Coastal risks are increasing from both development and climate change. Interest is growing in the protective role that coastal nature-based measures (or green infrastructure), such as reefs and wetlands, can play in adapting to these risks. However, a lack of quantitative information on their relative costs and benefits is one principal factor limiting their use more broadly. Here, we apply a quantitative risk assessment framework to assess coastal flood risk (from climate change and economic exposure growth) across the United States Gulf of Mexico coast to compare the cost effectiveness of different adaptation measures. These include nature-based (e.g. oyster reef restoration), structural or grey (e.g., seawalls) and policy measures (e.g. home elevation). We first find that coastal development will be a critical driver of risk, particularly for major disasters, but climate change will cause more recurrent losses through changes in storms and relative sea level rise. By 2030, flooding will cost $134–176.6 billion (for different economic growth scenarios), but as the effects of climate change, land subsidence and concentration of assets in the coastal zone increase, annualized risk will more than double by 2050 with respect to 2030. However, from the portfolio we studied, the set of cost-effective adaptation measures (with benefit to cost ratios above 1) could prevent up to $57–101 billion in losses, which represents 42.8–57.2% of the total risk. Nature-based adaptation options could avert more than $50 billion of these costs, and do so cost effectively with average benefit to cost ratios above 3.5. Wetland and oyster reef restoration are found to be particularly cost-effective. This study demonstrates that the cost effectiveness of nature-based, grey and policy measures can be compared quantitatively with one another, and that the cost effectiveness of adaptation becomes more attractive as climate change and coastal development intensifies in the future. It also shows that investments in nature-based adaptation could meet multiple objectives for environmental restoration, adaptation and flood risk reduction.

As coastal communities around the globe contend with the impacts of climate change including coastal hazards such as sea level rise and more frequent coastal storms, educating stakeholders and the general public has become essential in order to adapt to and mitigate these risks. Communicating SLR and other coastal risks is not a simple task. First, SLR is a phenomenon that is abstract as it is physically distant from many people; second, the rise of the sea is a slow and temporally distant process which makes this issue psychologically distant from our everyday life. Virtual reality (VR) simulations may offer a way to overcome some of these challenges, enabling users to learn key principles related to climate change and coastal risks in an immersive, interactive, and safe learning environment. This article first presents the literature on environmental issues communication and engagement; second, it introduces VR technology evolution and expands the discussion on VR application for environmental literacy. We then provide an account of how three coastal communities have used VR experiences developed by multidisciplinary teams—including residents—to support communication and community outreach focused on SLR and discuss their implications.

As the world’s population grows to a projected 11.2 billion by 2100, the number of people living in low-lying areas exposed to coastal hazards is projected to increase. Critical infrastructure and valuable assets continue to be placed in vulnerable areas, and in recent years, millions of people have been displaced by natural hazards. Impacts from coastal hazards depend on the number of people, value of assets, and presence of critical resources in harm’s way. Risks related to natural hazards are determined by a complex interaction between physical hazards, the vulnerability of a society or social-ecological system and its exposure to such hazards. Moreover, these risks are amplified by challenging socioeconomic dynamics, including poorly planned urban development, income inequality, and poverty. This study employs a combination of machine learning clustering techniques (Self Organizing Maps and K-Means) and a spatial index, to assess coastal risks in Latin America and the Caribbean (LAC) on a comparative scale. The proposed method meets multiple objectives, including the identification of hotspots and key drivers of coastal risk, and the ability to process large-volume multidimensional and multivariate datasets, effectively reducing sixteen variables related to coastal hazards, geographic exposure, and socioeconomic vulnerability, into a single index. Our results demonstrate that in LAC, more than 500,000 people live in areas where coastal hazards, exposure (of people, assets and ecosystems) and poverty converge, creating the ideal conditions for a perfect storm. Hotspot locations of coastal risk, identified by the proposed Comparative Coastal Risk Index (CCRI), contain more than 300,00 people and include: El Oro, Ecuador; Sinaloa, Mexico; Usulutan, El Salvador; and Chiapas, Mexico. Our results provide important insights into potential adaptation alternatives that could reduce the impacts of future hazards. Effective adaptation options must not only focus on developing coastal defenses, but also on improving practices and policies related to urban development, agricultural land use, and conservation, as well as ameliorating socioeconomic conditions.

Flooding is the most common and damaging of all natural disasters in the United States, and was a factor in almost all declared disasters in U.S. history. Direct flood losses in the U.S. in 2011 totaled $8.41 billion and flood damage has also been on the rise globally over the past century. The National Flood Insurance Program paid out more than $38 billion in claims since its inception in 1968, more than a third of which has gone to the one percent of policies that experienced multiple losses and are classified as “repetitive loss.” During the same period, the loss of coastal wetlands and other natural habitat has continued, and funds for conservation and restoration of these habitats are very limited. This study demonstrates that flood losses could be mitigated through action that meets both flood risk reduction and conservation objectives. We found that there are at least 11,243km² of land in coastal California, which is both flood-prone and has natural resource conservation value, and where a property/structure buyout and habitat restoration project could meet multiple objectives. For example, our results show that in Sonoma County, the extent of land that meets these criteria is 564km². Further, we explore flood mitigation grant programs that can be a significant source of funds to such projects. We demonstrate that government funded buyouts followed by restoration of targeted lands can support social, environmental, and economic objectives: reduction of flood exposure, restoration of natural resources, and efficient use of limited governmental funds.

The need to reduce risks from coastal storms and climate change in coastal areas has given rise to efforts to make greater use of integrated ecosystem-based approaches. Assessment of the role and cost efficiency of adaptation measures is increasingly demanded. Applying the Economics of Climate Adaptation framework in the US Gulf Coast, we compare nature-based defenses, artificial defenses, and policy measures for adaptation and risk reduction and quantify their costs and benefits under a variety of economic growth and climate change scenarios. Our analyses are spatially explicit and all models, tools and information are open source. The framework includes (i) a probabilistic assessment of hazards, (ii) estimation of damages and (iii) assessment of adaptation and risk reduction measures. We perform sensitivity analyses to understand the parameters that created the most variation in risk assessment and most influenced estimates of cost effectiveness. We find that high rates of economic growth and coastal development are likely to create greater risks in the near term than climate change, due to the increase in exposed assets. Nature-based solutions such as oyster reef and marsh restoration are particularly cost effective, but their cost-effectiveness is highly dependent on where these measures are used. As decision-makers look for the most cost effective group of measures for adaptation and risk reduction, these approaches and results should be particularly useful for informing management priorities.

Sea level rise increases community risks from erosion, wave flooding, and tides. Current management typically protects existing development and infrastructure with coastal armoring. These practices ignore long-term impacts to public trust coastal recreation and natural ecosystems. This adaptation framework models physical responses to the public beach and private upland for each adaptation strategy over time, linking physical changes in widths to damages, economic costs, and benefits from beach recreation and nature using low-lying Imperial Beach, California, as a case study. Available coastal hazard models identified community vulnerabilities, and local risk communication engagement prioritized five adaptation approaches—armoring, nourishment, living shorelines, groins, and managed retreat. This framework innovates using replacement cost as a proxy for ecosystem services normally not valued and examines a managed retreat policy approach using a public buyout and rent-back option. Specific methods and economic values used in the analysis need more research and innovation, but the framework provides a scalable methodology to guide coastal adaptation planning everywhere. Case study results suggest that coastal armoring provides the least public benefits over time. Living shoreline approaches show greater public benefits, while managed retreat, implemented sooner, provides the best long-term adaptation strategy to protect community identity and public trust resources.