Coastal Flood Hazard Research Articles

Time‐Varying Emulator for Short and Long‐Term Analysis of Coastal Flood Hazard Potential

AbstractRising seas coupled with ever increasing coastal populations present the potential for significant social and economic loss in the 21st century. Relatively short records of the full multidimensional space contributing to total water level coastal flooding events (astronomic tides, sea level anomalies, storm surges, wave run‐up, etc.) result in historical observations of only a small fraction of the possible range of conditions that could produce severe flooding. The Time‐varying Emulator for Short‐ and Long‐Term analysis of coastal flood hazard potential is presented here as a methodology capable of producing new iterations of the sea‐state parameters associated with the present‐day Pacific Ocean climate to simulate many synthetic extreme compound events. The emulator utilizes weather typing of fundamental climate drivers (sea surface temperatures, sea level pressures, etc.) to reduce complexity and produces new daily synoptic weather chronologies with an auto‐regressive logistic model accounting for conditional dependencies on the El Niño Southern Oscillation, the Madden‐Julian Oscillation, seasonality, and the prior two days of weather progression. Joint probabilities of sea‐state parameters unique to simulated weather patterns are used to create new time series of the hypothetical components contributing to synthetic total water levels (swells from multiple directions coupled with water levels due to wind setup, temperature anomalies, and tides). The Time‐varying Emulator for Short‐ and Long‐Term analysis of coastal flood hazard potential reveals the importance of considering the multivariate nature of extreme coastal flooding, while progressing the ability to incorporate large‐scale climate variability into site specific studies assessing hazards within the context of predicted climate change in the 21st century.

Advancing global storm surge modelling using the new ERA5 climate reanalysis

This study examines the implications of recent advances in global climate modelling for simulating storm surges. Following the ERA-Interim (0.75° × 0.75°) global climate reanalysis, in 2018 the European Centre for Medium-range Weather Forecasts released its successor, the ERA5 (0.25° × 0.25°) reanalysis. Using the Global Tide and Surge Model, we analyse eight historical storm surge events driven by tropical—and extra-tropical cyclones. For these events we extract wind fields from the two reanalysis datasets and compare these against satellite-based wind field observations from the Advanced SCATterometer. The root mean squared errors in tropical cyclone wind speed reduce by 58% in ERA5, compared to ERA-Interim, indicating that the mean sea-level pressure and corresponding strong 10-m winds in tropical cyclones greatly improved from ERA-Interim to ERA5. For four of the eight historical events we validate the modelled storm surge heights with tide gauge observations. For Hurricane Irma, the modelled surge height increases from 0.88 m with ERA-Interim to 2.68 m with ERA5, compared to an observed surge height of 2.64 m. We also examine how future advances in climate modelling can potentially further improve global storm surge modelling by comparing the results for ERA-Interim and ERA5 against the operational Integrated Forecasting System (0.125° × 0.125°). We find that a further increase in model resolution results in a better representation of the wind fields and associated storm surges, especially for small size tropical cyclones. Overall, our results show that recent advances in global climate modelling have the potential to increase the accuracy of early-warning systems and coastal flood hazard assessments at the global scale.

Development of a coastal vulnerability index using analytical hierarchy process and application to Ravenna province (Italy)

The assessment of coastal vulnerability to natural hazards is a major concern in coastal areas worldwide, particularly in the context of climate change and increased coastal development. In this work an index of physical vulnerability to sea level rise and marine floods was designed and applied over the coast of the Ravenna Province (Italy), a low-lying coastal area historically known as being susceptible to coastal flooding and erosion. The index is intended to be at the same time scientifically sound and easy to apply, so it is composed of five relevant variables (elevation, dunes, artificial protection structures, shoreline change rates, and land cover) that were weighted by using a multi-criteria decision making approach, namely the analytical hierarchy process. The weightings were assigned by experts familiar with coastal processes in the area, and all with background in environmental science. This enabled a transparent approach on integrating established expert knowledge to assign the relative importance of the variables in defining vulnerability scores. The final vulnerability score for each segment along the investigated coast was calculated by applying the weighted sum of all variables. For verification purposes, the obtained vulnerability ranking was compared to existing coastal flood hazard maps developed by regional authorities in the framework of the EU Floods Directive (2007/60/EC), and to real inundation events generated by historical storms. The integration of this framework into geographical information systems resulted in informative maps, useful to a variety of end-users such as coastal managers and decision makers.

Impact of storm propagation speed on coastal flood hazard induced by offshore storms in the North Sea

Storm propagation speed (SPS) can noticeably impact coastal floods around semi-closed basins influenced by extratropical offshore storms. As a case study, the SPS impact on potential flood hazards due to extreme water levels along the UK east coast was studied using a numerical shelf sea model (FVCOM). The storm Xaver, which caused the largest North Sea surge over the past 60 years, was studied as a base scenario. Halving/doubling the SPS results in a smaller surge and a longer/shorter surge duration. Hence, the largest peak water level was found at actual speed, while the largest potential flood hazard occurred at half speed. Tide–surge interaction tends to reduce the M2 tide along the coast and advance its propagation for all SPS. A three-dimensional semi-analytical model, including a time-periodic wind forcing, was used to investigate the dominant mechanisms behind the surge dynamics, where wind duration is directly related to the SPS. Long wind durations correspond to small SPS, and vice versa. The semi-analytical model was applied to the North Sea. The model reproduces the spatial features of the North Sea surge and its dependence on SPS, confirming the surge induced by offshore storms is primarily associated with wind set-up. Model results suggest the SPS of Xaver is likely to have contributed greatly to the occurrence of the largest North Sea surge due to wind-generated resonance. The impact of the SPS on the surge and tide–surge interaction are of great importance to coastal flood hazard assessment.

Quantifying road vulnerability to coastal hazards: Development of a synthetic index

As part of a collaborative study with the Ministry of Transport of Québec, a Coastal Road Erosion and Flooding Vulnerability Index (CREFVI) was developed for the short (2020), medium (2060) and long term (2100). Nine study sites in Eastern Québec (Canada) were used to develop the index, for a total of 122.4 km of roads. The index includes 14 parameters relating to the following: the exposure of a site to erosion and coastal flooding hazard; the characteristics of the road segment; the characteristic of the road network; and adaptation to erosion (e.g. the presence of defence structures). Each parameter received a score between 1 and 5 according to its propensity to increase (5) or not (1) the vulnerability of the road. CREFVI values for the study sites vary between 0 and 159.1 and have been divided into 5 classes reflecting the actions needed to reduce the site's vulnerability: Not vulnerable (no intervention necessary), Low, Medium, High, Critical (immediate intervention required). For the roads analyzed, 0.5 km have a critical CREFVI value as of 2020, 1.7 km as of 2060 and 2.6 km by 2100. Currently, only 20.6% of the road segments are vulnerable to coastal hazards, but this percentage rises to 36.4% by 2060 and to 54.3% by 2100. This index is an important decision-making tool for improving road management, prioritizing future actions and determining which parameters require intervention.

Differences in assigning probabilities to coastal inundation hazard estimators: Event versus response approaches

AbstractCoastal flood risk assessment requires a reliable estimation of the frequency of inundation hazards, that is, characterising the hazard magnitude and assigning a probability of occurrence. In this work we analyse the uncertainty introduced in the assessment associated to the method to assign the probability of occurrence to coastal flood hazards. To this end we have compared the use of two general methods, the response and the event approaches. Different procedures are used to characterise coastal inundation hazards depending on the analysis scale and data availability. Thus, a range of possibilities has been analysed, from simple estimators such as run‐up to modelled flood‐prone areas. The analysis has been performed for all wave and water level conditions around the Spanish coast. The results show that the differences between the methods are location‐dependent, and thus, determined by the exposure to wave and water level conditions. When using the event approach, the run‐up or total water level (with good correlation between waves and surge) distributions reasonably approximate those of the response approach with low associated uncertainty. When the assessment aims to output overtopping discharges or inundation maps, observed differences suggest that the event approach would produce misleading conclusions in inundation‐related coastal management and decision‐making.

A flood inundation forecast of Hurricane Harvey using a continental-scale 2D hydrodynamic model

Forecasts of tropical cyclones have seen rapid improvements in recent years as expanding computational capacity permits more runs of finer resolution meteorological models with increasing representation of physical processes. However, the utilization of a hydrodynamic component in these models is often neglected, meaning flood forecasts typically output point water levels that give little indication of a projected inundation extent on the ground. Here, we append this critical component to the forecast cascade by coupling Fathom-US, a continental-scale hydraulic model which employs the LISFLOOD-FP numerical scheme, to forecasts of streamflow, rainfall and coastal surge height from the National Oceanic and Atmospheric Administration (NOAA). Medium-term (2–15 days) flood inundation forecasts, as well as hindcasts driven by real-time observations, were executed for Hurricane Harvey by rapidly simulating pluvial and coastal flood hazard and extracting fluvial flood maps from an existing US-wide simulation library. The resultant ~30 m resolution depth grids were then validated against post-event observations collated by the US Geological Survey. Across the disaster zone, the hindcast (forecast) model captured, on average, 78% (75%) of the benchmark flood extent, obtained a Critical Success Index of 0.66 (0.57) and deviated from observed high water marks by ~1 m (~1.2 m). When compared to a simpler GIS-based approach, the hydraulic model exhibited much higher skill in replicating observations. This study shows that fully hydrodynamic approaches can be practicably employed in large-scale forecast frameworks at high resolution to produce skillful projections of inundation extent without significantly affecting the forecast lead time.

A methodology for urban micro-scale coastal flood vulnerability and risk assessment and mapping

One of the most dangerous challenges to settlements in the UK comes from flooding. Currently, there is extensive map coverage of flood hazards zones in the UK; however, it is increasingly recognised that risk associated with natural hazards cannot be reduced solely by focussing on the hazard. There is also an urgent need for methods of evaluating and mapping flood vulnerability and risk in detail. Despite its significance, conventional flood risk assessment methodologies often underestimate likely levels of vulnerability in areas prone to hazards, yet it is the degree of vulnerability within a community that determines the consequences of any given hazard. The research presented proposes a general methodology to assess and map Coastal Flood Vulnerability and Risk at a detailed, micro-scale level. This captures aspects that are considered crucial and representative of reality (socio-economic, physical and resilient features). The methodology is then applied to a UK case study (city of Portsmouth). Environment Agency flood hazard data, National Census socio-economic data and Ordnance Survey topographic map data have been used to evaluate and map coastal flood vulnerability, examining neighbourhoods within census wards. This led to a subsequent analysis of Coastal Flood Risk, via the combination of a Coastal Flood Vulnerability Index and a Coastal Flood Hazard Index, for the Portsmouth ward Hilsea. This, consequently, identifies potential weaknesses that could lead to more effective targeting of interventions to improve resilience and reduce vulnerability in the long term and provides a basis for hazard and environmental managers/planners to generate comprehensive national/international vulnerability and risk assessments.

Increased coastal wave hazard generated by differential wind and wave direction in hyper-tidal estuaries

Wave overtopping and subsequent coastal flood hazard is strongly controlled by wind and water levels, and is especially critical in hyper-tidal estuaries where even small changes in wave heights can be catastrophic if they are concurrent with high spring tide. Wave hazard in estuaries is largely attributed to high amplitude shorter period, locally generated wind waves; while low amplitude longer period waves rarely impact low-lying coastal zones up-estuary. Here, the effect of wind and wave properties on up-estuary wave propagation and the sensitivity of significant wave height are investigated numerically along the shoreline of the Severn Estuary, southwest England, as an example. Representative values for wind speed and direction, wave height, period and direction are used to identify key combinations of factors that define the wave hazard generation. High amplitude, short period wind waves are sensitive to opposing winds, with a steepening effect that varies along the estuary shoreline, highlighting the effect of estuarine geometry on wave hazard. Low amplitude, long period wind waves respond with maximum variability in significant wave height to strong winds resulting in their propagation further up-estuary. Our results advance current understanding of the compound interaction between wind and waves, and identify critical conditions maximizing the hazard and hazard variability along the shoreline. The outcomes from this research can help to avoid economic losses from operational downtime in ports and harbors, inform sustainable coastal sea defense design and understand how wave hazard may vary under future climate due to changing storm tracks. Results can also be applied to the design of coastal infrastructure and facilitation of emergency response planning.

Coastal Flooding Hazard Due to Overflow Using a Level II Method: Application to the Venetian Littoral

In recent years, marine flooding and its impacts have become a question of growing interest, since coastal areas are the most heavily populated and developed land zones in the world. This paper presents a rapid tool for mapping at regional scale the hazard associated with coastal flooding due to overflow. The tool merges a recently developed numerical model that solves a simplified form of the Shallow-Water Equations and is suited for Graphic Processing Unit (GPU) acceleration, with a Level II reliability method that allows producing hazard maps of inland flooding propagation. The procedure was applied to two stretches of the Venetian littoral, i.e., Valle Vecchia and Caorle, located in the northern Adriatic Sea. The application includes the site descriptions and the resulting hazard maps that show the probability of failure in each point of the coast for a given inland inundation level.

ASSESSING NON-LINEAR RESPONSE IN EXTREME COASTAL WATER LEVELS

Rising sea levels and the resultant amplification of flood frequencies and magnitude has the potential to significantly change coastal flood hazards over the coming century. The Federal Emergency Management Agency (FEMA) has recognized the potential future implications of Sea Level Rise (SLR) on coastal hazards and flood insurance. However, at present, FEMA does not incorporate future conditions information in to their regulatory or non-regulatory products in the framework of their National Flood Insurance Program. Many other programs that create products to support risk recognition and resilient planning are based on “bathtub” approaches (for example NOAA’s Sea Level Rise Viewer: https://coast.noaa.gov /digitalcoast/tools/slr). In order to better understand non-linear changes in coastal flood hazards, due to increased water depth and wave heights, or in the surge propagation pathway, FEMA has funded a series of pilot studies. For this study an end-of-the-century SLR condition has been imposed on storm surge simulations in West Florida to gain further understanding into how SLR may modify surge and wave effects, as well as potential techniques for approximating these via efficient approximate methods. Both the detailed nonlinear methods and approximate linear approaches for developing SLR advisory information will be evaluated and compared for this study. A second, mid-century SLR condition was utilized for a shoreline change analysis to evaluate how recession due to SLR may affect coastal flood hazards.

Analysis of the risk associated with coastal flooding hazards: a new historical extreme storm surges dataset for Dunkirk, France

Abstract. This paper aims to demonstrate the technical feasibility of a historical study devoted to French nuclear power plants (NPPs) which can be prone to extreme coastal flooding events. It has been shown in the literature that the use of historical information (HI) can significantly improve the probabilistic and statistical modeling of extreme events. There is a significant lack of historical data on coastal flooding (storms and storm surges) compared to river flooding events. To address this data scarcity and to improve the estimation of the risk associated with coastal flooding hazards, a dataset of historical storms and storm surges that hit the Nord-Pas-de-Calais region during the past five centuries was created from archival sources, examined and used in a frequency analysis (FA) in order to assess its impact on frequency estimations. This work on the Dunkirk site (representative of the Gravelines NPP) is a continuation of previous work performed on the La Rochelle site in France. Indeed, the frequency model (FM) used in the present paper had some success in the field of coastal hazards and it has been applied in previous studies to surge datasets to prevent coastal flooding in the La Rochelle region in France. In a first step, only information collected from the literature (published reports, journal papers and PhD theses) is considered. Although this first historical dataset has extended the gauged record back in time to 1897, serious questions related to the exhaustiveness of the information and about the validity of the developed FM have remained unanswered. Additional qualitative and quantitative HI was extracted in a second step from many older archival sources. This work has led to the construction of storm and coastal flooding sheets summarizing key data on each identified event. The quality control and the cross-validation of the collected information, which have been carried out systematically, indicate that it is valid and complete in regard to extreme storms and storm surges. Most of the HI collected is in good agreement with other archival sources and documentary climate reconstructions. The probabilistic and statistical analysis of a dataset containing an exceptional observation considered as an outlier (i.e., the 1953 storm surge) is significantly improved when the additional HI collected in both literature and archives is used. As the historical data tend to be extreme, the right tail of the distribution has been reinforced and the 1953 “exceptional” event does not appear as an outlier any more. This new dataset provides a valuable source of information on storm surges for future characterization of coastal hazards.

An integration and assessment of multiple covariates of nonstationary storm surge statistical behavior by Bayesian model averaging

Abstract. Projections of coastal storm surge hazard are a basic requirement for effective management of coastal risks. A common approach for estimating hazards posed by extreme sea levels is to use a statistical model, which may use a time series of a climate variable as a covariate to modulate the statistical model and account for potentially nonstationary storm surge behavior (e.g., North Atlantic Oscillation index). Previous works using nonstationary statistical approaches to assess coastal flood hazard have demonstrated the importance of accounting for many key modeling uncertainties. However, many assessments have typically relied on a single climate covariate, which may leave out important processes and lead to potential biases in the projected flood hazards. Here, I employ a recently developed approach to integrate stationary and nonstationary statistical models, and characterize the effects of choice of covariate time series on projected flood hazard. Furthermore, I expand upon this approach by developing a nonstationary storm surge statistical model that makes use of multiple covariate time series, namely, global mean temperature, sea level, the North Atlantic Oscillation index and time. Using Norfolk, Virginia, as a case study, I show that a storm surge model that accounts for additional processes raises the projected 100-year storm surge return level by up to 23 cm relative to a stationary model or one that employs a single covariate time series. I find that the total model posterior probability associated with each candidate covariate, as well as a stationary model, is about 20 %. These results shed light on how including a wider range of physical process information and considering nonstationary behavior can better enable modeling efforts to inform coastal risk management.

Effects of urban development on future multi-hazard risk: the case of Vancouver, Canada

Disaster risk reduction should anticipate how future natural hazard risk would be influenced by changes in urban vulnerability. This paper investigates the effect of one key driver of change, urban development. It models current and future risk for the year 2041 in a rapidly growing urban area, Vancouver, Canada, from both earthquake and coastal flood hazard. Three urban development futures are considered—status quo, compact, and sprawled development—that differ in the housing stock configuration used to accommodate an identical, projected increase in population and dwellings. Results indicate that while exposure is expected to increase substantially in future, the implications for risk vary greatly between hazards and impact types. For earthquake, population increase is attenuated by improvements in the building stock, whereas for flooding, disaster impacts increase at a much higher rate than population growth. Overall, disruption impacts are more sensitive than damage to changes in population and development. The effect of urban development on future risk is not unidirectional, but depends upon hazard type, impact type, and degree of climate change. None of the development futures is consistently best from a risk perspective, but along many dimensions, compact development yields more severe disaster impacts relative to status quo development. The findings underscore the importance of considering natural hazard risk in urban development planning, and of recognizing the inherent differences between hazards and impact types in this planning.

Vulnerability Analysis of the Venetian Littoral and Adopted Mitigation Strategy

This paper discusses the key aspects of the recent Coastal Plan of the Veneto Region (IT). Its aim is to propose a single mitigation strategy for coastal erosion that is valid for the whole Veneto Region, and possibly elsewhere, as well as a method to assign a priority level to any action. The suggested mitigation action against erosion depends on urbanization level, beach width, as well as cross-shore and long-shore sediment transport. The criterion used to give a priority level to mitigation actions is based on a vulnerability index that takes into account erosive tendency, existing coastal flooding hazards, coast value, environmental relevance, tourist pressure, urbanization level, the presence of production activities, and cultural heritage. A sample case featuring the littoral of Rosolina is also provided and includes a site description, the sediment budget, critical issues and possible mitigation measures.

Estimations of statistical dependence as joint return period modulator of compound events – Part 1: Storm surge and wave height

Abstract. The possibility of utilizing statistical dependence methods in coastal flood hazard calculations is investigated since flood risk is rarely a function of just one source variable but usually two or more. Source variables in most cases are not independent as they may be driven by the same weather event, so their dependence, which is capable of modulating their joint return period, has to be estimated before the calculation of their joint probability. Dependence and correlation may differ substantially from one another since dependence is focused heavily on tail (extreme) percentiles. The statistical analysis between surge and wave is performed over 32 river ending points along European coasts. Two sets of almost 35-year hindcasts of storm surge and wave height were adopted, and results are presented by means of analytical tables and maps referring to both correlation and statistical dependence values. Further, the top 80 compound events were defined for each river ending point. Their frequency of occurrence was found to be distinctly higher during the cold months, while their main low-level flow characteristics appear to be mainly in harmony with the transient nature of storms and their tracks. Overall, significantly strong values of positive correlations and dependencies were found over the Irish Sea; English Channel; and south coasts of the North Sea, Norwegian Sea, and Baltic Sea, with compound events taking place in a zero-lag mode. For the rest, mostly positive moderate dependence values were estimated even if a considerable number of them had correlations of almost zero or even a negative value.

Global probabilistic projections of extreme sea levels show intensification of coastal flood hazard

Global warming is expected to drive increasing extreme sea levels (ESLs) and flood risk along the world’s coastlines. In this work we present probabilistic projections of ESLs for the present century taking into consideration changes in mean sea level, tides, wind-waves, and storm surges. Between the year 2000 and 2100 we project a very likely increase of the global average 100-year ESL of 34–76 cm under a moderate-emission-mitigation-policy scenario and of 58–172 cm under a business as usual scenario. Rising ESLs are mostly driven by thermal expansion, followed by contributions from ice mass-loss from glaciers, and ice-sheets in Greenland and Antarctica. Under these scenarios ESL rise would render a large part of the tropics exposed annually to the present-day 100-year event from 2050. By the end of this century this applies to most coastlines around the world, implying unprecedented flood risk levels unless timely adaptation measures are taken.

Probabilistic mapping of storm-induced coastal inundation for climate change adaptation

This paper describes a probabilistic approach for mapping of coastal flood hazards associated with sea-level rise and storm intensification toward the end of the 21st century. Under the Representative Concentration Pathway (RCP) 8.5, the Coupled Model Intercomparison Project Phase 5 (CMIP5) predicts a 0.6-m ensemble mean of sea-level rise for the Central Pacific from the 1986–2005 to 2081–2100 epochs. Fifty downscaling simulations of the 2080–2099 period from the CMIP5 NCAR-CCSM4 model produce 2492 hurricanes around the Hawaiian Islands. In comparison with a control dataset for the 1980–1999 period, the simulated future hurricanes show a slight increase in number and a northward shift of the tracks toward the Hawaiian Islands. There are 627 hurricanes in the 2080–2099 dataset with potential impact on Oahu, and the top 24 storms selected by wind speed at the urban Honolulu coast define a scenario set for inundation mapping. A suite of spectral wave, circulation, and Boussinesq models in a nested grid system describes generation and propagation of surge and waves across the ocean as well as wave setup and runup at the coast. The interoperable package includes phase-averaged and phase-resolving processes to determine the coastal flood hazards over a range of spatial and temporal scales during a hurricane event. Since the simulated dataset corresponds to a quasi 1000-year period, barring the tail end of the distribution, the suite of inundation scenarios enables definition of flood hazard maps with return periods of up to 500 years or annual exceedance probabilities of 0.2% or greater for climate change adaptation.

The role of spatial planning in reducing exposure towards impacts of global sea level rise case study: Northern coast of Java, Indonesia

Spatial planning is expected to facilitate climate change adaptation by directing future spatial and infrastructure developments away from zones that are exposed to climate-related hazards. This study attempts to confirm this understanding by mapping the effects of the various spatial plans on the northern coast of Java, Indonesia. First, the study maps the extent of coastal hazards for the baseline year of 2010 using a GIS-based inundation model. An overlay in GIS demonstrates the influence of spatial plans for the projection year of 2030. This allows for calculating the economic losses of the planned developments. The case study shows that the current provincial spatial plans direct land use conversions along the northern coast of Java to continue to occur in the future. This could significantly decrease the regional capacity in dealing with the exposure to coastal inundation. The analysis also demonstrates that a total area of 55,220 ha of land prone to inundation, consisting of protected area (1488 ha), fishponds (32,916 ha) and agricultural land (20,814 ha), is planned to be converted into industry (13,399 ha) and settlements (41,821 ha). Thus, these areas will be also prone to inundation in 2030. This change would potentially lead to an economic loss of 246.6 billion USD. The spatial plans issued by the national and provincial governments for regulating the future land use on the northern coast of Java have not integrated measures against hazards related to global sea level rise. Meanwhile, many existing developments have already been affected by coastal inundation. Rather than reducing the exposure towards coastal flood hazards, the case study shows that spatial plans could even increase the risk of climate-related hazards and cause higher economic losses. These findings provide a different perspective on the role of spatial planning for climate change adaptation than what is stated in the literature.

Contextualizing institutional factors in an indicator-based analysis of hazard vulnerability for coastal communities

Indicator-based approaches to hazard vulnerability analysis are designed to produce policy-relevant information, but are limited in their ability to incorporate indicators that reflect the complex nature and contextual influence of institutional factors on vulnerability. This study focuses on local government policy and practice as an institutional factor and draws on a survey of municipal practitioners to inform indicators that reflect it. Rather than assess relative vulnerability, the study takes an original approach to construct an index that identifies similarities and differences in forms of capital that influence vulnerability across communities. The index is demonstrated through a case study of 50 coastal communities in British Columbia, Canada. The study uses local practitioner knowledge to inform indicators of institutional capital that influence vulnerability to coastal flood hazards, investigates associations between key indicators, and illustrates that incorporating meaningful indicators of institutional capital can enable contextual analysis of how local policy factors affect vulnerability.