Increasing Sea Level Rise Research Articles

Predicting beach rotation using multiple atmospheric indices

Shoreline change in the form of beach rotation can occur at event to decadal timescales, especially in semi-sheltered embayments with bi-directional wave climates, leading to enhanced coastal vulnerability under predictions of increased sea level rise. Previous studies have shown that phases of winter-averaged atmospheric indices in the North Atlantic correlate with variations in average winter wave height and dominant direction; however, predictions of a localised wave climate and beach rotation from individual climate indices has exhibited limited skill. Here we show that the combination of two major north Atlantic climate indices, the North Atlantic Oscillation (NAO) and West Europe Pressure Anomaly (WEPA), improves the prediction of a wave power directionality index (WDI), known to correlate with beach rotation along the length of a headland bound gravel embayment. Results using a combination of NAO and WEPA, improves predictions of WDI with an associated R2 of 0.66, when compared to 0.23 and 0.31 for NAO and WEPA individually. Hindcast (WDIWW3) and index predicted (WDIPred) values of the WDI were shown to validate against measured beach rotation from 2008 to 2018 and modelled inshore potential longshore energy fluxes from 1980 to 2018. A long-term historic time series of WDIPred (1906–present) was then hindcast using records of NAO and WEPA. Qualitative validation of long-term beach rotation in response to the WDIPred is achieved with proxy records of beach change in the form of oblique and aerial photography and topographic maps. Low frequency (~60 years) beach rotation is shown to follow phases of the detrended cumulative WDIPred values, over the period of 1906 to 2018, linked to the multi-decadal fluctuations in detrended cumulative values of NAO and WEPA. When examined in the context of millennial-scale proxy NAO records, it is clear the recent centurial-scale analysis does not capture past variability and duration. This work has shown that: (1) potential future season ahead forecasts of atmospheric indices may skilfully predict beach rotation in many regions with bi-directional wave climates; and (2) historical analysis highlights the potential past phases of extreme coastal realignment. These new insights will lead to proactive and informed management from local authorities and coastal engineers.

Increased Organic Carbon Burial in Northern Florida Mangrove‐Salt Marsh Transition Zones

AbstractBlue carbon habitats like salt marshes and mangroves bury large amounts of carbon with limited area; however, they also are increasingly susceptible to current climate change. Combined effects of rising temperatures, decreasing freeze frequencies, and increasing sea level rise rates are resulting in mangrove replacement of salt marshes along the southern United States. Surface soils analyzed here from wetlands along northern Florida Atlantic and Gulf Coasts showed higher apparent sedimentation rates in mangrove‐dominated sites (1.5–3.2 mm yr−1) and where mangroves are migrating into the marsh (termed transition sites, 2.3–3.8 mm yr−1). Average carbon burial rates were higher in transition sites for both coasts (27–47 g C·m−2·yr−1) compared to the respective mangrove (10–22 g C·m−2·yr−1) and salt marsh (4–7 g C·m−2·yr−1) sites. Lignin biomarker data (Λ‐6, Λ‐8, and C/V) indicated that mangrove and transition sites had higher lignin inputs from woody vascular plants compared to salt marsh sites, which may slow decadal‐ to centennial‐scale decay. Higher amino acid concentrations in mangrove soils relative to mangrove biomass (1.8–2.3 mmol g C−1 vs. 0.2–0.9 mmol g C−1) and lower C/N indicated that these mangrove sites receive higher algal inputs than the transition and salt marsh sites, attributed to greater tidal inundation in the mangrove sites given their position near the shoreline. Overall, increased accretion, carbon burial, and lignin in mangrove transition sites indicate that this migration may increase carbon burial and increase the stability and residence time of buried soil carbon. Future studies on mangrove migration in northern Florida can verify this through replication and elevation analysis.

Coastal Lowlands' Inundation Risk Assessment with High-resolution TanDEM-X DEM in Qingdao Coastal Plains, China

Abstract. Global warming plays a principal role on the continuous increasing sea-level rise, which exposes coastal regions worldwide to flooding threat. However, the challenge is that the regional impact of SLR flooding can be variable, especially when considering multiple effects of land subsidence, long-term general sea-level rise and extreme weather conditions like storm surge. In this paper, we build module with high-resolution InSAR-derived precision DEMs with resolution of 4 m, long-term SLR trend and episodic signals of climate change to calculate the relative sea level in AD 2100 on various scenarios over the Jiaozhou Bay, one typical region of the biggest peninsula in China and an important economic centre adjoining to the Yellow Sea. The potential of TanDEM-X DEM for coastal vulnerability mapping in the Qingdao coastal area were evaluated in order to investigate the effect of the accuracy and resolution of coastal topography on the reliability and usefulness of elevation-based sea-level rise assessments. The results reveal that coastal lowland areas over the JiaozhouBay are extremely vulnerable in the following years within 21st century with use of high-accuracy TanDEM-X DEM data, which would be an advantage for further elevation-based dynamic assessments of coastal inundation events considering storm surges, abnormal high tides, and extreme precipitation events. which would be vital for locally coastal protection and decision-making.

Exposure of real estate properties to the 2018 Hurricane Florence flooding

Abstract. Quantifying the potential exposure of property to damages associated with storm surges, extreme weather and hurricanes is fundamental to developing frameworks that can be used to conceive and implement mitigation plans as well as support urban development that accounts for such events. In this study, we aim at quantifying the total value and area of properties exposed to the flooding associated with Hurricane Florence that occurred in September 2018. To this aim, we implement an approach for the identification of affected areas by generating a map of the maximum flood extent obtained from a combination of the flood extent produced by the Federal Emergency Management Agency's (FEMA's) water marks with those obtained from spaceborne radar remote-sensing data. The use of radar in the creation of the flood extent allows for those properties commonly missed by FEMA's interpolation methods, especially from pluvial or non-fluvial sources, and can be used in more accurately estimating the exposure and market value of properties to event-specific flooding. Lastly, we study and quantify how the urban development over the past decades in the regions flooded by Hurricane Florence might have impacted the exposure of properties to present-day storms and floods. This approach is conceptually similar to what experts are addressing as the “expanding bull's eye effect”, in which “targets” of geophysical hazards, such as people and their built environments, enlarge as populations grow and spread. Our results indicate that the total value of property exposed to flooding during Hurricane Florence was USD 52 billion (in 2018 USD), with this value increasing from USD ∼10 billion at the beginning of the past century to the final amount based on the expansion of the number of properties exposed. We also found that, despite the decrease in the number of properties built during the decade before Florence, much of the new construction was in proximity to permanent water bodies, hence increasing exposure to flooding. Ultimately, the results of this paper provide a new tool for shedding light on the relationships between urban development in coastal areas and the flooding of those areas, which is estimated to increase in view of projected increasing sea level rise, storm surges and the strength of storms.

National-Scale Built-Environment Exposure to 100-Year Extreme Sea Levels and Sea-Level Rise

Coastal flooding from extreme sea levels will increase in frequency and magnitude as global climate change forces sea-level rise (SLR). Extreme sea-level events, rare in the recent past (i.e., once per century), are projected to occur at least once per year by 2050 along many of the world’s coastlines. Information showing where and how built-environment exposure increases with SLR, enables timely adaptation before damaging thresholds are reached. This study presents a first national-scale assessment of New Zealand’s built-environment exposure to future coastal flooding. We use an analytical risk model framework, “RiskScape”, to enumerate land, buildings and infrastructure exposed to a present and future 100-year extreme sea-level flood event (ESL100). We used high-resolution topographic data to assess incremental exposure to 0.1 m SLR increases. This approach detects variable rates in the potential magnitude and timing of future flood exposure in response to SLR over decadal scales. National built-land and asset exposure to ESL100 flooding doubles with less than 1 m SLR, indicating low-lying areas are likely to experience rapid exposure increases from modest increases in SLR expected within the next few decades. This highlights an urgent need for national and regional actions to anticipate and adaptively plan to reduce future socio-economic impacts arising from flood exposure to extreme sea-levels and SLR.

A simple, dynamic, hydrological model for mesotidal salt marshes

Salt marsh hydrology presents many difficulties from a measurement and modeling standpoint: bi-directional flows of tidal waters, variable water densities due to mixing of fresh and salt water, significant influences from vegetation, and complex stream morphologies. Because of these difficulties, there is still much room for development of a truly mechanistic model of salt marsh groundwater and surface-water hydrology. This in turn creates an obstacle for simulating other marsh processes, such as nutrient cycling, that rely heavily on hydrology as a biogeochemical control and as a mode of nutrient transport. As a solution, we have used water level data collected from a well transect in Winant Slough, a mesotidal salt marsh on the Oregon coast, to create and calibrate a simple, empirical dynamic marsh hydrology model with few parameters. The model predicts the response of a marsh's water table level to tides and precipitation as a function of surface elevation and distance from tidal channel. Validation was conducted using additional well data from a separate transect in Winant Slough (achieving a standard error of 2.5 cm) and from two other mesotidal marshes in Tillamook Bay, Oregon (achieving standard errors of 3.1 cm and 3.6 cm). Inundation frequencies of the top 10 cm of soil were estimated from model outputs to be 18.3% of a 14.8-day tidal cycle for the area closest to the tidal creek and 59.3% for the area furthest from the creek. Model outputs were also used to predict the amount of soil pore space available to receive incoming tide water in Winant Slough, finding the volume available to range from 12.5% to 24.7% of the incoming marsh tidal prism volume, depending on the maximum tide height. Incrementally increasing sea level rise scenarios ranging from 15 cm to 75 cm predicted an exponential decrease in soil pore space available to receive incoming tidal water and an approximately linear increase in inundation frequency of the top 10 cm of soil; this substantial change in hydrology would impact the marsh's ability to process incoming water and could alter the zonation of vegetation. The model is relatively easy to apply to salt marshes and can provide informative hydrology predictions to land managers, ecologists, and biogeochemists who may not have the time or expertise required to apply more complex models.

37 years of Common Tern Sterna hirundo breeding at Sečovlje Salina

Abstract Years ago, the Common Tern Sterna hirundo was known to nest in Slovenia along larger watercourses. Today it only breeds locally in artificially built nesting areas. On the seashore, its nesting was confirmed for the first time in 1983, when 9 pairs bred in the Sečovlje Saltpans. In the same year, we started mapping the breeders in the Sečovlje Saltpans, which has continued till this very day. Since 2010, we have been systematically collecting data on the number of fledged birds. In 1991, the number of breeding pairs increased, which coincides with the increase in other parts of the Mediterranean. Since 1991, the size of the breeding population has been quite stable, ranging from 30 to 70 pairs. The Common Tern’s breeding success in the Sečovlje Saltpans is poor, mainly due to precipitation (40% of all unsuccessful nests) and predation (35%). Long, dry periods without rainfall have a positive effect on the hatching and fledging success. Appropriate water management, artificial islands and access to nesting sites control can prevent the disturbance caused by visitors and, in part, predators such as foxes and martens. At the Sečovlje Saltpans, the Common Tern’s survival depends entirely on the active management. The expected climate change, with increasing sea level rise and consequently more frequent flooding of low-lying areas, further aggravates its existence and survival in the Sečovlje Saltpans.

Phytoremediation: Climate change resilience and sustainability assessment at a coastal brownfield redevelopment

Phytoremediation offers a nature based solution (NBS) for contaminated soil remediation; however, its application under a brownfield redevelopment context has not been well studied. Moreover, climate change could impact large numbers of contaminated sites, yet there remains little research on the potential impacts for remediation. This study examined phytoremediation at a brownfield redevelopment in the San Francisco Bay area, where thousands of cleanup sites are vulnerable to rising sea levels. Life cycle assessment (LCA) was used to determine both primary and secondary impacts and the system's resilience to various sea level scenarios and hydroclimatic conditions was investigated. It was found that the phytoremediation project rendered only a small environmental footprint, and was associated with low cost and substantial socioeconomic benefits. For instance, it fitted well with the site redevelopment setting by offering attractive landscape features. Moreover, under a modeled moderate sea level rise scenario, the groundwater hydraulic gradient at the site decreased, which was coupled with greater natural biodegradation and reduced plume migration, and, therefore, lower life cycle impact. There was also minimal increase in the vapor intrusion risk with increased sea level. Overall, phytoremediation at the site was found to be resilient to a moderate sea level rise and other hydroclimatic effects induced by climate change. However, the system performance responded to increasing sea level rise in a non-linear manner. Under a high sea level rise scenario, the system is predicted to perform abruptly worse.

Stepwise extreme learning machine for statistical downscaling of daily maximum and minimum temperature

Increasing temperature from climate change can bring a number of different risks such as more droughts and heat waves, and increasing sea level rise. Assessment of climate change with future scenarios is essential to adapt these impacts. To provide climate change information through the outputs of general circulation models at finer resolution, a reliable and accurate downscaling model has always been of great interest. Meeting this need, artificial neural network (ANN) has been commonly employed in downscaling for nonlinear models. Extreme learning machine (ELM), a recently developed ANN, is an efficient learning algorithm for generalized single hidden layer feedforward neural networks. In light of its simple learning algorithm, we introduced a useful approach to combine the stepwise feature selection method into ELM for temperature downscaling, as stepwise ELM (SWELM), since model complexity and computational time consumption of a traditional ANN impedes application of stepwise feature selection. This SWELM is able to identify the most influential predictors in a dataset and use them to train a nonlinear model while removing the irrelevant ones. The ELM and SWELM as well as regular ANN were tested in a simulation study. Results indicated that ELM even with randomness of weights and biases in the nodes of input and hidden layers better performed than did ANN. Also, SWELM presents a capability to select the influential predictors and remove the unrelated variables. A case study with downscaling temperature of Wisconsin, USA, showed that ELM was a comparable alternative to ANN. SWELM outperformed the ANN algorithm for temperature downscaling and sometimes predicted the temperature increase larger than did others for future scenarios. The current study of temperature downscaling with the statistical tool allows assessing the possible impacts of climate change in a local scale and some developing countries where sophisticate research cannot be eligible.

Adaptation, Sea Level Rise, and Property Prices in the Chesapeake Bay Watershed.

Coastal communities are facing the dual threat of increasing sea level rise (SLR) and swelling populations, causing challenging policy problems. To help inform policy makers, this paper explores the property price impact of structures that help protect against SLR using a novel and spatially explicit dataset of coastal features. Results indicate that adaptation structures can have a significant positive impact on waterfront home prices, with the most vulnerable homes seeing the largest impacts. The Chesapeake Bay is facing increasing pressure from SLR, and this is one of the first papers to report that local property markets are incorporating that threat.

Vulnerability of Coastal Resort Cities to Mean Sea Level Rise in the Mexican Caribbean

We evaluated the potential economic impacts of increasing sea level rise (SLR) along the Mexican Caribbean where there are major gaps in our understanding of the mechanisms controlling flooding duration and frequency associated to future ecological and economic impacts. We determined the negative economic impact of SLR on infrastructure in the largest urban centers (Cancun, Isla Mujeres, Playa del Carmen, Puerto Morelos and Cozumel) in the state of Quintana Roo (Mexico) that are considered the largest tourism “hot spots” (resort cities) in the country. The tourism industry in this coastal area injects >8 billion dollars year−1 to the Mexican economy. Our conservative economic assessment regarding the impact of SLR, under a 1 m scenario for all coastal cities is $330 million USD. Further projections for worst scenarios (SLR >2 m) show a non-linear trend where the cost of inaction can reach up to $1.4 billion USD (2 m SLR scenario) and $2.3 billion USD (3 m SLR scenario). This potential loss of infrastructure, as construction cost, is staggering and represents a robust baseline to start evaluating with more detail future impacts of climate variability and change on the Mexican Caribbean coastline.

Ocean Acidification: An Introduction

Ocean acidification (OA) generally refers to the ongoing decrease in ocean pH. Ocean acidification is caused primarily by the oceanic uptake of excess carbon dioxide (CO2) from the atmosphere. Other impacts related to climate change (increased sea level rise, coastal flooding and extreme weather events) often receive more attention than OA, but the acidification of the Earth’s oceans is well documented and is a major concern for the marine science community. This publication is the first in a series that addresses ocean acidification in Florida. It specifically explains the changes that are occurring to the chemistry of our coastal and oceanic waters because of elevated carbon dioxide levels. Additional publications address potential environmental, economic, and social implications for Florida.

Disaster mitigation of climate change effects on small islands (case of Harapan and Kelapa Islands)

The vulnerability is the sequence of condition that determines whether a hazard will cause disaster or not. The small islands are easily affected by the climate change effects. The small islands are particularly vulnerable to the projected of climate change effects. Harapan and Kelapa Islands is a small island in the Thousand Islands Region, DKI Jakarta Province. This study aims to analyze of climate change effects on social, economic, and environmental on small islands. This study using key indicators consist of social, economic, environment, and climate change. The methods applied in this research is GIS and system dynamics or called by spatial dynamics. The result showed that the area of study categorized as the vulnerable area to the climate change effects, this is due to the increasing sea level rise and rainfall, the growing population number and density, and the expanding built area. Therefore, the need for disaster mitigation and adaptation efforts on the climate change effects.

Mapping inundation probability due to increasing sea level rise along El Puerto de Santa María (SW Spain)

Global sea levels have risen through the twentieth and twenty-first centuries. This rise will almost certainly continue and probably accelerate during the rest of the twenty-first century, albeit there is strong disagreement about the range of future sea level rise due to uncertainties regarding scenarios and emission of greenhouse gasses. Although the impacts of sea level rise are diverse, inundation during high tides is one of the most obvious and immediate consequences. A probabilistic methodology for mapping the inundation hazard because of sea level rise has been applied to the coast of El Puerto de Santa Maria in the province of Cadiz in southwest Spain. This methodology involves a step forward since represents the full range of probabilities, associated with each scenario of sea level rise considered, and thus offers a more realistic view of the probability of inundation in each area. Results show large differences in the spatial distribution of probable inundation in urban areas and wetlands leading to different consequences for management actions.

Characterizing the 2D shape complexity dynamics of the islands of Sundarbans, Bangladesh: a fractal dimension approach

Fractal dimension index (FDI) and shape index (SI) of the islands of Bangladesh Sundarbans situated at the estuarine part of the Ganges–Brahmaputra–Meghna (GBM) delta were estimated with the aid of remote sensing techniques between the years 1989 and 2010. The main objective was to correlate the temporal change in these two indices within two decades with the possible geomorphic processes regulating these patterns. The Sundarban region is composed of almost 200 islands having self-similar coastlines with FDI and SI ranged from 1.002 to 1.202 and 1.016 to 7.546, respectively. Both FDI and SI values along with their temporal change showed that the complexity and irregularity in the island shape increased in the northern and north-eastern parts of the Sundarbans, while in the southern end it exhibited an opposite trend. Apart from a few exceptions, the longer serrated coastlines of the north (FDI > 1.18) became more serrated and rough due to the predominant tidal effect (particularly ebb tidal flow) within the two decades. The comparatively smoother coastlines of the southern islands (FDI < 1.18) became more compact and circular due to strong sea wave action during the same course of time. The spatial variation in FDI was explained in terms of the relative elevation of the islands, which was found to be lower in the northern part, their differential response to rising sea level and the amplified tidal action in this funnel shaped estuary. Apart from changes in fractal dimension, a net land loss of ≈ 60 km2 was observed within this island system during the study period. These observations imply that with an increasing sea level rise, the northern and southern parts of Sundarbans Island system will respond differentially, resulting in inundation in northern area (water encroachment in the low-lying islands) and land loss in the southern part (erosion in the coastal boundary) causing a severe loss of ecosystem services provided by the mangrove forest.

The role of economic, policy, and ecological factors in estimating the value of carbon stocks in Everglades mangrove forests, South Florida, USA

Old growth mangroves in existing protected areas store more carbon than restored forests or plantations. Carbon storage in such forests has economic value independent of additionality, offering opportunities for policy makers to ensure their maintenance, and inclusion in climate change mitigation strategies. Mangrove forests of the Everglades National Park (ENP), South Florida, though protected, face external stressors such as hydrological alterations because of flooding control structures and agriculture impacts and saltwater intrusion as a result of increasing sea level rise. Moreover, decreased funding of Everglades’ restoration activities following the recent economic crisis (beginning 2008) threatens the restoration of the Greater Everglades including mangrove dominated coastal regions. We evaluate several economic and ecological challenges confronting the economic valuation of total (vegetation plus soil) organic carbon (TOC) storage in the ENP mangroves. Estimated TOC storage for this forested wetland ranges from 70 to 537 Mg C/ha and is higher than values reported for tropical, boreal, and temperate forests. We calculate the average abatement cost of C specific for ENP mangroves to value the TOC from $2–$3.4 billion; estimated unit area values are $13,859/ha–$23,728/ha. The valuation of the stored/legacy carbon is based on the: 1) ecogeomorphic attributes, 2) regional socio-economic milieu, and 3) status of the ENP mangroves as a protected area. The assessment of C storage estimates and its economic value can change public perception about how this regulating ecosystem service of ENP mangrove wetlands (144,447ha) supports human well-being and numerous economic activities. This perception, in turn, can contribute to future policy changes such that the ENP mangroves, the largest mangrove area in the continental USA, can be included as a potential alternative in climate change mitigation strategies.

Flood and Storm Hazard Adaptation in New Jersey’s Coastal Zone: Barriers and Opportunities

New Jersey’s coastal zone has a long history of storm and flood hazard vulnerability, as documented by copious technical reports, historical maps and surveys, storm damage assessments and flood insurance claims. In the context of geologic time, this vulnerability can be attributed, in part, to increasing sea level rise resulting from melting of Pleistocene glaciers. In the context of human time, extensive development, redevelopment and urbanization of the New Jersey coast has contributed significantly to this vulnerability. At the same time, financial constraints at the state and federal level and increasing taxpayer liability for damage recovery costs will create challenges in long-term adaptation. A number of New Jersey academics have identified the magnitude of natural hazard vulnerabilities and the importance of mitigation to promote public safety, with James K. Mitchell of Rutgers University being one of the notable contributors to that effort. Current mitigation measures may be partially effective in protecting people and property in the short term. However, barriers to effective hazard area management and adaptation planning, including physical, financial, social, demographic and political constraints, need to be addressed. Understanding the scope and impact of these barriers is critical to developing the necessary long-term adaptation plans that will promote a safe and sustainable future for New Jersey.

Influence of the Wax Lake Delta sediment diversion on aboveground plant productivity and carbon storage in deltaic island and mainland coastal marshes

Coastal Louisiana is experiencing a significant loss of coastal wetland area due to increasing sea level rise, subsidence, sediment starvation and marsh collapse. The construction of large scale Mississippi River sediment diversions is currently being planned in an effort to help combat coastal wetlands losses at a rate of >50 km−2 y−1. The Wax Lake Delta (WLD) is currently being used as a model for evaluating potential land gain from large scale diversions of Mississippi River water and sediment. In this study, we determine the impact of the WLD diversion on plant production at newly formed islands within the delta and adjacent, mainland freshwater marshes. Plant aboveground productivity, sediment nutrient status and short term accretion were measured at three locations on a transect at each of three fresh water marsh sites along Hog Bayou and at six newly formed emerging island sites in the delta. Spring flooding has resulted in a greater increase in plant production and consequently, greater carbon sequestration potential in adjacent mainland marshes compared to the newly formed island sites, which contain less total carbon (C), nitrogen (N), and phosphorus (P) in the sediment. While sediment diversions are predicted to create land, as seen in island formation in the WLD, the greatest benefit of river sediment diversions from a carbon credit perspective might be to the adjacent freshwater mainland marshes for several reasons. Both greater plant production and sediment C accumulation are two important factors for marsh stability, while perhaps even more critical, is the prevention of the loss of stored sediment C in the marsh profile. This stored C would be lost without the introduction of freshwater, nutrients and sediment through river sediment diversion efforts.

Monitoring sea level rise-induced hazards along the coast of Accra in Ghana

Sea level rise, increased erosion and flooding threaten vulnerable coastal communities globally. Monitoring the changes in the coastal zone enables the risk levels to be detected and quantified. Such information facilitates developing sustainable policies to effectively manage hazards in the coastal zone. This study used available geospatial data to assess the physical state of the Accra coast and established ground control points that will facilitate effective monitoring of change. The data used included a bathymetric map (hard copy) with last revision in 1992, digital topographic map (2002) of the coast, 2005 orthophoto map and the geology map of Accra. The reliability of the data was determined, and the data were analysed using GIS tool. Ten concrete ground control points were established, mapped using DGPS and connected to the Ghana national coordinate system to form a network for effective monitoring in the coastal zone. The results revealed that the western region of the Accra coast has lower elevations onshore which will facilitate inundation from sea level rise. Comparing nearshore bathymetric profiles indicates that the eastern coast is deeper relative to the central and western. This will enable waves to break closer to the coast under increasing sea level rise thereby dissipating energy to facilitate sediment transport. Computed potential sediment transport rate revealed that the rate ranges between 4.1 × 105 and 7.2 × 105 m3/year. Using the control points established as reference points to monitor the coastal system will enable changes that can result in hazard to be detected and quantified.

Doubling of coastal erosion under rising sea level by mid-century in Hawaii

Chronic erosion in Hawaii causes beach loss, damages homes and infrastructure, and endangers critical habitat. These problems will likely worsen with increased sea level rise (SLR). We forecast future coastal change by combining historical shoreline trends with projected accelerations in SLR (IPCC RCP8.5) using the Davidson-Arnott profile model. The resulting erosion hazard zones are overlain on aerial photos and other GIS layers to provide a tool for identifying assets exposed to future coastal erosion. We estimate rates and distances of shoreline change for ten study sites across the Hawaiian Islands. Excluding one beach (Kailua) historically dominated by accretion, approximately 92 and 96 % of the shorelines studied are projected to retreat by 2050 and 2100, respectively. Most projections (~80 %) range between 1–24 m of landward movement by 2050 (relative to 2005) and 4–60 m by 2100, except at Kailua which is projected to begin receding around 2050. Compared to projections based only on historical extrapolation, those that include accelerated SLR have an average 5.4 ± 0.4 m (±standard deviation of the average) of additional shoreline recession by 2050 and 18.7 ± 1.5 m of additional recession by 2100. Due to increasing SLR, the average shoreline recession by 2050 is nearly twice the historical extrapolation, and by 2100 it is nearly 2.5 times the historical extrapolation. Our approach accounts for accretion and long-term sediment processes (based on historical trends) in projecting future shoreline position. However, it does not incorporate potential future changes in nearshore hydrodynamics associated with accelerated SLR.