Low-lying Coastal Communities Research Articles

Epidemiological association between water salinity and blood pressure in coastal populations: ambient temperature’s role as a confounder

Due to global climate change and anthropogenic activities, many low-lying coastal communities experience high sodium in drinking water as a result of saltwater intrusion, an emerging environmental health problem in many coastal regions. Drinking saline water is associated with higher sodium intake and hypertension. Exposure to higher ambient temperatures is common in many regions affected by saltwater intrusion, particularly in tropical and subtropical regions. Little attention has been given to the role of ambient temperature in the epidemiological association between drinking saline water and population blood pressure. We argue that high ambient temperatures increase water salinity and influence communities' sodium intake, urinary sodium excretion, and blood pressure. Hence, we hypothesize that ambient temperature is a potential confounder for the relationship between drinking saline water and population blood pressure. Testing the hypothesis requires a detailed measurement of urinary, blood, and sweat biomarkers (e.g., sodium), the population's blood pressure, and their drinking water’s salinity. An increasing number of coastal regions and islands will face the dual burden of high ambient heat exposure and saltwater intrusion in the future. Future studies are needed to determine the association between drinking saline water and blood pressure after adjusting for ambient temperature in saltwater intrusion-affected regions.

Tropical cyclone activity over the past 1200 years at the Pelican Cays, Belize

Tropical cyclone (TC) models indicate that continued planet warming will likely increase the global proportion of powerful TCs (specifically Categories 4 and 5 hurricanes), increasingly jeopardizing low-lying coastal communities and resources such as the Pelican Cays, Belize. The combination of increased coastal development and continued relative sea-level rise puts these communities at even higher risk of damage from TCs. The short TC observational record for the western Caribbean hampers the extensive study of TC activity on centennial timescales, which hinders our ability to fully understand past TC climatology and improve the accuracy of TC models. To better assess TC risk, paleotempestological studies are necessary to put future scenarios in perspective. Here, we present a high-resolution reconstruction of coarser-grained sediment deposits associated with TC (predominately ≥ Category 2 hurricanes) passages over the past 1200 years from Elbow and Lagoon Cays, two coral reef-bounded lagoons at the northern and southern end of the Pelican Cays; the most southern Belizean paleotempestological site to date. Coincident timing of historic storms with statistically significant coarser-grained deposits within cay lagoon sediment cores allows us to determine which historic TCs likely generated event layers (tempestites) archived in the sediment record. Our compilation frequency analysis indicates one active interval (above-normal TC activity) from 1740-1950 CE and one quiet interval (below-normal TC activity) from 850-1018 CE. The active and quiet intervals in the Pelican Cays composite record are anticorrelated with those from nearby and re-analyzed TC records to the north, including the Great Blue Hole (∼100 km north) and the Northeast Yucatan (∼380 km northwest). This site-specific anticorrelation in TC activity along the western Caribbean indicates that we cannot rely on any one single TC record to represent regional TC activity. However, we cannot discount that these anticorrelated periods between the western Caribbean sites are due to randomness. To confirm that the anticorrelation in TC activity among sites from the western Caribbean is indeed a function of climate change and not randomness, an integration of more records and TC model simulations over the past millennium is necessary to assess the significance of centennial-scale variability in TC activity recorded in reconstructions from the western Caribbean.

A Science and Community-Driven Approach to Illustrating Urban Adaptation to Coastal Flooding to Inform Management Plans

Academic research plays a pivotal role in illustrating and testing potential future adaptation strategies to sea level rise in low-lying coastal communities and enhances local municipalities’ adaptation plans. In Waikīkī, Hawai‘i, the built environment is increasingly impacted by flooding from multiple drivers: sea level rise-induced direct marine inundation, storm-drain backflow, and groundwater inundation (GWI), compounded by high-wave runup, extreme tides, heavy rainfall, and a shallow groundwater table. Given Waikīkī’s economic and cultural importance, in-place accommodation of flooding is desired, yet implementation plans have not been developed. By combining current scientific research, urban design visualizations, and community feedback, the interdisciplinary research team advanced intentional communication between the many parties seeking increased flood resilience through the end of the 21st century. Site-specific architectural renderings were a key tool to prompt structured community input on the coordination, prioritization, policy, and feasibility of adaptation measures for buildings, utilities, transportation, and open space. Public outreach reports document that the majority of participants thought all adaptation strategies presented were applicable, especially relocating critical equipment in buildings and streets. Proposed methods to develop sea level rise-adjusted minimum building elevation requirements may inform local municipalities’ future codes to minimize coastal property damage. The multi-year iterative process fostered growing participation in hosted and invited events, further improving the publicly distributed research products.

A deep-learning model for rapid spatiotemporal prediction of coastal water levels

With the increasing impact of climate change and relative sea level rise, low-lying coastal communities face growing risks from recurrent nuisance flooding and storm tides. Thus, timely and reliable predictions of coastal water levels are critical to resilience in vulnerable coastal areas. Over the past decade, there has been increasing interest in utilizing machine learning (ML) based models for emulation and prediction of coastal water levels. However, flood advisory systems still rely on running computationally demanding hydrodynamic models. To alleviate the computational burden, these physics-based models are either run at small scales with high resolution or at large scales with low resolution. While ML-based models are very fast, they face challenges in terms of ensuring reliability and ability to capture any surge levels. In this paper, we develop a deep neural network for spatiotemporal prediction of water levels in coastal areas of the Chesapeake Bay in the U.S. Our model relies on data from numerical weather prediction models as the atmospheric input and astronomical tide levels, while its outputs are time series of predicted water levels at several tide gauge locations across the Chesapeake Bay. We utilized a CNN-LSTM setting as the architecture of the model. The CNN part extracts the features from a sequence of gridded wind fields and fuses its output to several independent LSTM units. The LSTM units concatenate the atmospheric features with respective astronomical tide levels and produce water level time series. The novel contribution of the present work is in spatiotemporality and in prioritization of the physical relationships in the model to maintain a high analogy to hydrodynamic modeling, either in the network architecture or in the selection of predictors and predictands. The results show that this setting yields a strong performance in predicting coastal water levels that cause flooding from minor to major levels. We also show that the model stands up successfully to the rigorous comparison with a high-fidelity ADCIRC model, yielding mean RMSE and correlation coefficient of 14.3 cm and 0.94, respectively, in two extreme cases, versus 12.30 cm and 0.96 for the ADCIRC model. The results highlight the practical feasibility of employing fast yet inexpensive data-driven models for resilient coastal management.

Stochastic properties of coastal flooding events – Part 2: Probabilistic analysis

Abstract. Low-intensity but high-frequency coastal flooding, also known as nuisance flooding, can negatively affect low-lying coastal communities with potentially large socioeconomic effects. Partially driven by wave runup, this type of flooding is difficult to predict due to the complexity of the processes involved. Here, we present the results of a probabilistic analysis of flooding events measured on an eroded beach at the Texas coast. A high-resolution time series of the flooded area was obtained from pictures using convolutional neural network (CNN)-based semantic segmentation methods, as described in the first part of this contribution. After defining flooding events using a peak-over-threshold method, we found that their size follows an exponential distribution. Furthermore, consecutive flooding events were uncorrelated at daily timescales but correlated at hourly timescales, as expected from tidal and day–night cycles. Our measurements confirm the broader findings of a recent multi-site investigation of the probabilistic structure of high-water events that used a semi-empirical formulation for wave runup. Indeed, we found a relatively good statistical agreement between our CNN-based empirical flooding data and predictions using total-water-level estimations. As a consequence, our work supports the validity of a relatively simple probabilistic model of high-frequency coastal flooding driven by wave runup that can be used in coastal risk management and landscape evolution models.

Estimating the combined risks of sea level rise and storm surges using a numerical model: Application to Macao

The storm surges caused by tropical cyclones may lead to overtopping floods in low-lying coastal communities, which will be further exacerbated by sea level rise. In this study, a numerical model is developed that can simulate the two-dimensional surface flow and one-dimensional drainpipe flow simultaneously. Then this model is validated and applied to Macao Peninsula. The compound flood scenarios of storm surge and sea level rise are therefore forecasted, with storm surge return periods of 5-, 10-, 20-, 50-, 100-, and 200-years, and sea level rises by 0 m, 0.5 m and 1.0 m. The overtopping floods caused by storm surges are mainly distributed in the west and northwest of Macao Peninsula. When the sea level rises by 1.0 m, the backflow occurs 2 h earlier than that does under the current sea level. Adding pumping station can reduce backflow and improve drainage efficiency significantly. The effectiveness of the drainage system during floods can be quantified using backflow coefficient and drainage efficiency coefficient, which both decrease as the storm tide level increases. In the worst-case scenario of 200-year-return-period storm surge and 1-m sea level rise, the flooding area accounts for 41.1% of the land area, and the population at risk reaches 68.4% of the total population. The storm-surge-prone area overlaps with densely populated area in western Macao Peninsula, where the effects of storm surge and sea level rise are intensified.

Impacts of climate change on the tourist-carrying capacity at La Playa beach (Sardinia, IT)

It is largely acknowledged that global mean sea level is rising and accelerating increasing low-lying coastal communities’ exposure and vulnerability. The IPCC AR5 identified the Mediterranean Sea as one of the semi-enclosed seas with projected high rate. Impacts of sea level rise (SLR) at local scale affect the number of visitors in highly vulnerable beaches and previous paper have quantified these adverse effects. In this paper we want to say that coastal climate change is not just sea level rise and other climatic factors can affect the optimal beach carrying capacity in complex and uncertain ways. Specifically, the paper shows that the effects of selected climatic factors as wave, rainfall and wind can be opposite to that of SLR and the beach management could even benefit from those trends.

Trivariate Joint Distribution Modelling of Compound Events Using the Nonparametric D-Vine Copula Developed Based on a Bernstein and Beta Kernel Copula Density Framework

Low-lying coastal communities are often threatened by compound flooding (CF), which can be determined through the joint occurrence of storm surges, rainfall and river discharge, either successively or in close succession. The trivariate distribution can demonstrate the risk of the compound phenomenon more realistically, rather than considering each contributing factor independently or in pairwise dependency relations. Recently, the vine copula has been recognized as a highly flexible approach to constructing a higher-dimensional joint density framework. In these, the parametric class copula with parametric univariate marginals is often involved. Its incorporation can lead to a lack of flexibility due to parametric functions that have prior distribution assumptions about their univariate marginal and/or copula joint density. This study introduces the vine copula approach in a nonparametric setting by introducing Bernstein and Beta kernel copula density in establishing trivariate flood dependence. The proposed model was applied to 46 years of flood characteristics collected on the west coast of Canada. The univariate flood marginal distribution was modelled using nonparametric kernel density estimation (KDE). The 2D Bernstein estimator and beta kernel copula estimator were tested independently in capturing pairwise dependencies to establish D-vine structure in a stage-wise nesting approach in three alternative ways, each by permutating the location of the conditioning variable. The best-fitted vine structure was selected using goodness-of-fit (GOF) test statistics. The performance of the nonparametric vine approach was also compared with those of vines constructed with a parametric and semiparametric fitting procedure. Investigation revealed that the D-vine copula constructed using a Bernstein copula with normal KDE marginals performed well nonparametrically in capturing the dependence of the compound events. Finally, the derived nonparametric model was used in the estimation of trivariate joint return periods, and further employed in estimating failure probability statistics.

Beyond the vulnerability/resilience dichotomy: Perceptions of and responses to the climate crisis on Emau, Vanuatu

In Vanuatu, a South Pacific island nation, the effects of climate change pose new challenges for low-lying coastal communities. This study explores how one village on Emau, an island offshore of capital island Efate, has developed several overlapping strategies to manage climate change impacts, including drought and sea level rise. Informants reveal their perceptions of changing environmental baselines and how socio-economic processes, including population growth, cultural loss, and limited access to cash incomes, have shaped the community’s response. Informants describe four climate adaptation strategies: 1) expanding access to cash income through seasonal or urban labor migration; 2) leveraging international expertise and funding to meet their goals; 3) developing hybrid forms of traditional practices and contemporary ideology to preserve environmental knowledge; and 4) performing physical and emotional labor to preserve and remain on their land. These strategies span oceans and cross international borders, refuting narratives of islands’ being ‘isolated’ from the rest of the world and passive ‘victims’ of climate change. Contextualizing perceptions of and responses to environmental change provides critical nuance to the resilience/vulnerability framework, which alone obscures ongoing political, social and economic processes on islands.

Saltwater intrusion in estuaries with different dynamic depths

Sea-level rise threatens to increase saltwater intrusion in low-lying coastal communities worldwide. In addition, changing patterns of evaporation and precipitation are expected to modify the lengths of saltwater intrusion in estuaries. This study aims to define the length of saltwater intrusion among distinct estuaries with contrasting responses to variations in river discharge and water level. A Markov-chain Monte Carlo model was used as a supervised machine learning of the relationship among saltwater intrusion length, river discharge, water level, wind velocity and pluvial precipitation in three estuaries The supervised learning provided a relationship to project saltwater intrusion for different climatic conditions in the estuaries. The length of saltwater intrusion and river discharge were proportional for the dynamically deep Dee River estuary (UK) and Capibaribe River estuary (Brazil). Increased river discharge in those two estuaries was followed by increased limit of saltwater intrusion. For these two cases, however, it is hypothesized that beyond a threshold of river discharge, both estuaries will show a decreased saltwater intrusion with increased river discharge and transition to dynamically shallow estuaries. The dynamically shallow St. Johns River estuary (USA) had the typically expected response of decreased saltwater intrusion after increases in river discharge.

Climate change and the increasing vulnerability of the poor in the Commonwealth

ABSTRACT Many millions of the most-deprived people of the Commonwealth live in highly vulnerable locations: the tropical countries affected by cyclones (hurricanes or typhoons). Tropical cyclone intensities have been increasing since the mid-1990s. Their tracks may be shifting poleward. The associated storm surges are growing in height and severity. From the Caribbean to eastern Africa, the islands of the Indian Ocean, South Asia, Australia and the Pacific communities face, increasing flooding, housing and workplace damage and loss of livelihoods. Among the most vulnerable are those living in low-lying coastal communities on coral islands, the deltas of great rivers, and coastal sand barriers. These communities are often dependent on small-scale fisheries and are at great risk. This vulnerability has been aggravated by the COVID-19 pandemic which has struck urban areas already suffering from outbreaks of infectious diseases such as dengue, cholera, and diarrhoea. When storm damage affects the public health infrastructure the ability to cope with these multiple hazards is likely to be overstretched. Investment in disaster preparation and relief for these worsening vulnerability situations. Action has to be taken at all levels, from the household and local community to municipal, regional and national governments. This article argues that international support is critical and governments should be increasing international aid.

Probabilistic tsunami hazard and exposure assessment for the pacific islands- Fiji

Tsunami are known to be one of the most powerful and destructive natural hazards to impact low-lying coastal communities. The Republic of Fiji is situated in a complex tectonic setting at the boundary of two active plates in the South-west Pacific; the Indo-Australian and Pacific Plate, making the country highly vulnerable to earthquakes and tsunami. Local and regional source tsunami is a concern for emergency management. This is due to the limited warning time in receiving a tsunami alert and issuing warnings to the public. Fiji's greatest local and regional tsunami hazard risk is from the Tonga-Kermadec trench and South New Hebrides faults. This paper presents the first probabilistic tsunami hazard assessment of a credible 1 in 10,000 year event for Fiji's two largest populated islands, Viti Levu and Vanua Levu. Subsequent to the probabilistic tsunami hazard assessment, this paper presents the results of a tsunami exposure assessment of the population, assets and critical infrastructure vulnerable to tsunami inundation from Tonga-Kermadec and South New Hebrides tsunami sources. This study applies a mix methodology approach, using a combination of hydrodynamic models, probabilistic approaches, Geographic Information Systems and quantitative analysis to determine maximum tsunami heights and exposure to tsunami hazard. Results of the exposure assessment indicates provinces in Vit Levu and Vanua Levu are likely to be susceptible to various tsunami inundation heights, concluding that people and assets in provinces such as Macuata and Tailevuare more vulnerable to tsunami. The results of this study provides valuable information for the Government of Fiji specifically the National Disaster Management Office, Mineral Resources Department, the National Tsunami Warning Centre and at risk communities. This will increase tsunami risk knowledge and will encourage decisive warning times and allow emergency management to make informative decision-making in regards to emergency preparedness and response planning.

Establishing a framework of a watershed-wide screening tool to support the development of watershed-based flood protection plans for low-lying coastal communities

Flood risk analysis is the instrument by which floodplain and stormwater utility managers create strategic adaptation plans to reduce the likelihood of flood damages in their communities, but there is a need to develop a screening tool to analyze watersheds and identify areas that should be targeted and prioritized for mitigation measures. The authors developed a screening tool that combines readily available data on topography, groundwater, surface water, tidal information for coastal communities, soils, land use, and precipitation data. Using the outputs of the screening tool for various design storms, a means to identify and prioritize improvements to be funded with scarce capital funds was developed, which combines the likelihood of flooding from the screening tool with a consequence of flooding assessment based on land use and parcel size. This framework appears to be viable across cities that may be inundated with water due to sea-level rise, rainfall, runoff upstream, and other natural events. The framework was applied to two communities using the 1-day 100-year storm event: one in southeast Broward County with an existing capital plan and one inland community with no capital plan.

Generational retreat: locally driven adaption to coastal hazard risk in two Indigenous communities in Fiji

The relocation and retreat of low-lying coastal communities are expected to increase in anticipation of, and response to, sea-level rise and subsequent coastal hazard risks. As such, there is burgeoning attention in research and policy surrounding relocation that is managed and supported through external sources. Yet there exists limited research into the ways Indigenous communities are autonomously retreating from emerging coastal hazard risk, despite long histories of mobility and inherent adaptive capacities. We contribute to this gap through qualitative data derived from two low-lying coastal iTaukei (Indigenous Fijian) communities that are exposed to coastal erosion, storm surges, and flooding events, alongside other socioeconomic pressures. We explore the approach of “generational retreat” which is emerging as a long-term relocation strategy employed by village residents. Generational retreat is a form of mobility whereby households, namely, younger generations, incrementally retreat in response to existing, emerging, and anticipated coastal changes while maintaining connections to place and village life. We show how communities are drawing on local processes and resources to direct autonomous adaptation pathways which are suited to local sociopolitical, cultural, and environmental contexts. We further explore opportunities for governments and external actors in supporting these locally conceived and driven forms of retreat as an adaptive and sustainable response to coastal change.

Increasing threat of coastal groundwater hazards from sea-level rise in California

Projected sea-level rise will raise coastal water tables, resulting in groundwater hazards that threaten shallow infrastructure and coastal ecosystem resilience. Here we model a range of sea-level rise scenarios to assess the responses of water tables across the diverse topography and climates of the California coast. With 1 m of sea-level rise, areas flooded from below are predicted to expand ~50–130 m inland, and low-lying coastal communities such as those around San Francisco Bay are most at risk. Coastal topography is a controlling factor; long-term rising water tables will intercept low-elevation drainage features, allowing for groundwater discharge that damps the extent of shoaling in ~70% (68.9–82.2%) of California’s coastal water tables. Ignoring these topography-limited responses increases flooded-area forecasts by ~20% and substantially underestimates saltwater intrusion. All scenarios estimate that areas with shallow coastal water tables will shrink as they are inundated by overland flooding or are topographically limited from rising inland. Sea-level rise raises water tables, causing flooding from below and saltwater intrusion. A modelling study predicts that coastal California groundwater flooding will expand 50–130 m inland with 1 m of sea-level rise, with areal flooding extent strongly dependent on topography and drainage capacity.

Simulating dune evolution on managed coastlines: Exploring management options with the Coastal Recovery from Storms Tool (CReST)

Despite the importance of coastal dunes to many low-lying coastal communities and ecosystems, our understanding of how both climatic and anthropogenic pressures affect foredune evolution on time scales of years to decades is relatively poor. However, recently developed coupled numerical modeling tools have allowed for the exploration of the erosion and growth of coastal foredunes on time scales of hours to years. For example, Windsurf is a new process-based numerical modeling system (Cohn et al. 2019a) that simulates the evolution of dune-backed sandy coastal systems in response to wave, wind, and water level forcings. CReST, developed as a front-end interface to Windsurf, aims to add the ability to incorporate beach nourishment and dune construction, beach and dune grading, dune grass planting scenarios, dune grass removal, and the presence of hard engineering structures into the model framework to better account for the complex dynamics of managed coastlines. Initial model sensitivity tests suggest that the model provides a flexible framework to investigate the complex interactions between beaches and dunes for a variety of exploratory and applied applications.

COASTAL RESILIENCY: MULTI-TIER PROTECTION SYSTEM & RISK MANAGEMENT STRATEGY

North Atlantic hurricanes pose a significant threat to Caribbean islands and their low-lying coastal communities through storm surge, long period swells, coastal flooding, and duration wind and rain events. The increasing intensity and frequency of these damaging storms and rising sea levels require advances in the traditional approaches to coastal protection systems and risk management strategies. Adaptation strategies for coastal locations that do not have the option of mitigated retreat due to the significant infrastructure investment require innovative and tailored solutions to combat the threat of these storm events. In this paper, an 18-year case study of a Caribbean island Resort evaluates a long-term cumulative process of providing coastal protection solutions in stepped tiers and assessing their effectiveness over four Category 4 hurricanes (Lenny, 1998; Omar, 2008; Earl, 2010; Matthew, 2016).

Rethinking Coastal Community Approaches to Climate Change Impacts and Adaptation

Sorensen, C.; Knudsen, P.; Sorensen, P.; Damgaard, T.; Molgaard, M.R., and Jensen, J., 2018. Rethinking Coastal Community Approaches to Climate Change Impacts and Adaptation. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp.1521–1525. Coconut Creek (Florida), ISSN 0749-0208.Low-lying coastal communities face almost insurmountable challenges from floods and climate change. Research work on adaptation and mitigation particularly emphasizes on cities and mega-cities as a natural consequence of their agglomeration of people and assets. Less focus is put on smaller coastal communities and their challenges, one of which is a lack of local expertise and knowledge. Adaptation to climate change is often a local governance level task, however. Co-work between municipal and national authorities, the utility company, research, business, consultants and citizens has resulted in a common framework to address and deal with water-related challenges in a Danish coastal community. From an assessment of combined impacts of climate change (i.e. sea level rise and storm surges, precipitation and cloudbursts and associated groundwater level responses) and stresses from degrading sewer systems and land subsidence, impact zones are mapped. The multi-player, end-user defined work transcends sectors and builds capacity by sharing data and knowledge. It mainstreams climate change issues into business, management, planning and early warning: the overall goal is an adaptation strategy unfolded from stakeholder involvement and responsibility, cost-effective decision making, climate-related asset management processes and a holistic livable cities approach to this highly vulnerable coastal community. The collaboration and common framework enable the actors to articulate need of information and establish feedback mechanisms between local level work and e.g. sea level research and climate services.

Local values and fairness in climate change adaptation: Insights from marginal rural Australian communities

A key criterion of successful adaptation to climate change is that it avoids potential inequalities arising from climate impacts or from adaptation strategies themselves. Recent research on adaptation in developing and developed countries argues that the measures of such fairness cannot be captured by standard metrics of vulnerability and should be situated in the milieu of people’s daily lives and temporalities. Yet there is little empirical evidence to support this theoretical argument. This paper describes a method, and presents findings from research that aimed to understand and classify the lived values of four marginal rural communities at risk of sea-level rise in Australia to inform adaptation planning and implementation. Our research finds that there are at least five types of primary residents and second home-owners attached to these four low-lying coastal communities. Some of these residents are more likely to be amenable to relocation if their needs for affordable living and belonging are met. For others, there may be little that can be done to compensate for the loss of place attachment, and implementing a measured approach that provides them time to adapt to the idea of change and form connections to new places is the best that could be achieved. We discuss the implications of place-specific and people-centric values for achieving fair adaptation.

Natural Hazards, Sea Level Rise and the New Auckland Unitary Plan: Implications for Low Lying Coastal Communities

This paper uses the objectives and policies inherent in the New Zealand Coastal Policy Statement 2010 as a template for benchmarking the adaptation strategies contained in the Unitary Plan for Auckland City, New Zealand’s largest coastal municipal centre. The research analyses the stakeholder feedback from the public submission section devoted to coastal hazards, and assesses through selected criteria and a rating system, developed in conjunction with literature studies and stakeholder contribution, the degree to which the plan aligns with the policies of adaptation required by this Coastal Policy Statement. A case study tests the effectiveness of the adaptation requirements. Results indicate an appropriate degree of compliance with the relevant adaptation criteria, but that, in order to minimise future disruption, more attention should be given to the long-term planned withdrawal of housing from hazardous coastal situations.