfall, leading to more severe coastal flooding and storm surge.

Foredune growth and storm surge protection potential at the Eiderstedt Peninsula, Germany

In the context of climate change and associated sea level rise, coastal dunes can provide an essential contribution to coastal protection against wave attack and flooding. Since dunes are highly dynamic systems, their potential safety levels are related to their long-term development, varying in time and space, however pertinent research that ties those aspects together are generally scarce. The objective of this study is to analyze the long-term development of a young coastal foredune at the Eiderstedt peninsula, Germany and assess its coastal protection potential. This research presents (i) a novel semi-automated Dune Toe Tracking (DTT) method to systematically extract dune toes from cross-shore elevation profiles; (ii) established tools to derive the extraction of characteristic dune parameters and (iii) a newly defined Critical Storm Surge Level (CSSL) to relate spatio-temporal dune growth with coastal storm surge protection. Based on geospatial survey data, initial dune formation was identified in the 1980s. By 2015, the foredune had developed over a 6.5 km coastal stretch with a mean annual growth of 7.4m³/m. During the course of dune evolution, the seaward dune toe shifted seaward by an average of 2.3m/yr, while simultaneously increasing in height by an average of 1.1 cm/yr. Overall, the foredune formation established a new line of defense in front of an existing dike/dune line that provides spatially varying protection against a mean CSSL of 3.4m + NHN and can serve as an additional buffer against wave attack during severe storm events.

An experimental study of mitigating coastal dune erosion by using bio-carbonization of reactive magnesia cement

Due to coastal storm surge and wave or man-made activities, widespread coastal erosion events are emerging. In this study, the feasibility of bio-carbonation of reactive magnesium cement (RMC) to mitigate coastal erosion was investigated by conducting laboratory-scale wave erosion tests. The accumulative erosion volume (V), erosion resistance duration (Dre), and volume erosion rate (VIS) were calculated to evaluate the erosion resistance of sand dunes with the different cement thickness (T = 3 mm, 4 mm, and 5 mm) and RMC content (R = 1%, 1.5%, and 2%). The surface penetration resistance and the cementation product content (brucite/hydrated magnesia carbonates (HMCs)) were also measured to assess the effectiveness of bio-carbonation in sand dunes. Results show that in comparison with RMC hydration, the VIS decreased by 77%, Dre increased by 333%, and peak penetration resistance increased by 42% after the bio-carbonation treatment of sand dunes. Further improvements in these results were obtained with increasing T or R. Given varying T or R, we identify two types of erosion process responses under wave action. For bio-carbonation treatment with higher T or R, the erosion process response follows four phases. In contrast, for hydration treatment, or bio-carbonation treatment with lower T or R, Phase II does not exist because of small crust thickness or weak bond. The presentation of Phase II effectively delays the slope failure depending on larger erosion volume (V ≥ 93 cm3) and turns sudden into flexible failure. Scanned electron microscopy observations further revealed that HMCs formed by RMC bio-carbonation provided better filling and cementation effects than brucite formed by RMC hydration, however, massive amounts of HMCs concentrated in the shallow surface layer, causing hindered penetration and reducing the number of cementation products at higher depths.

PyVF: A python program for extracting vertical features from LiDAR-DEMs

Coastal and riverine flooding is one of the most common environmental hazards that affect billions of people worldwide. A coupled hydrologic and coastal storm surge simulation is required to develop an improved understanding of the individual and collective mechanisms that can cause flooding within watersheds. These simulations are dependent on an accurate digital elevation model (DEM); however, it is a challenge to include numerical model resolution as fine as contemporary DEMs due to the enormous computational cost. Therefore, significant vertical features (VFs) such as roadbeds, levees, railroads, and natural ridges must be identified and considered in developing the model representation of the DEM since the VFs can affect flow propagation. PyVF is an open-source program to extract significant VFs from a high-resolution, bare-earth, LiDAR-derived DEM automatically. This paper introduces the methods and shows the automated extraction of VFs for a coastal, urban, mountain and beach area.

Dynamic restoration and the impact of native versus invasive vegetation on coastal foredune morphodynamics, Lanphere Dunes, California, USA

AbstractThe Lanphere Dunes, part of the Humboldt Bay National Wildlife Refuge, has been the focus of foredune restoration efforts since the 1980s. Efforts have centred around removal of an invasive European beach grass species, Ammophila arenaria, introduced in the early 1900s to stabilize the dunes to protect landward communities from coastal flooding and storm surges. Despite effectively stabilizing the foredune, A. arenaria forms monotypic vegetation stands, with highly dense roots, rhizomes, and above‐ground biomass that can lead to pronounced scarping of the seaward slope, alongshore steering of wind and sediment, a lack of landward transfer of sand, and a steeper, more peaked profile.Effective foredune restoration must consider the coupled interactions between dominant plant type and the geomorphic processes that influence dune form. A 5 ha reach of recently restored foredune was monitored biannually with terrestrial laser scanner and uncrewed aerial systems platforms between 2015 and 2021 to characterize the impacts of dynamic restoration on foredune form and resiliency. This reach included two control plots: (1) native, non‐restored and (2) invasive, and three restored plots revegetated with native species: (3) a native grass (Elymus mollis), (4) a low‐lying herb and subshrub assemblage, and (5) a mixture of the native grass, herbs, and subshrubs.After five growing seasons, restored plots exhibited distinct geomorphic and sediment budget differences. Natively vegetated plots recovered from extensive scarping 2 years faster than the invasive plot. Restored plots saw foredune height (0.5–0.7 m) and width increase, landward extension (1 m) while maintaining a similar seaward position, and positive lee‐slope sediment budgets that exceeded both control plots (up to 0.015 m3 m−2 month−1). These results suggest that the native vegetation plots allowed increased landward sand transport across the foredune, and increased the capacity of the foredune to recover more quickly following dune scarping.

Model Simulation of Storm Surge in the Northwestern South China Sea Under the Impact of Sea Level Rise: A Case Study of Super Typhoon Rammasun (2014)

Because of global warming, the sea level is expected to continue to rise, possibly having a significant impact on the intensities and spatial distribution characteristics of coastal storm surges. In this study, we took super typhoon Rammasun (2014) as a case study and applied the SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model) to simulate storm surge in the northwestern South China Sea under future sea level rise (SLR) scenarios. To improve the accuracy of storm surge hindcast, we used reconstructed wind field to drive the model in which ERA5 reanalysis data were superposed on the wind field calculated from the Holland parametric cyclone model. The results show that the storm surge hindcast was significantly improved by using this reconstructed wind forcing. 2-D and 3-D model hindcast capabilities were compared; the 3-D model reproduced the storm surge better. The regional sea level projections in 2050, 2100, 2200, and 2300 for RCP 4.5 scenarios (provided by the IPCC AR6 dataset) were superposed on the original water depth as the predicted sea levels, then those depths were used in models of storm surge in the study area under a typhoon identical to Rammasun. Model results demonstrate that storm surge peaks in most sea areas decrease nearly linearly with SLR, especially in regions of high surges.

Impact of Coastal Disasters on Women in Urban Slums: A New Index

Coastal hazards, particularly cyclones, floods, erosion and storm surges, are emerging as a cause for major concern in the coastal regions of Vijayawada, Andhra Pradesh, India. Serious coastal disaster events have become more common in recent decades, triggering substantial destruction to the low-lying coastal areas and a high death toll. Further, women living in informal and slum housing along the Vijayawada coastline of Andhra Pradesh (CAP), India, suffer from multiple social, cultural and economic inequalities as well. These conditions accelerate and worsen women’s vulnerability among this coastal population. The existing literature demonstrates these communities’ susceptibility to diverse coastal disasters but fails to offer gender-specific vulnerability in urban informal housing in the Vijayawada area. Accordingly, the current study developed a novel gender-specific Women’s Coastal Vulnerability Index (WCVI) to assess the impact of coastal disasters on women and their preparedness in Vijayawada. Field data was collected from over 300 women through surveys (2) and workshops (2) between November 2018 and June 2019, and Arc-GIS tools were used to generate vulnerability maps. Results show that women are more vulnerable than men, with a higher death rate during coastal disaster strikes. The current study also found that gender-specific traditional wear is one of the main factors for this specific vulnerability in this area. Furthermore, the majority of the women tend to be located at home to care for the elders and children, and this is associated with more fatalities during disaster events. Homes, particularly for the urban poor, are typically very small and located in narrow and restricted sites, which are a barrier for women to escape from unsafe residential areas during disasters. Overall, the research reveals that most of the coastal disaster events had a disproportionately negative impact on women. The results from this present study offer valuable information to aid evidence-based policy- and decision-makers to improve existing or generate innovative policies to save women’s lives and improve their livelihood in coastal areas.

A GIS-based Screening Workflow for Coastal Storm Surge Impact Assessments and Mitigation Action Consideration

Balstrøm, T. and Kirby, J., 2022. A GIS-based screening workflow for coastal storm surge impact assessments and mitigation action consideration. Journal of Coastal Research, 38(4), 712–724. Coconut Creek (Florida), ISSN 0749-0208. A GIS-based screening workflow is presented, providing first overviews of storm surge–induced inundation impacts along coastlines and where to consider mitigative action. The modeling is based on analysis of a hydro-conditioned digital terrain model (DTM) in Esri's ArcGIS Pro environment targeting undergraduate students, professional municipality planners, federal agencies, and more. Unlike existing commercial inundation modeling software, this application works in a simplified timeless setting on steady-state surge levels. This is accomplished only at the cost of not predicting when a specific targeted location is inundated. In return, fast computations are obtained. First, it is demonstrated how the DTM is turned into a hydro-conditioned terrain model, DHyMSea, protecting surges from entering land where sluices, high-water flaps, etc., are present. Second, the inundation screening is initiated for a user-defined number of sea levels. The outputs are individual raster layers for each level showing inundation extents and depths. Also, outputs are produced for each modeled level to back trace where the inundation came from. Third, a combined raster shows the minimum surge level to inundate any cell in the DHyMSea. Fourth, when considered where to raise protecting dikes, they can be digitized and have their elevation values stamped onto the DHyMSea. Finally, the inundation scenarios can be re-executed to evaluate the mitigation impact; if necessary, the dikes' locations and elevation properties can be reconsidered, and the workflow re-executed once more. The workflow has proven successful in first assessments of inundation threats where sea levels are expected to rise significantly over the coming decades. Additionally, the workflow has proven successful in quality assessments of a DTM. To demonstrate the workflow's capabilities, storm surge consequences for the greater Copenhagen region's coastline in Denmark are discussed for inundation scenarios ranging from 1.0 m to 3.9 m above sea level in steps of 0.1 m.