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At least 145 records · Page 8Linked to original sources
USGS2007

Coupling alongshore variations in wave energy to beach morphologic change using the SWAN wave model at Ocean Beach, San Francisco, CA

Coastal managers have faced increasing pressure to manage their resources wisely over the last century as a result of heightened development and changing environmental forcing. It is crucial to understand seasonal changes in beach volume and shape in order to identify areas vulnerable to accelerated erosion. Shepard (1950) was among the first to quantify seasonal beach cycles. Sonu and Van Beek (1971) and Wright et al. (1985) described commonly occurring beach states. Most studies utilize widest spaced 2-D cross shore profiles or shorelines extracted from aerial photographs (e.g. Winant et al. 1975; Aubrey, 1979, Aubrey and Ross, 1985; Larson and Kraus, 1994; Jimenez et al., 1977; Lacey and Peck, 1998; Guillen et al., 1999; Norcorss et al., 2002) to analyzed systematic changes in beach evolution. But with the exception of established field stations, such as Duck, NC (Birkemeier and Mason, 1984), ans Hazaki Oceanographical Research Station (HORS) in Japan (Katoh, 1997), there are very few beach change data sets with high temporal and spatial resolutions (e.g. Dail et al., 2000; Ruggiero et al., 2005; Yates et al., in press). Comprehensive sets of nearshore morphological data and local in situ measurements outside of these field stations are very rare and virtually non-existent high-energy coasts. Studied that have attempted to relate wave statistics to beach morphology change require some knowledge of the nearshore wave climate, and have had limited success using offshore measurement (Sonu and Van Beek, 1971; Dail et al., 2000). The primary objective of this study is to qualitatively compare spatially variable nearshore wave predictions to beach change measurements in order to understand the processes responsible for a persistent erosion 'hotspot' at Ocean Beach, San Francisco, CA. Local wave measurements are used to calibrate and validate a wave model that provides nearshore wave prediction along the beach. The model is run for thousands of binned offshore wave conditions to help isolate the effects of offshore wave direction and period on nearshore wave predictions. Alongshore varying average beach change statistics are computed at specific profile locations from topographic beach surveys and lidar data. The study area is located in the San Francisco Bight in central California. Ocean Beach is a seven kilometer long north-south trending sandy coastline located just south of the entrance to the San Francisco Bay Estuary (Figure 1). It contains an erosion hotspot in the southern part of the beach which has resulted in damage to local infrastructure and is the cause of continued concern. A wide range of field data collection and numerical modeling efforts have been focused here as part of the United States Geological Survey's (USGS) San Francisco Bight Coastal Processes Study, which began in October 2003 and represents the first comprehensive study of coastal processes at the mouth of San Francisco Bay. Ocean Beach is exposed to very strong tidal flows, with measured currents often in excess of 1 m/s at the north end of the beach. Current profiler measurements indicate that current magnitudes are greater in the northern portion of the beach, while wave energy is greater in the southern portion where erosion problems are greatest (Barnard et al., 2007). The sub-aerial beach volume fluctuates seasonally over a maximum envelope of 400,000 m 3 for the seven kilometer stretch (Barnard et al, 2007). The wave climate in the region is dominated by an abundance of low frequency energy (greater than 20 s period) and prevailing northwest incident wave angles. The application of a wave model to the region is further complicated by the presence of the Farallon Islands 40 kilometers west, and a massive ebb tidal delta at the mouth of San Francisco Bay (~150 km 2 ), which creates complicated refraction patterns as wave energy moves from offshore Ocean Beach; however the cost and threat of the energetic nearshore environment have limited the temporal and spatial resolution of these measurements. Applying numerical models to predict wave and current patterns along the beach can help supplement the filed data that exists and provide opportunities to make prediction about the impacts of changing environmental forcing.

California↗
USGS2022

Local populations of eastern oyster from Louisiana differ in low salinity tolerance

Eastern oysters Crassostrea virginica support a critical commercial industry and provide many ecosystem services to coastal estuaries yet are currently threatened by changing estuarine conditions. A changing climate and the effects of river and coastal management are altering freshwater inflows into productive oyster areas, causing more frequent and extreme salinity exposure. Although eastern oysters are tolerant to a wide range of salinity means and variations, more frequent and extreme exposure to low salinity (<5‰) impacts oyster populations and aquaculture operations. This study assessed four Louisiana eastern oyster stocks to explore population-specific responses to low-salinity exposure. Hatchery-produced progeny (10–25 mm) were deployed in baskets kept off-bottom on longline systems in a low-salinity (mean ± 1 standard error of the mean daily salinity = 8.7 ± 0.2‰; range = 1.2–19.0‰) and a moderate-salinity (16.8 ± 0.3‰; 4.8–30.0‰) environment for 1 year, beginning in December 2019, with growth and mortality determined monthly. Significant differences in cumulative mortality between stocks at the end of the study were found at the low-salinity site, with the greatest increase in cumulative mortality occurring mid-July to mid-August. Mortality differences between stocks suggest that some eastern oyster populations (i.e., stocks) may be better suited to low salinity or low-salinity events than others. This difference may be attributed to similarity between site of origin and grow-out site conditions and/or to greater salinity variability and therefore higher phenotypic plasticity in some eastern oyster populations compared with others. The identification of oyster stocks able to survive under extreme low-salinity conditions may facilitate the development of “low-salinity-tolerant” broodstock to support aquaculture in areas experiencing and predicted to experience low-salinity events.

Louisiana↗
USGS2010

Evaluating ecological equivalence of created marshes: comparing structural indicators with stable isotope indicators of blue crab trophic support

This study sought to examine ecological equivalence of created marshes of different ages using traditional structural measures of equivalence, and tested a relatively novel approach using stable isotopes as a measure of functional equivalence. We compared soil properties, vegetation, nekton communities, and &delta; 13 C and &delta; 15 N isotope values of blue crab muscle and hepatopancreas tissue and primary producers at created (5-24 years old) and paired reference marshes in SW Louisiana. Paired contrasts indicated that created and reference marshes supported equivalent plant and nekton communities, but differed in soil characteristics. Stable isotope indicators examining blue crab food web support found that the older marshes (8 years+) were characterized by comparable trophic diversity and breadth compared to their reference marshes. Interpretation of results for the youngest site was confounded by the fact that the paired reference, which represented the desired end goal of restoration, contained a greater diversity of basal resources. Stable isotope techniques may give coastal managers an additional tool to assess functional equivalency of created marshes, as measured by trophic support, but may be limited to comparisons of marshes with similar vegetative communities and basal resources, or require the development of robust standardization techniques.

Estuaries and Coasts↗
USGS2019

Marshes are the new beaches: Integrating sediment transport into restoration planning

Recent coastal storms and associated recovery efforts have led to increased investment in nature-based coastal protection, including restoration of salt marshes and construction of living shorelines. In particular, many of these efforts focus on increasing vertical elevation through sediment nourishment, where sediment is removed from the tidal channel and placed on the marsh plain, or preventing lateral erosion through shoreline protection. In the USA alone, millions of dollars have been allocated or spent on these coastal protection solutions over the last few decades because of their perceived sustainability and ecologically positive co-benefits including habitat provision and carbon sequestration. These projects would benefit from integration of sediment transport pathways, budgets, and metrics during planning and modeling of restoration outcomes, in order to evaluate sustainability before investment. This is analogous to the decades of experience with coastal management and engineering on the open coast. Salt marshes are geomorphic features that rely partially on external sediment supply to maintain their network of tidal channels, intertidal flats, and marsh plain. Removing sediment from one component of the overall system to nourish another component may be counterproductive, given that the net sediment budget is unchanged. For example, dredging a tidal channel beyond its equilibrium condition will cause it to fill with sediment from the tidal flat or elsewhere in the system. This may cause slumping of the marsh edge, or over-deepening of other sections of the channel to compensate. Similarly, shoreline protection that prevents edge erosion hampers the marsh plain’s ability to accrete on the levee and naturally transgress landward or it starves other components of the system of regularly supplied sediment. A limited vertical or lateral-only perspective, instead of a three-dimensional perspective, during project planning and evaluation may lead to suboptimal decision-making regarding restoration priorities, approaches, and outcomes. I contend that before significant investments are made in marsh restoration through sediment nourishment or shoreline protection, sediment transport measurements and models that consider sediment dynamics should be integrated into the early phases of restoration planning. This will help identify where and under what conditions marsh restoration will most likely be successful and economically justified. Triaging and prioritizing is then possible, which is a sustainable approach for restoration, given the persistent vulnerability of marshes to sea-level rise, storms, and sediment deficits.

Estuaries and Coasts↗
USGS2022

Within-marsh and landscape features structure ribbed mussel distribution in Georgia, USA, marshes

Ribbed mussels, Geukensia demissa , are marsh fauna that are used in coastal management and restoration due to the ecosystem services they provide. Ribbed mussel restoration efforts may be improved with a greater understanding of the environmental drivers of ribbed mussel distribution at multiple spatial scales to predict areas where restoration could be successful. This study sought to estimate the effects of within-marsh (4 m) and landscape (500 m) factors on ribbed mussel distribution. Ribbed mussel densities were surveyed at 11 sites along the coast of Georgia, USA, and overlaid with spatial data for within-marsh factors (elevation, distance to marsh features, slope) as well as landscape factors (percent cover by subtidal creek, forest, and development within a 500-m radius). The distribution model was then validated using three previously unsurveyed marshes and explained 55% of the variance in ribbed mussel abundance. Ribbed mussel abundances and occupancy were most sensitive to changes in within-marsh factors (elevation and distance to subtidal creeks, bodies of water inundated during the full tidal cycle) but were also sensitive to landscape features (percent landcover of forests and development). The highest ribbed mussel densities were found in mid-elevation areas (~ 0.7 m NAVD88), far from subtidal creeks, and in marshes surrounded with forest and development. These results contrast with distributions in the northeastern USA, where ribbed mussels are distributed along subtidal creek banks. This work suggests that restoration may be most effective when focused on appropriate elevations and at locations away from the marsh-creek ecotone.

Georgia↗
USGS2024

7.10 - Beneficiaries, equity, and trade-offs in estuarine and coastal ecosystem services

Estuarine and coastal ecosystems support human populations in myriad ways. Traditionally, researchers have focused on the biophysical processes that underlie these benefits and their economic values. In the decade since the 1st Treatise, the literature on cultural ecosystem services, human health benefits, and the equitable distribution of societal benefits and burdens has grown tremendously. In this chapter we outline three dimensions of equity as they relate to estuarine and coastal ecosystems: procedural, recognitional, and distributional equity. We then apply the dimensions of equity to a suite of provisioning, regulating, and cultural ecosystem services. Finally, we explore trade-offs and beneficiaries of these ecosystem services using three case studies that consider equity in a variety of estuarine and coastal management decisions.

Book chapter↗
USGS2015

Classification of rocky headlands in California with relevance to littoral cell boundary delineation

Despite extensive studies of hydrodynamics and sediment flux along beaches, there is little information on the processes, pathways and timing of water and sediment transport around rocky headlands. In this study, headlands along the California coast are classified to advance understanding of headland dynamics and littoral cell boundaries in support of improved coastal management decisions. Geomorphological parameters for 78 headlands were quantified from geological maps, remote-sensing imagery, navigational charts, and shoreline geospatial databases. K -means cluster analysis grouped the headlands into eight distinct classes based on headland perimeter, bathymetric slope ratio, and the headland apex angle. Wave data were used to investigate the potential for sediment transport around the headland types and determine the efficacy of the headland as a littoral cell boundary. Four classes of headland appear to function well as littoral cell boundaries, with headland size (e.g., perimeter or area) and a marked change in nearshore bathymetry across the headland being relevant attributes. About half of the traditional California littoral cell boundaries align with headland classes that are expected to perform poorly in blocking alongshore sediment transport, calling into question these boundaries. Better definition of these littoral cell boundaries is important for regional sediment management decisions.

California↗
USGS2016

Decoupling processes and scales of shoreline morphodynamics

Behavior of coastal systems on time scales ranging from single storm events to years and decades is controlled by both small-scale sediment transport processes and large-scale geologic, oceanographic, and morphologic processes. Improved understanding of coastal behavior at multiple time scales is required for refining models that predict potential erosion hazards and for coastal management planning and decision-making. Here we investigate the primary controls on shoreline response along a geologically-variable barrier island on time scales resolving extreme storms and decadal variations over a period of nearly one century. An empirical orthogonal function analysis is applied to a time series of shoreline positions at Fire Island, NY to identify patterns of shoreline variance along the length of the island. We establish that there are separable patterns of shoreline behavior that represent response to oceanographic forcing as well as patterns that are not explained by this forcing. The dominant shoreline behavior occurs over large length scales in the form of alternating episodes of shoreline retreat and advance, presumably in response to storms cycles. Two secondary responses include long-term response that is correlated to known geologic variations of the island and the other reflects geomorphic patterns with medium length scale. Our study also includes the response to Hurricane Sandy and a period of post-storm recovery. It was expected that the impacts from Hurricane Sandy would disrupt long-term trends and spatial patterns. We found that the response to Sandy at Fire Island is not notable or distinguishable from several other large storms of the prior decade.

New York↗
USGS2020

Modeling pathogen dispersal in marine fish and shellfish

Bio-physical models are a useful tool for understanding dispersal and transmission of marine pathogens. While utilized for larval dispersal models, they are only recently being used in epidemiological studies and are currently underutilized by the marine epidemiology field. Bio-physical models are useful for spatial planning and coastal management. For example, they have been used for spatial planning of salmon farm site locations, and to establish early warning networks. Bio-physical modeling can be used to test hypotheses, rather than simply develop them. Model resolution and computation demands must be balanced when making decisions about model parameters. Epidemiological bio-physical models are in their infancy. While they have proven useful so far, future applications of these models can incorporate more aspects of disease dynamics and address many additional questions.

Trends in Parasitology↗
USGS2016

Mapping changing distributions of dominant species in oil-contaminated salt marshes of Louisiana using imaging spectroscopy

The April 2010 Deepwater Horizon (DWH) oil spill was the largest coastal spill in U.S. history. Monitoring subsequent change in marsh plant community distributions is critical to assess ecosystem impacts and to establish future coastal management priorities. Strategically deployed airborne imaging spectrometers, like the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), offer the spectral and spatial resolution needed to differentiate plant species. However, obtaining satisfactory and consistent classification accuracies over time is a major challenge, particularly in dynamic intertidal landscapes. Here, we develop and evaluate an image classification system for a time series of AVIRIS data for mapping dominant species in a heavily oiled salt marsh ecosystem. Using field-referenced image endmembers and canonical discriminant analysis (CDA), we classified 21 AVIRIS images acquired during the fall of 2010, 2011 and 2012. Classification results were evaluated using ground surveys that were conducted contemporaneously to AVIRIS collection dates. We analyzed changes in dominant species cover from 2010 to 2012 for oiled and non-oiled shorelines. CDA discriminated dominant species with a high level of accuracy (overall accuracy = 82%, kappa = 0.78) and consistency over three imaging dates (overall 2010 = 82%, overall 2011 = 82%, overall 2012 = 88%). Marshes dominated by Spartina alterniflora were the most spatially abundant in shoreline zones (≤ 28 m from shore) for all three dates (2010 = 79%, 2011 = 61%, 2012 = 63%), followed by Juncus roemerianus (2010 = 11%, 2011 = 19%, 2012 = 17%) and Distichlis spicata (2010 = 4%, 2011 = 10%, 2012 = 7%). Marshes that were heavily contaminated with oil exhibited variable responses from 2010 to 2012. Marsh vegetation classes converted to a subtidal, open water class along oiled and non-oiled shorelines that were similarly situated in the landscape. However, marsh loss along oil-contaminated shorelines doubled that of non-oiled shorelines. Only S. alterniflora dominated marshes were extensively degraded, losing 15% (354,604 m 2 ) cover in oiled shoreline zones, suggesting that S. alterniflora marshes may be more vulnerable to shoreline erosion following hydrocarbon stress, due to their landscape position.

Louisiana↗
USGS2011

Networks - The assessment of marine reserve networks: Guidelines for ecological evaluation

As marine ecosystems are plagued by an ever-increasing suite of threats including climate change, pollution, habitat degradation, and fisheries impacts (Roessig et al ., 2004; Lotze et al ., 2006; Jackson, 2008), there are now no ocean areas that are exempt from anthropogenic impacts (Halpern et al ., 2008). In order to preserve marine biodiversity, ecosystem function, and the goods and services provided by resistant and/or resilient systems, marine reserves have been increasingly recommended as part of an ecosystem-based approach to management (Browman and Stergiou, 2004; Levin et al ., 2009). Marine reserves are defined as “areas of the ocean completely protected from all extractive and destructive activities” (Lubchenco et al ., 2003) and can be experimental controls for evaluating the impact of these activities on marine ecosystems. Growing scientific information has shown consistent increases in species density, biomass, size, and diversity in response to full protection inside reserves of varying sizes and ages located in diverse regions (Claudet et al ., 2008; Lester et al ., 2009; Molloy et al ., 2009). However, most of these data are from individual marine reserves and therefore have inherently limited transferability to networks of marine reserves, which when properly designed can outperform single marine reserves for a variety of ecological, economic, and social management goals (Roberts et al ., 2003; Almany et al ., 2009; Gaines et al ., 2010). The concept of marine reserve networks grew out of a desire to achieve both conservation and fishery management goals by minimizing the potential negative economic, social, and cultural impacts of a single large reserve while still producing similar or even greater ecological and economic returns (Murray et al ., 1999; Gaines et al ., 2010). In addition, reserves networks can provide insurance by protecting areas across a region and spreading the risk that these sites may be impacted by localized catastrophes such as hurricanes or oil spills (Allison et al ., 2003). The World Conservation Union's Marine Programme defines a network as “a collection of individual marine protected areas (MPAs) or reserves operating co-operatively and synergistically, at various spatial scales and with a range of protection levels that are designed to meet objectives that a single reserve cannot achieve” (IUCN–WCPA, 2008). However, general terms such as “co-operatively” and “synergistically” can have myriad meanings. Without a clear definition of a network, it becomes difficult to identify attainable management goals and design a process for evaluating whether the network achieves those goals. Besides, different management goals may in turn result in the need for different types of networks. The use of MPAs with varying protection levels together with no-take zones in multiple-zoning schemes adds another layer of complexity to network design and evaluation; however, partially protected areas are generally used to manage coastal uses and avoid conflicts (rather than for strict ecological purposes) and are therefore a function of the local social, economic, and cultural context. As we are here interested in the ecological effects of networks, for the purposes of this chapter, we focus on marine reserves because these areas are no-take and therefore offer greater ecological benefits than other types of MPAs that allow some forms of extraction (Lester and Halpern, 2008).

Book chapter↗
USGS2011

A Bayesian network to predict coastal vulnerability to sea level rise

Sea level rise during the 21st century will have a wide range of effects on coastal environments, human development, and infrastructure in coastal areas. The broad range of complex factors influencing coastal systems contributes to large uncertainties in predicting long-term sea level rise impacts. Here we explore and demonstrate the capabilities of a Bayesian network (BN) to predict long-term shoreline change associated with sea level rise and make quantitative assessments of prediction uncertainty. A BN is used to define relationships between driving forces, geologic constraints, and coastal response for the U.S. Atlantic coast that include observations of local rates of relative sea level rise, wave height, tide range, geomorphic classification, coastal slope, and shoreline change rate. The BN is used to make probabilistic predictions of shoreline retreat in response to different future sea level rise rates. Results demonstrate that the probability of shoreline retreat increases with higher rates of sea level rise. Where more specific information is included, the probability of shoreline change increases in a number of cases, indicating more confident predictions. A hindcast evaluation of the BN indicates that the network correctly predicts 71% of the cases. Evaluation of the results using Brier skill and log likelihood ratio scores indicates that the network provides shoreline change predictions that are better than the prior probability. Shoreline change outcomes indicating stability (-1 < rate < 1 m/yr) or erosion (rate < -1 m/yr) tend to occur for two sets of input scenarios. Stable shoreline change rates occur mainly for low rates of relative sea level rise and occur in low-vulnerability geomorphic settings. Rates indicating erosion result for cases where the rate of relative sea level rise is high and moderate-to-high vulnerability geomorphic settings occur. In contrast, accretion (rate > 1 m/yr) was not well predicted. We find that BNs can assimilate important factors contributing to coastal change in response to sea level rise and can make quantitative, probabilistic predictions that can be applied to coastal management decisions. Copyright ?? 2011 by the American Geophysical Union.

Journal of Geophysical Research F: Earth Surface↗
USGS2026

Exploring future ecogeomorphic state transitions of an undeveloped barrier island: Multidecadal model projections for North Core Banks, NC, USA

Ecogeomorphic state transitions in coastal barrier systems will be impacted and likely amplified by projected accelerated sea-level rise and enhanced storm intensity over the next several decades. When, where, and how these transitions will take place remain uncertain and complex, yet are of primary interest to coastal managers looking to prepare for future changes. Here, we apply the new Mesoscale Explicit Ecogeomorphic Barrier model to generate probabilistic projections of future ecogeomorphic state transitions up to year 2050 for the undeveloped North Core Banks (NCB), North Carolina, United States. In our full probabilistic projection, which accounts for stochasticity from uncertainty in sea-level rise and high-water event (HWE) projections, loss of barrier interior to passive sea-level rise submergence dominates ecogeomorphic state transitions, suggesting that the biggest threat to many undeveloped barriers in the next several decades will come from the back-barrier rather than ocean-side. Additionally, this projection suggests that dune and unvegetated interior states are most volatile, with the intensity of state transitions varying significantly alongshore. In projections simulating a range of deterministic sea-level rise rates, higher rates enhance: overwash frequency; loss of beach and dune states; and interior submergence. We also find that state transitions are less sensitive to HWE intensity than sea-level rise, and that more frequent, moderate HWEs—rather than the largest events—may be the principal drivers of mesoscale ecogeomorphic state change. Our projections highlight important future mesoscale trends of ecogeomorphic state transitions for NCB that are likely relevant to other stable, sediment-rich barrier systems of U.S. coastlines.

North Carolina↗
USGS2025

Benchmarking shoreline prediction models over multi-decadal timescales

Robust predictions of shoreline change are critical for sustainable coastal management. Despite advancements in shoreline models, objective benchmarking remains limited. Here we present results from ShoreShop2.0, an international collaborative benchmarking workshop, where 34 groups submitted shoreline change predictions in a blind competition. Subsets of shoreline observations at an undisclosed site (BeachX) over short (5-year) and medium (50-year) periods were withheld from modelers and used for model benchmarking. Using satellite-derived shoreline datasets for calibration and evaluation, the best performing models achieved prediction accuracies on the order of 10 m, comparable to the accuracy of the satellite shoreline data, indicating that certain beaches can be modelled nearly as well as they can be remotely observed. The outcomes from this collaborative benchmarking competition critically review the present state-of-the-art in shoreline change prediction as well as reveal model limitations, facilitate improvements, and offer insights for advancing shoreline-prediction capabilities.

New South Wales↗
USGS2012

Integrating field research, modeling and remote sensing to quantify morphodynamics in a high-energy coastal setting, ocean beach, San Francisco, California

Wave and coastal circulation modeling are combined with multibeam bathymetry, high-resolution beach surveys, cross-shore Personal Water Craft surveys, digital bed sediment camera surveys, and real-time video monitoring to quantify morphological change and nearshore processes at Ocean Beach, San Francisco. Initial SWAN (Simulating Waves Nearshore) wave modeling results show a focusing of wave energy at the location of an erosion hot spot on the southern end of Ocean Beach during prevailing northwest swell conditions. During El Nin??o winters, swell out of the west and southwest dominates the region, and although the wave energy is focused further to the north on Ocean Beach, the oblique wave approach sets up a strong northerly littoral drift, thereby starving the southern end of sediment, leaving it increasingly vulnerable to wave attack when the persistent northwest swell returns. An accurate assessment of the interaction between wave and tidal processes is crucial for evaluating coastal management options in an area that includes the annual dredging and disposal of ship channel sediment and an erosion hot spot that is posing a threat to local infrastructure. Copyright ASCE 2006.

Conference Paper↗
USGS2024

Hydrodynamic and salinity tesponse to tidal restoration in the Herring River Estuary, MA, considering present and future sea levels

Coastal salt marshes are crucial ecosystems that provide habitat for a variety of species, improve water quality, and play a major role in the global carbon cycle. However, many salt marshes have been severely damaged by human activities such as diking and draining for urban development. Recently, there has been a noticeable shift toward the prioritization of coastal marsh restoration to re-establish their ecosystem services. The removal of anthropogenic barriers such as dikes, sluices, and culverts is a critical component of many projects because it allows for the restoration of tidal flow to support natural hydrologic regimes and salinity conditions, which play a dominant role in determining the ecological and biogeochemical functioning of marshes. This study examines how proposed removal of hydraulic structures will influence the hydrologic potential for marsh restoration in the Herring River Estuary in Cape Cod, Massachusetts, USA. Construction of dikes, roadways, and low-capacity culverts over the last century has substantially restricted tidal flow in the Herring River Estuary, leading to degradation of salt marsh habitat. The estuary is now undergoing the first phase of a restoration project to re-introduce natural hydrologic conditions, increase salinity, and restore salt marsh habitat. To assess how the Herring River Estuary will respond to human- and climate-driven modifications, we develop and apply a validated hydrodynamic model to simulate the complex tidal and salinity dynamics of the estuary under a range of restoration and sea level rise scenarios. We then quantify how salinity and critical hydrologic variables, including tidal range and depth of mean high water, will evolve for various restoration scenarios considering present and future sea levels. The results of this research can inform coastal management and restoration plans that re-create the natural functioning of the system while protecting critical infrastructure and reducing the risk of restoration failure.

Massachusetts↗
USGS2015

A linear relationship between wave power and erosion determines salt-marsh resilience to violent storms and hurricanes

Salt marsh losses have been documented worldwide because of land use change, wave erosion, and sea-level rise. It is still unclear how resistant salt marshes are to extreme storms and whether they can survive multiple events without collapsing. Based on a large dataset of salt marsh lateral erosion rates collected around the world, here, we determine the general response of salt marsh boundaries to wave action under normal and extreme weather conditions. As wave energy increases, salt marsh response to wind waves remains linear, and there is not a critical threshold in wave energy above which salt marsh erosion drastically accelerates. We apply our general formulation for salt marsh erosion to historical wave climates at eight salt marsh locations affected by hurricanes in the United States. Based on the analysis of two decades of data, we find that violent storms and hurricanes contribute less than 1% to long-term salt marsh erosion rates. In contrast, moderate storms with a return period of 2.5 mo are those causing the most salt marsh deterioration. Therefore, salt marshes seem more susceptible to variations in mean wave energy rather than changes in the extremes. The intrinsic resistance of salt marshes to violent storms and their predictable erosion rates during moderate events should be taken into account by coastal managers in restoration projects and risk management plans.

Proceedings of the National Academy of Sciences of↗
USGS2021

Global-scale changes to extreme ocean wave events due to anthropogenic warming

Extreme surface ocean waves are often primary drivers of coastal flooding and erosion over various time scales. Hence, understanding future changes in extreme wave events owing to global warming is of socio-economic and environmental significance. However, our current knowledge of potential changes in high-frequency (defined here as having return periods of less than 1 year) extreme wave events are largely unknown, despite being strongly linked to coastal hazards across time scales relevant to coastal management. Here, we present global climate-modeling evidence, based on the most comprehensive multi-method, multi-model wave ensemble, of projected changes in a core set of extreme wave indices describing high-frequency, extra-tropical storm-driven waves. We find changes in high-frequency extreme wave events of up to ∼50%–100% under RCP8.5 high-emission scenario; which is nearly double the expected changes for RCP4.5 scenario, when globally integrated. The projected changes exhibit strong inter-hemispheric asymmetry, with strong increases in extreme wave activity across the tropics and high latitudes of the Southern Hemisphere region, and a widespread decrease across most of the Northern Hemisphere. We find that the patterns of projected increase across these extreme wave events over the Southern Hemisphere region resemble their historical response to the positive anomaly of the Southern Annular Mode. Our findings highlight that many countries with low-adaptive capacity are likely to face increasing exposure to much more frequent extreme wave events in the future.

Environmental Research Letters↗